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JOURNAL OF TRANSPORTATION
of the Institute of Transportation Engineers
VOLUME 6, ISSUE 1
Advancing transportation knowledge and
practices for the benefit of society
A
EDITORIAL BOARD
Senior Editor
Dr. Lester A. Hoel, P.E., FITE
L.A. Lacy Distinguished Professor of
Engineering Emeritus
University of Virginia
Assistant Senior Editor
Dr. Dennis L. Christiansen, P.E., FITE
Director
Texas A&M Transportation Institute
Texas A&M University System
Dr. Max Donath
Professor of Mechanical Engineering and
Director, Intelligent Transportation Systems
Institute
University of Minnesota
Dr. Adib Kanafani
Professor of the Graduate School
University of California, Berkeley
Dr. John M. Mason, Jr., P.E., FITE
Vice President for Research and Economic Development
Auburn University
Dr. Kumares C. Sinha, P.E., FITE
Olson Distinguished Professor
School of Civil Engineering
Purdue University
Dr. Joseph M. Sussman
JR East Professor of Civil and Environmental
Engineering and Engineering Systems
Massachusetts Institute of Technology
Dr. C. Michael Walton, P.E., FITE
Professor of Civil Engineering
Ernest H. Cockrell Centennial Chair in Engineering
Civil Engineering Department
University of Texas at Austin
ASSOCIATE EDITORS
Dr. Ardeshir Faghri
Professor & Director
of Delaware Center For
Transportation
University of Delaware
Dr. Jon D. Fricker, P.E. (FITE)
Professor
Purdue University
Dr. Peter G. Furth
Professor
Northeastern University
Dr. James L. Gattis, P.E.
Professor
University Of Arkansas
Dr. Bruce N. Janson
Professor
University of Colorado
Dr. B. Kent Lall, P.E.
Professor
Portland State University
Dr. Thomas Mulinazzi P.E.,
FITE
Professor
University of Kansas
Dr. Errol C. Noel, P.E., FITE
Professor
Howard University
Dr. Martin T. Pietrucha, P.E.,
FITE
Director, The Larson Institute
Pennsylvania State University
Dr. Mitsuru Saito, P.E., FITE
Professor
Brigham Young University
Rhonda K. Young, P.E.
Associate Professor
University of Wyoming
Dr. William Young, P.E.,
FITE
Professor
Monash University
Dr. William J. Sproule,
P.Eng., FITE
Professor
Michigan Tech University
Dr. William C. Taylor, P.E.
Professor
Michigan State University
STAFF
Marianne Saglam
Managing Editor
Courtney Day
Editorial Assistant
The Journal of Transportation of the Institute of Transportation Engineers is circulated electronically yearly by the Institute of Transportation
Engineers, 1627 Eye Street, NW, Suite 600, Washington, DC 20006 USA, phone: 202-785-0060. ©2014 Institute of Transportation
Engineers. All rights reserved except for brief quotation with attribution. The views expressed in the articles are those of the authors
and do not reflect official ITE policy unless so stated. ISSN 2162 1616. Journal of Transportation of ITE is distributed free electronically
to ITE members. Issues may be downloaded at www.ite.org/JOT.
of the Institute of Transportation Engineers
VOLUME 6 | NUMBER 1 | JULY 2014
CONTENTS
C
omparing Perceived and Actual Travel Time Savings on Freeways with Managed Lanes
1
By Prem Chand Devarasetty, Ph.D., Mark Burris, Ph.D., P.E., and Huang Chao, Ph.D., P.E.
T
ransforming the Washington, DC, USA,
Parking Meter Program Using a Lean Six
Sigma Improvement Process
15
By Soumya S. Dey, P.E., PMP
P
ublic Perception of Double Crossover Diamond Interchanges
33
By Kristy Jackson, Christopher Cunningham, P.E., Chunho Yeom,
Joseph E. Hummer, Ph.D., P.E., and Adam Kirk, P.E., PTOE, AICP
A
Methodology Using GPS to Inventory University Campus Parking
55
By Brian Maleck, Wayne A. Sarasua, Ph.D., P.E., Jennifer Ogle, Ph.D., P.E., and Kweku Brown
T
he Effect of Additional Lane Length on Double-Lane Roundabout Operation
By Samuel Hammond, Christopher Hunter, Ph.D., and Kevin Chang, Ph.D., P.E.
INSTITUTE OF TRANSPORTATION ENGINEERS 1627 Eye Street, NW, Suite 600, Washington, DC 20006 USA
P: 202.785.0060 F: 202.785.0609 www.ite.org
71
Comparing Perceived and Actual Travel Time
Savings on Freeways with Managed Lanes
By Prem Chand Devarasetty, Ph.D., Mark Burris, Ph.D., P.E., and Huang Chao, Ph.D., P.E.
Respondents to a 2010 revealed preference survey were asked questions related to their
recent travel on Houston’s Katy Freeway (Houston, TX, USA). One question asked if they
experienced any travel time savings by using the new Katy Managed Lanes (MLs). This study
examined any difference between their perceived and actual travel time savings. This study found
that travelers overestimated the travel time savings they experienced by traveling on the MLs by
a factor of 4. The magnitude of misperception varied with individuals, but the average individual
saved approximately 3 minutes and thought they saved nearly 12 minutes. Linear regression
models were fit to model the misperception of the travel time savings and found that both trip
characteristics and respondent socioeconomic characteristics had an effect on the magnitude of
misperception of travel time savings. Respondents’ trip purpose, gender, and income were found
to be significant predictors of how well they estimated their travel time savings.
Introduction
The emergence of managed lanes (MLs) in the United States provides transportation planners and
researchers an opportunity to better understand how travelers value their time. Since MLs offer
an uncongested, faster, paid alternative to general purpose lanes (GPLs), it is possible to observe
the amount of toll travelers are willing to pay to save travel time on the MLs. This comparison has
the advantage of both sets of lanes being in the same highway corridor with similar entry and exit
opportunities. Even with this relatively straightforward comparison, there are still difficulties in
determining the value travelers place on their travel time savings. Two of the larger issues include (1)
the value travelers place on the added reliability of the MLs and (2) the fact that the amount of time
1
the travelers think the MLs save them may differ from reality. This paper takes an in-depth look at
the second issue.
This research compared data collected on actual travel conditions along Katy Freeway to data
obtained as part of a survey of Katy Freeway travelers. The survey data included questions regarding
the respondent’s most recent trip on the Katy Freeway along with the amount of time they thought
the MLs saved them plus several stated preference questions.
Literature Review
Understanding traveler behavior, and particularly travelers’ willingness to pay for travel time savings,
has been an important area of research going back to the late 1960s.1–3 Some of the early efforts to
determine travelers’ value of time focused on revealed preference data, including the choice between
modes.2,4 However, those comparisons clearly have many additional, and critical, differences other
than just cost and time.
More recent efforts have frequently used stated preference data from surveys to estimate value
of time, controlling for as many other factors as possible.5–9 In the stated preference approach,
several hypothetical travel scenarios or travel alternatives with different travel times and trip costs
are presented to respondents, and they are asked to choose the alternative that best suits their
travel. From the stated preference data, discrete choice models are fit to estimate the respondents’
willingness to pay.
Both revealed preference and stated preference approaches have their strengths and weaknesses.10
Since the revealed preference approach relies on the revealed responses, it is impossible to get
revealed preference data on a facility that does not exist, whereas in the stated preference approach,
since the scenarios can be hypothetical, it is possible to find travelers’ preference among choices
that include a nonexistent facility. However, this is also a major weakness of the stated preference
approach, since the stated preference approach includes hypothetical choices and not actual choices.
Making the actual decision is more complex compared to answering a hypothetical scenario, since
the consequences of the decision (benefits or loss) are experienced.10
There is abundant literature with both revealed preference and stated preference approaches used to
estimate travelers’ willingness to pay for travel time savings.4,5,11–14 Value of the estimated willingness
to pay varied by the type of the approach used. There were a few willingness-to-pay studies conducted
on MLs, but some of those found that the median willingness-to pay-values estimated using stated
preference data were approximately half the values estimated using revealed preference data.5,13 Two
possible explanations were given by Brownstone and Small for this underestimation of willingness
to pay by stated preference approaches.15 One explanation is that people have time inconsistency
in their actual behavior, but not in their hypothetical behavior. In actual behavior, people may
generally prefer to choose the free lane, but other time constraints may come into play and they end
up needing to take the toll lane. However, they overlook those constraints while answering the stated
preference questions and thus choose the toll road more often in real life than in hypothetical stated
preference questions. In other words, in the stated preference question the traveler answers based on
their typical trip. But in real life some of the trips may be hurried or pressed for time. On those few
trips they do choose the toll lane.6
The other possible explanation is one of the major criticisms against the revealed preference approach.
Travelers have difficulty reporting their actual travel times and travel time savings. Rather, they tend
to over- or underestimate the travel time savings they experienced. In the studies conducted on SR
91 and I-15, when travelers were asked to report the travel time savings they obtained when using the
express lanes, their responses were typically about twice as much as the average travel time savings
2
THE INSTITUTE OF TRANSPORTATION ENGINEERS
in these lanes.15,16 This seems to indicate that people tend to overestimate their travel time savings.
However, these previous studies used the average time saved compared to the reported time saved.
The studies did not have information on how much time was saved during the exact date and time
the trip was taken. It is possible, although unlikely, that the travelers reporting their travel time
savings did indeed save as much time as they thought they did, and they just happened to travel
during some pockets of extreme congestion. Our research removed this potential explanation by
comparing the actual travel time of travelers on the Katy Freeway during the time of their trip to
their estimate of time saved.
Steimetz found that travelers give a value for congested travel time that is twice as much as for
noncongested travel time.17 This may be a possible explanation for overestimation of the travel
time savings. Psychologists also argue that the misperception of time depends on the magnitude
of the duration. Fortin and Rousseau stated that short intervals of time tend to be overestimated
and long intervals of time tend to be underestimated.18 Since the revealed preference approach is a
common method of estimating the willingness to pay for travel time savings, there is a need to better
understand the travel time misperception among the travelers.
Objectives
The main objective of this research is to examine the difference between travelers’ perceived travel
time savings and their actual travel time savings. An effort will also be made to understand if the
magnitude of the misperception (over- or underestimation) of travel time savings is dependent on
trip characteristics and/or traveler characteristics.
This study uses data collected from a 2010 survey conducted on Katy Freeway travelers in Houston
and detailed traffic data collected on the roadway. Details on the survey data and actual ML usage
are described in the next section.
Data
The Katy Freeway is an eight-lane road with a three-lane one-way frontage road in each direction (see
Figure 1). In addition to these lanes, a portion (12-mile stretch) of the Katy Freeway near downtown
was designed with two MLs in each direction.19 The 12-mile Katy Freeway MLs extend from west of
SH6 to the I-10/I-610 interchange (see Figure 2). The MLs are open to both single-occupant vehicles
(SOVs) and high-occupancy vehicles (HOVs). The SOVs pay a toll to use the MLs at all times, while
HOVs only pay a toll during off-peak hours.
3
Figure 1. Katy Freeway (a crash occurred downstream causing this congestion,
which also allowed for easy identification of the lanes).
Figure 2. Katy Freeway managed lanes and automatic vehicle identification sensor locations.
Source: TxDOT. Katy Freeway Website, Texas Department of Transportation. Available: www.katyfreeway.org.
[Accessed May 15, 2009.]
4
2010 Katy Freeway Survey
The survey was posted on a Texas A&M Transportation Institute server and was made available for
public access through the Katy Freeway website. The data collection process started on June 1, 2010,
and continued until July 15, 2010. Residents of Houston who use the Katy Freeway on a regular basis
or have used it recently were encouraged to participate in the survey. The existence of the survey was
advertised to the public through online and news media. To increase participation in the survey,
two gas cards worth $250 each were given to two randomly chosen respondents. In addition to the
website ads, the Harris County Toll Road Authority added a brief note regarding the existence of
the survey to its monthly account e-notices. E-mails were also sent to the 3,077 respondents from a
previous (2008) Katy Freeway survey who had indicated an interest in participating in a follow-up
survey.20 A total of 4,919 responses were obtained from the survey. However, only 3,325 of those
4,919 responses were completed to a point where they were useful for analysis.
The 2010 survey questionnaire consisted of five sections. The first section asked the respondents
details about their most recent trip on the Katy Freeway. About half of the respondents were asked
about their trip toward downtown Houston and the other half about their trip away from downtown.
Respondents were asked what day of the week the trip occurred on, when the trip began, when it
ended, where the respondent got on and off the Katy Freeway, the type of vehicle, etc. Since the
survey was administered online, the date the survey was taken was also known. Knowing the date the
survey was taken, combined with the day of week and time of day the respondents indicated their
last trip occurred, means we know the most likely date and time of their most recent trip. There is no
guarantee that this is the correct date of the trip, since the questionnaire asked travelers to indicate
the day of the week of their most recent trip. For many, that would be the most recent day of the
week indicated in the survey (for example, the most recent Monday). But for infrequent Katy Freeway
travelers that may have been 2 or 3 weeks prior. Based on their frequency of use of the Katy Freeway
(see Table 1), more than 96 percent of respondents traveled on the Katy Freeway during the most
recent week, and therefore their day and time of travel was known.
Table 1. Survey respondents’ frequency of Katy Freeway travel.
Number of Trips on the
Katy Freeway during the
Last Full Week
Percentage of
Respondents
0
3.3
1
3.9
2
4.7
3
2.9
4
0.1
5
19.6
7
0.1
8
1.6
10
23.4
12
1.4
15
21.9
20 or more
17.1
In the second section, respondents were introduced to the new MLs and were asked about their use
of those lanes.14 The third section was intended to identify the risk-taking behavior or preferences
5
of the respondents with one risk-aversion question presented in the survey. In the fourth section,
the respondents were presented with stated preference questions, and the last section consisted of
questions regarding socioeconomic characteristics of the respondents.
Of the 3,325 respondents, 1,004 indicated that they had used the MLs on their recent trip. Although
1,004 respondents indicated that they used the MLs, 277 respondents’ entry and/or exit locations did
not match ML entry or exit locations. Twenty respondents did not provide some of the information
(entry and/or exit location, day of the most recent trip, start time of the trip) required to extract
the actual travel time savings. Those respondents were removed from further analysis, leaving 707
responses from travelers who used the MLs on their most recent trip.
These 707 survey responses were then weighted to better reflect both the frequency of travel on the
Katy Freeway and the percentage of trips that were on the MLs. Using the data from the automatic
vehicle identification (AVI) sensors (see Figure 2), it was possible to get an estimate of how frequently
drivers with transponders are observed using the Katy Freeway and what percentage of their trips
are on the GPLs versus the MLs (see Table 2). This is only an estimate, since the AVI sensors do not
capture 100 percent of the trips on the GPLs. Note that this sample of survey respondents comprised
only those respondents who used the MLs. Therefore, only those travelers who actually used the MLs
at least once during the period of this survey were included in the control totals for the weights.
In addition, we found 57 respondents who indicated 0 trips on the Katy Freeway in the prior week
but did indicate trips on the Katy MLs. These respondents did not read or pay attention to the
instructions in the question that indicated for them to count all trips on the Katy Freeway (GPLs or
MLs). Another 7 respondents did not include their number of trips, and 28 respondents indicated
0 trips on the MLs. To get an accurate weight, these respondents also had to be removed, leaving
617 responses. Despite losing some data and the inherent problems with AVI sensors on the GPLs,
weighting the survey sample to better reflect the observed (AVI) data should improve the survey’s
ability to represent all ML travelers based on their frequency of Katy Freeway use and percentage of
ML use. However, note that the same analyses were run on unweighted data, and the results were
nearly identical to the results shown in this paper that are based on weighted data.
Table 2. Weighting of survey responses.
Observed Percentage/Survey Percentage of Travelers = Weight
Katy Freeway Trips on the MLs
Katy Freeway usage
(All Lanes)
Low (1 trip/week)
Low (1 or 2 trips/week)
Medium (2 to 4 trips/week)
High ( 5+ trips/week)
53.8/12.0 = 4.49
0.4/7.3 = 0.05
0.00/0.2 = 0.00
Medium (3 to 9 trips/week)
29.3/3.6 = 8.22
7.3/17.8 = 0.41
2.2/10.9 = 0.20
High (10+ trips/week)
2.9/1.6 = 1.78
2.1/8.1 = 0.25
2.0/38.8 = 0.05
a
As an example, 53.8 percent of Katy Freeway travelers used the Katy Freeway (any lane) one or two times per
week and the Katy MLs once per week. The survey included 12 percent of respondents who indicated that
frequency of Katy Freeway use. Therefore, that group of survey respondents had a weight of 4.49. Remember,
for both the survey and for the real-world data we have limited the sample to those travelers who used the MLs
at least once.
a
Observed Traffic Data
Two types of vehicle sensors—Wavetronix and AVI—are installed along the Katy Freeway by Texas
Department of Transportation (TxDOT) (see Figure 2 for AVI sensor locations). These sensors
6
collect data on the speed and volume on all the lanes on the Katy Freeway. These data were used to
estimate the actual travel time savings offered by the MLs.
Travel Time
Time taken to travel various sections of the Katy Freeway on the MLs and GPLs was calculated using
the AVI data. AVI sensors are located along the MLs and the GPLs in each direction of travel on the
Katy Freeway (see Figure 2). Each AVI sensor identifies each transponder-equipped vehicle based on
the vehicle’s unique transponder ID and records the time when the vehicle is identified. The vehicle
IDs recorded at an AVI sensor are matched with the adjacent AVI sensor data, and the time difference
each vehicle required to cover the distance between those sensors is known. There are more than 1
million instances per day recorded in Houston and approximately 170,000 observations per day on
the Katy Freeway—more than sufficient to obtain reliable travel times. For each 15-minute period, the
average travel time for all identified vehicles between those two sensors was calculated and recorded.
These travel times were used to calculate the actual travel time savings offered by the MLs.
Results
The final data included the responses from the 617 survey respondents, and all analyses were
weighted based on the weights shown in Table 2. In the survey, the respondents were asked how
much travel time they thought they saved by traveling on the MLs. Their perceived travel time
savings are presented in Table 3. Approximately 97 percent of the respondents reported that they
had experienced some travel time savings. From the survey question regarding their most recent trip,
we obtained their Katy Freeway entry and exit locations. This information was used to determine
the total length of their trip and the length of their trip in the portion of the freeway that had MLs.
Table 3. Respondents’ perceived travel time savings.
Perceived Travel Time Savings
Percentage of Respondents
0 min.
3.3
1 to 2 min.
8.6
3 to 5 min.
22.6
6 to 10 min.
25.1
11 to 15 min.
23.3
16 to 20 min.
8.1
21 to 25 min.
1.2
26 to 30 min.
6.6
More than 30 min.
Weighted actual averagea
1.2
11.8 min.
Note that this weighted average uses the actual responses prior to
the responses being grouped in bins as in this table.
a
As a comparison, from the observed travel time data, the average travel time savings (over all nonholidays for all of 2009) were estimated for the 11.4-mile section of the Katy Freeway for both the
eastbound and westbound directions (see Figure 3). The average travel time savings varied by time
of day, but the maximum average travel time savings was approximately 8 minutes in the westbound
direction and approximately 6 minutes in the eastbound direction. Average travel time savings
outside of the peak period was considerably less than 6 to 8 minutes.
7
Figure 3. Average travel time savings on the MLs by time of day for all of 2009.
This research assumes that these values are a representative sample of drivers’ true perceptions
regarding the amount of time saved when using the MLs. However, when using survey data, there are
always potential biases. In this survey there may be a sample bias consisting of travelers who really
like using MLs because they think they save so much time—thus making them more likely to take
the survey. There could also be a respondent bias, as respondents are justifying their own use of MLs
by indicating an impressive amount of travel time savings. In an effort to minimize these potential
impacts, (1) we examined the data for any responses that appeared to be from the same person (none
were found), (2) the results were weighted to better reflect ML travelers (as discussed above), and (3)
any respondents who indicated a time savings greater than 30 minutes were removed.
Next, the perceived travel time savings for respondents’ most recent trip (Table 3) (which were
obtained from the survey) will be compared to their actual travel time savings. The actual travel time
savings for that recent trip was obtained by using the respondents’ recent trip information (survey
date, day of week of the most recent trip, entry and exit locations, and start time of the trip) provided
in the survey and then looking up the actual travel time savings obtained from sensor data. For
example, if a respondent had taken the survey on June 16, 2010, and indicated that their most recent
trip was on a Friday and it started at 8:00 a.m., then the most likely date of his/her recent trip would
be the previous Friday, that is, June 11, 2010. This was based on our assumption that since most of
the respondents were frequent users of the Katy Freeway (see Table 1), their most recent trip reported
on the survey likely occurred within the seven days prior to their taking the survey. In addition,
many travelers did not travel the full length of the MLs. Only the travel time savings between the
respondents’ entry to and exit from the Katy Freeway was included in the actual time savings.
The average actual travel time savings was only approximately 25 percent of the average perceived
time savings. This is similar to what has been found in previous studies of MLs, although previous
studies found the estimated actual time savings to be closer to 50 percent of perceived time savings.5,13
However, with the previous studies there is the possibility that those travelers happened to travel
when the GPLs were particularly slow and thus may have saved as much time as they perceived.
8
Previous studies did not have access to actual trip times, so our study is able to investigate this
difference in perceived versus actual time savings in greater depth.
A scatter plot of the perceived and the observed average travel time savings was created (see Figure 4).
It can be seen that the perceived travel time savings is much higher than the average observed travel
time savings. This plot shows the magnitude of the overestimation of the travel time savings and
raises an interesting question: Can revealed preference responses be used for policy analysis? It can
be seen that few respondents underestimated travel time savings and a majority of the respondents
overestimated the travel time savings. The weighted average difference between perceived and
observed travel time savings was around 8.8 minutes when all data are included (8.5 minutes when
responses greater than 30 minutes are excluded; see the following discussion). (Note that the result
for unweighted data excluding values greater than 30 minutes was 9.6 minutes, slightly larger than
with weighted data.)
Figure 4. Perceived vs. average observed travel time savings.
To examine whether the magnitude of over- or underestimation of travel time savings is related to
any of the respondents’ trip characteristics or their socioeconomic characteristics, a linear regression
model was estimated (see Table 4 and Equation 1). A small number of respondents (approximately
1.2 percent) indicated that they saved more than 30 minutes by traveling on the MLs. However, more
than 30 minutes of travel time savings for a 12-mile section seems extreme, and it can also be seen
from Figure 4 that 99.9 percent of the time the observed travel time savings was less than 20 minutes.
Therefore, those respondents who indicated that they saved more than 30 minutes were excluded
from the model, leaving 597 respondents in the model.
9
The dependent variable for the model is the difference between the perceived and observed travel
time savings. Trip purpose, distance traveled on the MLs, age, gender, income, direction of travel,
education, and number of trips on the Katy Freeway in the previous week were considered as
independent variables. However, many of the variables were found not to be significant in predicting
the magnitude of the difference in perceived travel time savings. Misperception of the travel time
savings was higher for female respondents than male respondents. Respondents on recreational
trips perceived travel time savings that were more accurate than those respondents with other trip
purposes. This might be because travelers who are traveling for recreation are generally not pressed
for time and can more clearly internalize the difference in travel speeds. Or it may be because they
more often travel at off-peak times, when the speeds on the two types of lanes are closer, making
comparison easier. It is interesting to see that lower-income (annual household income less than
$25,000) respondents did not overestimate the travel time savings as much as mid- and high-income
respondents. A possible explanation for this might be that lower-income respondents are more
carefully judging what value they are receiving (in time savings) for the toll that they pay, since it is a
larger portion of their spending money.
Table 4. Linear regression model for difference between perceived and observed
travel time savings.
Parameter
Estimate
p Value
Intercept
8.0
0.00
Annual income
-3.0
0.00
Trip purpose is recreational
-1.1
0.05
Female
2.5
0.00
< $25,000
Perceived Travel Time Savings – Actual Observed Travel Time Savings=
8.0 – 3.0×Annual Income<25,000 – 1.1×Trip PurposeRecreational+2.5×Female (Equation 1)
Where: Annual Income < $25,000 = 1 if annual household income was less than $25,000; 0 otherwise
Trip PurposeRecreational = 1 if the traveler was on a recreational trip; 0 otherwise
Female = 1 if the traveler was female, 0 otherwise
Conclusions
The objective of this research was to examine the difference between travelers’ perceived travel
time savings and their actual travel time savings, and to better understand the magnitude of any
misperception of the travel time savings. This research used data from a 2010 survey on Katy Freeway
travelers. In the survey, respondents were asked for information on their most recent trip on the Katy
Freeway, including the date, time, and how much travel time they think they saved by using the MLs.
This provided their perceived travel time savings and enough information to identify their (most
likely) actual travel time savings using sensor data from the Katy Freeway.
The perceived travel time savings varied considerably across the respondents. Nearly 97 percent of
the respondents indicated that they experienced some travel time savings. Very few respondents
underestimated travel time savings, and a majority of the respondents overestimated the travel time
savings. On average, respondents perceived they saved approximately 12 minutes when they really
saved closer to 3 minutes, estimating that they saved nearly four times as much as they actually did.
These results are higher than in the limited literature in the area, where perceived travel time savings
are approximately twice the average maximum savings in the peak period.
10
Linear regression models were fit to model the magnitude of over- and underestimation of the
travel time savings. Among the trip characteristics, only trip purpose (work or recreation) was found
to be a significant predictor of the degree of misperception of travel time savings. Respondents’
characteristics, including gender and income, were also found to be significant in predicting the
degree of misperception of travel time savings. This study shows that there is considerable difference
between perceived and actual values.
This research has shown that travelers do have difficulty estimating the time they save while using
MLs. They greatly overestimate the amount of time saved. However, exactly how to incorporate this
understanding in mode choice models or traffic revenue estimates is unknown. It may well be that
even though travelers are saving a small amount of time, they value that time savings (and avoiding
congestion) much higher—possibly similar to their amount of perceived travel time savings. This is
an area that needs additional research. However, with empirical ML data now available to examine,
we are gaining a better understanding of how drivers perceive and value travel time savings.
Acknowledgments
The authors recognize that support for this research was provided by a grant from the U.S. Department
of Transportation, University Transportation Centers Program to the Southwest Region University
Transportation Center, which is funded, in part, with general revenue funds from the state of Texas.
The authors would also like to thank Harris County Toll Road Authority, Houston-Galveston Area
Council, and Houston Transtar for their help in spreading the word about the survey. The authors
would also like to thank Richard Trey Baker for all the support he provided in hosting the survey.
Three anonymous reviewers from ITE also helped to make this paper better through their comments.
Any errors and omissions are the responsibility of the authors.
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Choice Model for Houston, Texas.” Transport Policy, Vol. 18, No. 4 (2011): 595–603.
7.
Patil, S., M. Burris, W.D. Shaw, and S. Concas. “Variation in the Value of Travel Time Savings
and Its Impact on the Benefits of Managed Lanes.” Transportation Planning and Technology, Vol. 34,
No. 6 (2011): 547–65.
8.
Devarasetty, P., M. Burris, and W.D. Shaw. “The Value of Travel Time and Reliability-Evidence
from a Stated Preference Survey and Actual Usage.” Transportation Research Part A, Vol. 46 (2012):
1227–1240.
11
9.
Devarasetty, P., M. Burris, and W.D. Shaw. “Do Travelers Pay for Managed Lane Travel as
They Claimed They Would? A Before and After Study of Houston Katy Freeway Travelers.”
Transportation Research Record: Journal of the Transportation Research Board, No. 2297 (2012): 56–65.
10. Whitehead, J.C., S.K. Pattanayak, G.L. Van Houtven, and B.R. Gelso. “Combining Revealed
Preference and Stated Preference Data to Estimate the Nonmarket Value of Ecological Services:
An Assessment of the State of the Science.” Journal of Economic Surveys, Vol. 22, No. 5 (2002):
872–908.
11. Hensher, D.A. “Measurement of the Valuation of Travel Time Savings.” Journal of Transport
Economics and Policy, Vol. 35 (2001): 71–98.
12. Black, I.G. and J.G. Towriss. Demand Effects of Travel Time Reliability. London: UK Department of
Transportation, Her Majesty’s Stationery Office, 1993.
13. Small, K.A., C. Winston, and J. Yan. “Uncovering the Distribution of Motorists’ Preferences for
Travel Time and Reliability.” Econometrica, Vol. 73 (2005): 1367–1382.
14. Burris, M., P. Devarasetty, and W.D. Shaw. Managed Lane Travelers-Do They Pay for Travel As They
Claimed They Would? College Station, TX: Texas A&M Transportation Institute, The Texas A&M
University System, 2011.
15. Brownstone, D. and K.A. Small. “Valuing Time and Reliability: Assessing the Evidence from
Road Pricing Demonstrations.” Transportation Research Part A: Policy and Practice, Vol. 39 (2005):
279–293.
16. Sullivan, E., K. Blakely, J. Daly, J. Gilpin, K. Mastako, K. Small, and J. Yan. “Continuation Study
to Evaluate the Impacts of the SR91 Value-Priced Express Lanes: Final Report.” California
Polytechnic State University at San Luis Obispo, December 2000, [Online]. Available:
http://ceenve.ceng.calpoly.edu/sullivan/SR91.
17. Steimetz, S.S.C. “Defensive Driving and the External Costs of Accidents and Travel Delays.”
Working paper. Department of Economics, University of California at Irvine, April 2004.
18. Fortin, C. and R. Rousseau. “Interference from Short-Term Memory Processing on Encoding
and Reproducing Brief Durations.” Psychological Research, Vol. 61 (1998): 269–276.
19. TxDOT. Katy Freeway Website, Texas Department of Transportation, [Online]. Available:
www.katyfreeway.org. [Accessed May 15, 2009.]
20. Burris, M. and S. Patil. Estimating the Benefits of Managed Lanes. College Station, TX: Texas A&M
Transportation Institute, The Texas A&M University System, 2009.
12
Prem Chand Devarasetty received his Ph.D. from Texas A&M University. He is currently
working as a senior risk analyst at PayPal Data Services in Austin, TX, USA. He has
published several research articles and reports on the value managed lane travelers place
on travel time and travel time reliability. His research interests are in toll road pricing
and in understanding travelers’ behavior toward toll road pricing.
Mark Burris, Ph.D., P.E., is the Herbert D. Kelleher Professor in the Zachry Department
of Civil Engineering at Texas A&M University and a research engineer with the Texas
A&M Transportation Institute. His main area of interest is traveler behavior in response
to pricing, particularly congestion (or value) pricing. He has been, and continues to
be, involved in many projects in this area and has published extensively in this area of
research. He is a member of ITE.
Chao Huang, Ph.D., P.E., is a transportation system modeler with C&M Associates in
Dallas, TX, USA. His main area of interest is traffic and revenue (T&R) forecasting and
congestion pricing in the toll facility. He has been involved in various T&R studies with
C&M and research projects with a focus on toll road/managed lane operating policy and
toll facility users’ response to price at the Texas A&M University. He is a member of the
TRB Committee on Transportation Economics, and his experience includes stated preference survey
design, benefit–cost analysis, transportation investment analysis, and traffic demand forecasting.
13
Transforming the Washington, DC, USA, Parking Meter
Program Using a Lean Six Sigma Improvement Process
By Soumya S. Dey, P.E., PMP
The District Department of Transportation (DDOT) is responsible for maintaining and
operating more than 18,000 metered on-street spaces in Washington, DC, USA. The program went
through significant changes in 2009 and 2010 including two rate adjustments, reintroduction of
meter enforcement on Saturdays, and extending hours of meter operation to 10:00 p.m. in highdemand areas. These changes caused operational problems for the department and frustration for the
customers. This paper describes how DDOT applied Lean Six Sigma (LSS) processes and techniques
to dramatically transform its on-street parking meter program. The paper introduces the concept
of LSS and discusses how some of the analytical techniques and concepts were applied. Techniques
such as root cause analysis, process capability, mean testing, Pareto analysis, and process mapping
were used to identify fundamental problems with the program and assets. Once the problems were
identified, DDOT quickly developed a strategic vision for the future and aggressively implemented the
vision. Applying LSS techniques has reaped significant rewards for DDOT within a very short period
of time. These benefits include higher customer satisfaction through enhanced payment options, a
lower number of service requests, better system uptime, more proactive management of assets, better
executive visibility, and increased revenue. Washington, DC’s parking program is now recognized as
one of the most innovative, forward-thinking programs in the country. The success of applying LSS in
parking has encouraged DDOT to apply this concept in other program areas as well.
15
Background
The District Department of Transportation (DDOT) is responsible for developing and maintaining
a cohesive, sustainable transportation system that delivers safe, affordable, and convenient ways to
move people and goods—while protecting and enhancing the natural, environmental, and cultural
resources of the nation’s capital. As an agency, DDOT is unique—it has the attributes of both a state
and municipal department of transportation. As part of this mission, DDOT manages and operates
all the transportation assets in Washington, DC, USA. These assets are valued at $44 billion.1 Over
the past few years, DDOT has gone through a paradigm shift in how it manages its assets. These
techniques include performance-based contracting (with incentive/disincentive and liquidated
damages), application of data mining and process enhancement techniques such as Lean Six Sigma
(LSS), and participating in constructive partnering forums with the private sector for more costeffective service delivery.
DDOT is responsible for maintaining and operating more than 18,000 metered on-street spaces in
Washington, DC. Until late 2010, these spaces were controlled by two basic asset types: (1) traditional
single-space meters (SSMs) that each cover one space and (2) multi-space meters (MSMs) that cover
approximately an average of eight metered spaces. The MSMs are networked while the SSMs are
mechanical, non-networked assets. Moreover, the SSMs are more than 10 years old and at the end of
their useful life. From a customer’s perspective, credit cards were accepted as a payment option (in
addition to coins) only at the MSMs. For the rest of the assets, only coins were accepted. Up until late
2010 customers could pay by credit cards at only 23 percent of the metered spaces.
Between March 2009 and January 2010, the program underwent significant changes including two
rate adjustments, lifting of the Saturday moratorium on parking meter fees, and extending of the
duration during which meters are operational.2–4 These operational changes put significant stress on
a system that had assets that were beyond their useful life.
The changes also caused significant frustration among customers. Due to the rate adjustments, the
number of coin transactions on the system increased. This increased failure rates for the meters.
Consequently, customers frequently encountered broken meters.5 The rate increase also required
customers to carry more change. This caused additional frustration.6 Parking-related service requests
through Washington, DC’s centralized 311 system became the highest service request in DC. In
2010, the agency received approximately 200,000 parking meter–related service requests.7 Just to put
things in perspective, in 2009 DDOT received more parking meter–related service requests than the
Department of Public Works received as an entire agency.8 Also, the perception gap (the difference
between the percentage of on-time service delivery and customers’ perception about the level of
service delivery measured through a sample survey) for parking meters was at 55 percent.9 This
was the highest among all DDOT service categories. The press picked up on the negative customer
sentiment as well.10,11 The program became a burning issue for the department and the District of
Columbia. There was significant pressure on the agency to enhance the program.
This paper discusses how DDOT adopted an LSS-based approach to identify fundamental problems
with its assets and the program, developed a strategic approach to enhance the program, implemented
the recommendations, and achieved significant enhancement. It discusses some of the analytical
tools that were used in the process.
What is Lean Six Sigma?
Lean and Six Sigma are process improvement methodologies. Lean is a set of tools that is geared to
improving process flow while primarily focusing on the elimination of waste or non-value-added
16
activities from all business processes. Lean arose as a method to optimize auto manufacturing
(initially at Ford and Toyota). Lean focuses on eliminating seven sources of waste:12
1. Overproduction (manufacturing items ahead of demand);
2. Inventory (excess material and information);
3. Defects (production of off-specification products);
4. Transport (excess transport of work-in-process or products);
5. Motion (human movements that are unnecessary or straining);
6. Overprocessing (process steps that are not required); and
7. Waiting (idle time and delays).
Six Sigma specifically focuses on process variation. It is a methodology driven by understanding of
customer needs and the disciplined use of data, facts, and statistical analysis to improve and reinvent
organizational processes by reducing variation. Six Sigma evolved as a quality initiative to reduce variance
in the semiconductor industry (initially Motorola). From a purely statistical standpoint, a Six Sigma
process has 3.4 defects per one million opportunities.13 The statistical roots of the term Six Sigma have
become less important as Six Sigma has evolved into a comprehensive management system.
LSS is a combination of Lean and Six Sigma approaches. Despite their disparate roots, Lean and Six
Sigma share several fundamental commonalities including a focus on customer satisfaction, continuous
improvement, identification of root causes, and comprehensive employee involvement.14 LSS uses a databased approach to enhance workflow and business processes.
Though used primarily in the manufacturing sector, the concept of Lean and Six Sigma combined
has been applied successfully in the service sector as well.15 LSS for services is a business improvement
methodology that maximizes value by achieving the fastest rate of improvement in customer satisfaction,
cost, quality, process speed, and invested capital. LSS is a five-step process as shown in Figure 1.16 Each of
these processes has sample tools and procedures, as shown in Table 1.17
FIGURE 1. Lean Six Sigma process.
17
Table 1. Sample tools in Lean Six Sigma approach.
Define
Measure
Analyze
Improve
Control
Project definition
Hypothesis testing
Design of
experiments (DOE)
Control plan
Failure modes and
Basic statistics
(Measure of
central tendencies,
measure of
variation,
distributions, etc.)
effects analysis
(FMEA)
Graphical
techniques
Analysis of variance
(ANOVA)
Process mapping
Cause and effect
matrix
Means testing
Power & sample
size
Project closure
2k factorial design
Regression analysis
Confidence
intervals
Measurement
systems analysis
(MSA)
Capability analysis
Statistical process
control (SPC)
Literature review
LSS has been used extensively in the private sector. The author reviewed, among others, literature on LSS
application in the construction industry in Abu Dhabi, UAE,18 various service organizations (hospitals,
consulting, hotels, etc.) in Singapore,19 a production facility in Sweden,20 and a printing factory in
Ohio, USA.21 There are several documented uses of LSS across different levels of government as well.
Internationally, Randor discusses a framework that assesses tools and processes that are most relevant
and impactful when introducing Lean into a large government department in the United Kingdom.22
In the United States, federal agencies such as the Department of Defense, Environmental Protection
Agency, and Department of Energy; state agencies such as the Florida Department of Revenue; and
municipal agencies such as the City of Fort Wayne (Indiana), City of Hartford (Connecticut), and City
of Irving (Texas) have applied Six Sigma techniques to various components of their programs.23–25 Most
of the documented applications of LSS in the transportation industry have been in the area of logistics
and supply chain for humanitarian relief, airline, rental car, and rail operations.26,27 Lean techniques
have been used for the delivery and construction of infrastructure projects.28,29 However, as a concept,
LSS has not made significant inroads into the mainstream transportation engineering profession.
Change Framework
This section discusses the framework used by DDOT to transform its parking meter program. It was
a three-step process including (1) application of LSS to identify fundamental issues with the parking
program, (2) developing a vision for the future program and pilot testing state-of-the-art assets and
solutions to achieve those goals, and (3) implementation. The following three sections in this paper
discuss each of these three steps in the framework (shown in Figure 2).
18
Figure 2. Change Framework.
Application of Lean Six Sigma TOOLS
This section discusses how some of the tools in the LSS framework were applied to gain valuable
information and knowledge about DDOT’s parking meter assets.
Root Cause Analysis
There are several techniques that can be utilized for root cause analysis such as fishbone diagrams,
cause and effect mapping, and failure modes and effects analysis (FMEA). DDOT utilized cause
mapping to identify the “root causes” of the problems associated with the program. During this
process, it was important to distinguish between symptoms and causes. During the analysis it
became apparent that symptoms such as increase in the number of broken meters, broken meter
call volumes, and customer dissatisfaction were driven by four fundamental causes: aged assets,
non-communicating meters, increased coin transactions (because of the rate increases), and limited
payment options for customers (shown in Figure 3). Identifying the root causes was fundamental in
charting a future course for program enhancements.
19
Figure 3. Results of root cause analysis.
Control Chart for Call Volumes
The control chart is a tool that helps detect any extraordinary variation in the process—variation that
may indicate a problem or fundamental change in the process. Figure 4 shows a control chart for
the number of broken meter 311 calls received between February 2007 and April 2011. The control
chart shows the overall process mean (x) as well as the upper control limit (UCL) and lower control
limit (LCL). The UCL and LCL are three standard deviations from the mean. The chart also annotates
policy changes that likely impacted call volumes: the rate changes in April 2009 and January 2010 and
installation of networked SSMs in November 2010. It appears that the process has four distinct means:
■■
Between February 2007 and March 2009, the mean appeared to be between the overall mean (x)
and the LCL.
■■
Between March 2009 and January 2010, the mean jumped to between the overall mean (x) and the UCL.
■■
Between January 2010 and November 2010, the mean jumped to above the UCL.
■■
After new assets were introduced in November 2010, the mean dropped again to between the UCL
and the overall process mean (x).
Individual mean testing was conducted for each of the four time slices and indicated that the means
during the four periods were statistically different. This shows that external influences such as policy
changes and asset refresh affected the process.
20
Figure 4. Control chart for call volumes.
Pareto Analysis/Bad Actor Report
All service request calls to DC’s 311 system are fielded by the Office of Unified Communications,
entered into a service request system, and routed to appropriate agencies. DDOT analyzed parking
meter–related service request calls from the 311 system and performed a Pareto analysis. The analysis
(referred to within DDOT as the “bad actor report”) revealed that the worst 1,500 meters (8 percent
of assets) accounted for 40 percent of the call volume. (The worst meter is defined as the meter
that had the maximum number of 311 calls/service requests.) The 1,500 worst performing assets
averaged 25 calls per year. This implies technicians were dispatched to investigate these meters an
average of 25 times during the course of 1 year. The worst performing meter was “called-in” 95 times.
Ninety-five percent (1,425 out of 1,500) of the assets in the bad actor report were the oldest asset
types (SSMs). Figure 5 shows the distribution of call volume for the 1,500 worst performing meters.30
From a business and customer service standpoint, it made more sense to systematically replace these
aged assets with newer assets. The findings from this analysis were one of the major criteria for
prioritizing the asset refresh schedule.
Figure 5. Call distribution for 1,500 worst performing meters.
21
Mean Testing
Based on the Pareto analysis and the findings of the pilots, DDOT started replacing its worst
performing assets with newer, networked assets. Figure 6 shows how the call volumes for specific
groups of meters dropped after the old assets were replaced with new, networked assets. Hypothesis
testing of the mean call volumes before and after the installation revealed that the means were
statistically different.
Similar before and after mean testing was conducted on revenues for routes where new assets were
installed. The analysis revealed that asset refresh resulted in higher revenues as well.31 This was most
likely driven by two factors: (1) newer meters had better uptimes and were less likely to break down,
and (2) the newer, networked assets accepted credit cards, and hence customers had two options to
pay at these meters: coin or credit/debit card.
Figure 6. Mean testing for routes with new assets.
Process Capability
DDOT manages and operates the parking meter program using a performance-based asset
management contract. The contract requires the contractor to fix SSMs within 72 hours and MSMs
within 24 hours. It also requires an operability rate of 99 percent for MSMs and 97 percent for SSMs.
The contract allows incentives for exceeding the performance metrics and liquidated damages for
failing to meet the performance measures.
A capability analysis was conducted to ascertain whether the process was capable of meeting the 72
hours requirement. As shown in Figure 7, the contractor’s mean repair time was significantly below
22
the upper specification limit for SSMs (72 hours). The contractor was also meeting the 97 percent
operability requirement. Yet the program had a negative perception.
Figure 7. Capability analysis for meter repair process.
In examining the issue more closely, the team realized that there was a “measurement error” built
into how performance was being measured.
Measurement Error
Given that most of the assets are non-networked, operability and repair time were based on a work
order/service request system. This is largely a reactive system in that broken meters factor into the
operability equation only if they are “called in.” A broken meter that is not reported does not factor
into the operability calculation.
DDOT conducted some field observations based on a statistical sampling. The 95 percent confidence
interval for meter operability was between 82 percent and 90 percent, with a mean of 86 percent.
This is significantly lower than the 97 percent operability calculated through the work order system.
DDOT also conducted two independent “touch a meter” programs. During the program, DDOT
staff assessed the operability of its entire installed meter inventory (13,000 to 14,000 parking meters)
within a 1-week period. The operability of the meters using this effort was calculated to be between
80 percent and 85 percent. The measurement error helps explain the difference between the “ground
truth” and work order–based operability and helps explain the public frustration.
Process Flow Charts
DDOT also spent a considerable amount of time mapping out the various processes related to
parking and curbside management. The parking function in DDOT is very fragmented, with
individual groups responsible for policy, operations, signage, permitting, and enforcement. Process
mapping techniques revealed inefficiencies such as “hidden factories,” bottlenecks, and nonvalue-added activities. It was also apparent that there were delays whenever there was a hand-off
23
of responsibilities between different groups in DDOT. Process mapping allowed DDOT to get a
common understanding of the process and responsibilities and identify inefficiencies.32
Development of the Strategic Vision
Based on the findings of the LSS analysis, DDOT started the process of developing a strategic plan
and long-range vision for its metered on-street parking program. This section discusses the highlevel program goals and the pilot tests that were conducted to identify assets and programs that
would enable DDOT to reach the established goals.
Establishment of High-Level Program Goals
DDOT developed three high-level, simplistic goals for the parking meter program. Each goal was
subdivided into more detailed subgoals. These included:
■■
■■
■■
Improved customer service
●●
Multiple payment options
●●
Maximized convenience
●●
Real-time parking availability
●●
Fewer broken meters
Enhanced operational efficiency
●●
Dynamic pricing
●●
Real-time operational status
●●
Better uptime
●●
Lower operating cost
Better revenue management
●●
Minimized coin transaction
●●
Real-time auditing
Parking Pilots
In the summer of 2010, DDOT evaluated the state of the art in meter hardware, payment options,
and real-time occupancy sensing through a series of pilots. The pilots were conducted using a
competitive procurement process. DDOT tested two different configurations of MSMs (pay by space
and pay by license plate), credit card–accepting SSMs, occupancy sensors, and new payment options
such as pay by cell. The pilots were evaluated against the program goals, as shown in Table 2.33
24
Table 2. Assessment of pilots against program goals.
Program Goals
Pay by Cell
Smart SSM
Smart MSM
Multiple payment options
X
X
X
Customer convenience
X
X
X
Space Occupancy
Improved Customer Service
Real-time parking
availability
X
X
Fewer broken meters
X
X
X
X
X
X
Enhanced Operational Efficiency
Dynamic Pricing
X
Real-time operational
status
Better uptime
X
X
X
Lower operation cost
X
X
X
Minimized coin transaction
X
X
X
Real-time auditing
X
X
X
X
Better Revenue Management
X
Implementation
Based on the LSS analysis and the findings of the parking pilots in 2010, DDOT implemented a
series of changes to its parking meter program, with dramatic results. These included:
■■
Asset refresh—DDOT significantly increased the number of networked assets by procuring and
installing new, networked credit card–accepting SSMs and increased the coverage provided by MSMs.
■■
Launched a citywide pay-by-cell program—Following two very successful pilots, DDOT
launched a citywide pay-by-cell program in July 2011. The program turned out to be the most
successful pay-by-cell program in the country. As of May 2014, the program has 750,000
customers and has resulted in more than 15 million transactions accounting more than 40
percent of the annual parking revenue.34
■■
Issued a new contract for the next generation parking asset management—DDOT selected a
vendor for maintaining and managing its parking meter assets for the next 5 years. The contract
is structured as a performance-based contract with liquidated damages and incentive/disincentive
clauses. It is also structured to make sure that the city is not locked into paying for services that
it does not require. Recognizing that the asset mix and revenue mix would change substantially
over the next 5 years, the contract has fixed price elements, fixed unit prices by asset type for
maintenance, and a percentage fee for items such as coin collection and credit card processing.
It also requires the use of LSS techniques for program management and an integrated back-end
system for asset monitoring and management.35 The integrated back-end system would aggregate
all the data (operational, revenue, maintenance, etc.) from disparate assets (such as multiple meter
types, pay-by-cell transactions, parking occupancy detection devices, etc.) into a common platform
so that DDOT can make smart operational and strategic choices in managing and operating its
on-street parking meter program.
25
Parking Program Transformation
This section discusses some of the trends that started to evolve as DDOT started infusing smart
assets and alternative payment options into the parking program.
Non-Communicating Assets to Networked “Smart Assets”
DDOT started a systematic process of phasing out non-communicating meters with networked
assets. The changeover was done in a systematic manner based on the findings of the bad actor
report. MSMs were written into the standard specifications and incorporated as part of capital
improvements such as streetscape projects. Table 3 shows how the asset mix has changed over the
last 4 years. The number of spaces that are covered by credit card–accepting, networked meters
jumped from 23 percent in 2009 to 45 percent in 2013.
Table 3. Washington, DC’s changing asset mix for parking meters (2009 and 2013).
2009 Asset Mix
2013 Asset Mix
Networked
Payment
Options
# of
Meters
# of
Spaces
% of
Spaces
# of
Meters
# of
Spaces
% of
Spaces
Non-networked
single-space meters
No
Coin
13,234
13,234
77%
10,238
10,238
55%
Networked multispace meters
Yes
514
3,923
23%
638
5,104
28%
Networked singlespace meters
Yes
None
3,197
3,197
17%
17,157
14,073
18,539
Asset Type
Coin
Credit
Coin
Credit
TOTAL
–
–
13,748
Meter/
space ratio
–
–
0.80
0.75
% of spaces covered
by networked credit
card–accepting
assets
–
–
23%
45%
Coin Transactions to Cashless Transactions
With the introduction of credit card–accepting, networked meters and the launch of pay by cell, DC’s
revenue mix has undergone a significant transformation. In 2009, 80 percent of DC’s parking meter
revenue was in the form of coins. Currently, that percentage stands at only 30 percent. Therefore, a
majority of DC’s revenues are through virtual transactions, which have a lower cost structure than
coin revenues.36 Virtual revenue also provides an easier audit trail and real-time visibility into revenue
streams and meter usage.
26
Reactive to Proactive Maintenance
Operability of networked meters can be monitored in real time through a back-office system (as
opposed to non-network assets, where meter malfunctions have to be reported). Hence, with the
increase in networked assets, the meter maintenance strategy can be shifted from reactive to proactive.
This increases system uptime, revenue potential, and customer satisfaction. It also enables real-time
assessment of asset condition and a more realistic assessment of operability, repair time, etc., making
it easier to manage and monitor a pure performance-based contract. Proactive maintenance also
reduces the cost associated with fielding parking meter–related 311 calls.
“Asset Lite” Solutions
As pay-by-cell adoption rates increase, DC can start considering removing meters from a block face
in areas with high pay-by-cell usage. These meterless blocks would be available to customers using
pay by cell only. This can result in significant cost savings for DC, since an asset-lite solution such
as pay by cell costs significantly less than meter-based payment methods (such as coins or credit
cards). DDOT will be testing some of these asset-lite strategies in a federally funded pilot project in
the Chinatown area.37
Results
Program performance can be measured across various dimensions. The parking meter program has
gone through a transformation as a result of LSS analysis and follow-through. The following section
discusses some of the accomplishments.
■■
Increased payment options for customers—In 2009, people had one mode of payment (coin) at 70
percent of the metered spaces. Now people have at least two options (coin and pay by cell) to pay
at all locations. At 50 percent of the locations, people have three payment options (coin, credit/
debit, and pay by cell).
■■
Increased revenues—In 2009, DC’s parking meter revenue was $20 million. The last set of rate
adjustments occurred in January 2010. DC’s revenue in 2010 was $25 million. DC’s 2012 and
2013 parking revenues were $38 million and $40 million, respectively. This represents a 60 percent
revenue increase with the same set of parameters or policy framework. This is a function of better
management of the assets, more options to pay for metered parking, and better system uptime.
■■
Drop in call volumes—Parking meter–related call volumes can be considered as a surrogate for
customer satisfaction. Call volumes have dropped significantly since an all-time high in 2009 and
2010. 2013 call volumes were 40 percent lower than 2010 levels.
■■
Public perception about the program has increased—If the sentiment in the press is a reflection of
public perception, the program has undergone a sea change over the last 4 years. From headings
such as “Parking Meters a Bane to Mankind,” the press sentiment has turned to “Government at
Its Best” after the launch of the successful pay-by-cell program.38,39
■■
Enhanced executive visibility—Recognizing the success of the program and the full potential,
the executive office of the mayor allocated $25 million in capital funds for asset refresh and
modernization over the next three fiscal year budget cycles.
■■
National recognition—DC’s parking meter program is now widely acknowledged in the industry as
a forward-thinking program. In a recent survey conducted by the International Parking Institute,
DC was ranked fourth among innovative parking programs in the country.40
Figure 8 summarizes some of the performance trends in the parking meter program.
27
Figure 8. Program performance metrics.
28
Lessons Learned
Hilton and Sohal examine the relationship between the successful deployment of LSS in Australia and
a number of key explanatory variables that essentially comprise the competence of the organization,
the competence of the deployment facilitator, and the competence of the project leaders.41 Laureani
and Antony discuss critical success factors for LSS deployment in organizations.42
The success factors/lessons learned for DDOT are well aligned with the findings in the literature and
are discussed below:
■■
Get executive buy-in—For a program such as LSS to work, there needs to be a commitment and
buy-in at the executive level. At DDOT all key executives (the director, deputy director, associate
directors, and chief of staff) went through Six Sigma black belt training. This “signaled” the
agency staff about the importance of LSS and set the tone for the program within the agency. The
executives in turn have deep appreciation of the process and its potential.
■■
Develop a core group of champions—Build a core group of LSS champions throughout the agency.
This core group needs to comprise individuals who can adapt to change, believe in the benefits of
data-based decision making, be enthusiastic about applying the concept to their program areas,
and mentor other people in the organization. At DDOT, this core group got subsequent training
in a Six Sigma train-the-trainer course.
■■
Institutionalize LSS—Develop training program(s) and provide infrastructure support for the
concept to promulgate throughout the agency. LSS is now part of DDOT’s standard curriculum
through the training office.
■■
Apply LSS to the “right projects”—It helps if LSS is applied to a project of critical interest. This
ensures executive support, continuing momentum, and a sense of urgency. For DDOT, the parking
meter program was one of the highest priority problems that needed to be fixed. In addition, black
belt certification requires participants to work on a real-life project. Having executive leadership
trained ensured that LSS was being applied to projects of critical interest to the agency.
■■
Share success stories—Ensure that success stories are shared throughout the organization. DDOT
(and the DC government) has a performance/data-based culture. Sharing tangible benefits
achieved through application of LSS is part of the natural performance reporting process.
■■
Be patient; maintain momentum—Agency transformation through LSS is a marathon, not a sprint.
Success requires patience, discipline, and sustained focus over a period of time.
Conclusion
Application of LSS helped transform the parking meter program that used to be a source of frustration
for DDOT and its customers. LSS helped identify fundamental issues with the program and helped
DDOT to aggressively chart a path forward using a fact-based decision-making process. Following
the success of the parking program, LSS has been applied to other asset classes and programs at
DDOT as well. The principles and tools from LSS have been successfully applied to streetlights,
urban forestry, traffic control officers, and safety service patrols.
The current trends in public sector transportation agencies toward increased use of performance
management/measurement, a higher level of citizen engagement, and operating in a financially
constrained environment can serve as a catalyst for adopting process improvement efforts such
as LSS. Applied correctly, it has the potential to provide the framework for achieving sustainable
improvements to business processes and service delivery.
29
Acknowledgments
The author would like to acknowledge the contributions of Mark Derrick of Xerox Corporation and
Stephanie Dock of DDOT and their help in identifying, synthesizing, and analyzing the data used
for this paper. Their input, suggestions, and analysis were invaluable in crafting the message in this
paper. The author would also like to thank the reviewers and editors for their valuable input and
suggestions, which helped improve the quality of the final product.
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Enhance Its Parking System.” The Parking Professional, July 2011.
31
34. Dey, S.S. and A. Rao. “Dialing and Thriving—Two Years After Its Introduction, Pay-by-Cell
Enjoys Tremendous Success in Washington, DC” The Parking Professional, August 2013.
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(2014).
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Grant Program—Value Pricing Pilot Grant Application.” January 2012, [Online].
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[Online]. Available: www.washingtonpost.com/blogs/all-opinions-are-local/post/an-exampleof-government-at-its-best/2011/03/22/gIQA332RuL_blog.html. [Accessed July 29, 2013.]
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2011, [Online]. Available: www.washingtonpost.com/local/dc-rolls-out-pay-by-phone-parkingmeter-system/2011/04/20/AFg9pSEE_story.html. [Accessed July 29, 2013.]
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Sigma.” International Journal of Lean Six Sigma, Vol. 3, No. 4 (2012): 274–283.
Soumya S. Dey, P.E., PMP, is the director of research and technology transfer for the
District Department of Transportation. He has more than 20 years of experience in the
transportation profession, spanning the public and private sectors. He has a B.S. in civil
engineering from the Indian Institute of Technology, an M.S. in civil engineering from
Purdue University, and an MBA from the University of Maryland. He received ITE’s Past
Presidents Award and the Cafritz Award for Excellence in Public Leadership. He is a certified black
belt in Lean Six Sigma. He is a Fellow of ITE.
32
Public Perception of Double Crossover
Diamond Interchanges
By Kristy Jackson, Christopher Cunningham, P.E., Chunho Yeom, Joseph E. Hummer, Ph.D., P.E.,
and Adam Kirk, Ph.D., P.E., PTOE, AICP
A double crossover diamond (DCD) interchange (a.k.a. diverging diamond interchange)
is a new unconventional diamond-type interchange. The purpose of this interchange design is to
accommodate left-turning movements onto arterials and limited-access highways while eliminating
the need for a left turn bay and signal phase at the ramp terminals. During a large study sponsored
by the Federal Highway Administration, the research team examined how users perceived new DCD
interchanges using focus groups formed at three DCD sites with 20 total participants and attitudes
summarized from surveys conducted at two DCD sites with a total of 1,649 participants. The team
further explored the results of one of the surveys, comparing opinions expressed before and after
the installation of a DCD. The results from both the focus groups and surveys revealed that DCD
interchanges operated properly, but there is room for improvement in how these interchanges
might be more readily accepted by the public. In regards to general knowledge and comfort with
the interchange and safety (real or perceived), users generally thought the interchange was an
improvement over the existing facility. The most frequently reported issues are summarized for
further consideration in outreach, education, planning, or design. Specific changes could be made
in regards to the scope of the project to include adjacent interchanges, adjustments with signal
operations, and the inclusion of facilities to accommodate both bicyclist and pedestrian travel to
increase user satisfaction with DCD interchanges.
33
Introduction
A double crossover diamond (DCD) interchange (also known as a diverging diamond interchange, or
DDI) is a new unconventional diamond-type interchange. This interchange design accommodates
left-turning movements onto and off of the freeway while eliminating the need for a left turn bay
and signal phase at the ramp terminals.1 While the ramp configuration at the freeway is similar to a
traditional diamond interchange, traffic on the cross route moves to the left side of the roadway for
the segment between signalized ramp intersections.2 Pictured in Figure 1 is a typical DCD interchange
diagram oriented with an east-to-west arterial road. Directional movements are presented by origin–
destination methods, so, for instance, “W to E” means vehicular movements from the west to east
(shown in red).
Figure 1. Typical double crossover diamond layout showing vehicular movements
through the interchange
Source: Map data ©2014 Google Imagery ©2014 DigitalGlobe, USDA Farm Service Agency.
The first DCD interchange was installed in France in the 1970s, and the Missouri Department of
Transportation (DOT) implemented the first U.S. DCD interchange in Springfield, Missouri, on
June 21, 2009.2,3 The total number of DCD interchanges has increased rapidly since the initial one in
Springfield, and many more DCDs are under construction in the United States.
Due to the lack of experience with DCD interchanges, the Federal Highway Administration (FHWA)
executed a project (Project DTFH61-10-C-00029), Field Evaluation of Double Crossover Diamond
Interchanges, to investigate the first seven DCD interchanges installed nationwide. As part of the
project, the research team evaluated attitudes through focus groups and surveys at five of the seven
sites to gain insight into the public perception of the new DCD interchanges.
34
Literature Review
Shumaker et al. conducted a random survey of Institute of Transportation Engineers members to
document barriers inhibiting the implementation of unconventional intersection and interchange
designs (UIIDs), which included the DCD interchange.4 The survey responses from 103 UIID
projects rated both before and after opening showed that the public opinion generally improved
after opening, although the results did not specify which type of UIID projects were evaluated.
Respondents identified the largest barrier to widespread UIID use was lack of public and professional
support, although a range of other responses were given. Respondents were also asked to rank several
identified barriers such as public acceptance, professional support, and political barriers. For public
acceptance, the largest barriers were the potential for driver confusion and fear of the unknown. Lack
of proof of design function and safety concerns were the largest professional barriers. Political barriers
included public opinion and reiterated the lack of proof of design function as an issue. Respondents
overwhelmingly indicated that proof of the benefits offered by UIID designs is important and noted
that education should not be overlooked when attempting to overcome implementation barriers.
The North Carolina DOT studied benefits and capacities of superstreets, also known as restricted
crossing U-turn intersections, to develop a level-of-service estimation program.5 As part of the study,
they conducted mail/email surveys of residents and commuters in parallel with in-person surveys
of businesses to determine the general perception of the intersection for each user group type. The
results of the surveys showed mixed perceptions among user groups.
■■
■■
■■
Residents: More than half (52 percent) agreed there was a positive effect on safe navigation, while
23 percent said the superstreet has had a negative effect. In contrast, for the same resident survey,
38 percent reported navigation through a superstreet more confusing, whereas 35 percent reported
it easier/less confusing.
Commuters: Of those identified as commuters in the survey, approximately half of commuters
reported they experienced difficulty/confusion driving through the superstreet. Nearly half (44
percent) reported that the superstreet had not affected their ability to safely navigate the roadway
compared with the previous design, while 33 percent and 22 percent reported positive and negative
impacts, respectively.
Businesses: In-person surveys of surrounding businesses were completed at two superstreet
locations. Sixty percent and 42 percent at locations 1 and 2, respectively, indicated that the
superstreet had no effect or an improved effect on customer satisfaction with access to the store.
Business respondents reported some confusion by drivers, with 30 percent and 42 percent reporting
some confusion at locations 1 and 2, respectively. Responses varied on the reaction to traffic safety,
with 40 percent and 53 percent reporting improvement at the two locations, respectively.
FHWA developed a simulator experiment of a DCD interchange for the public before DCDs were
field implemented in Missouri.6 With the help of the Missouri DOT, they simulated three types of
DCD interchanges: a DCD interchange with full signs and lane markings, a DCD interchange with
minimized signs and lane markings, and a conventional diamond interchange. After 74 participants
had completed the evaluation experiment in the driving simulator, they concluded that safety
concerns of wrong ways at the crossover were not problematic, as no drivers looked at or attempted
to drive down the wrong approach. Other types of driver errors were found to be no more likely
with the DCD configurations than with the conventional diamond interchange. As a result of the
simulated experiment, they recommended a DCD interchange as an attractive alternative due to a
prospective safety benefit of less conflict points and more efficient signal operation.
35
Objectives
This paper presents the results from the focus groups and surveys conducted at the five new DCD sites.
The focus group and survey results should help agencies thinking about DCDs in several ways. First,
they should help agencies understand the general public perception for the unconventional interchange.
Perception is important and can assist with targeting educational materials that can explain unique
features of DCDs, such as driving on the opposite side of the road. Agencies looking to implement a
DCD project should be aware of perceptions regarding this design. Policymakers or highway designers
should consider the results of the focus groups and surveys when deciding whether or how to implement
DCDs for a candidate location. Second, it would be informative for agencies to use survey data to design
or calibrate DCDs to operate more efficiently. For example, there are many comments regarding signal
timing, which provide opportunities for traffic engineers to investigate and optimize a DCD signal system
based on public input. Lastly, issues brought up through the focus groups and survey may influence an
agency’s decision to alter a project so that it receives more public support. For example, a project may
receive less scrutiny if it includes considerations for adjacent intersections within the project scope or
has provisions for integrating bicycle and pedestrian facilities. The “before” and “after” survey approach
is also provided as a useful supplement to traditional public involvement. In understanding the general
issues and giving the public another opportunity to express their opinion, transportation professionals
trying to implement these designs can gain a better understanding of and work to address some of the
issues (both real and perceived) with the unconventional design.
Scope
From the seven new DCD installations studied for the FHWA project, a focus group was conducted
at three sites including Alcoa, TN, USA; Maryland Heights, MO, USA; and Kansas City, MO, USA.
Surveys were conducted at the sites in Lexington, KY, USA, and Rochester, NY, USA. The focus groups
and surveys were conducted after construction and at least 5 months after opening of the interchange,
with the exception of Rochester, where a “before” survey was also conducted prior to construction.
Table 1 shows the five DCD sites studied, the method (focus group or survey), the dates when the
public perceptions were gathered, and the overall number of participants/respondents.
Table 1. DCD interchanges studied for the focus group and survey.
Method
Focus
Group/
Survey Date
Participants /
Respondents
Dec. 12, 2010
Focus group
June 21, 2011
7
Kansas City, MO
[I-435 @ Front St.]
Nov. 7, 2011
Focus group
Aug 15, 2012
7
Maryland Heights, MO
[I-270 @ Dorsett Rd.]
Oct. 17, 2010
Focus group
(interviews)
Aug 9, 2011
6
Lexington, KY
[KY 4 @ US 68]
Aug. 14, 2011
Survey
Jan 20, 2012–
Feb 24, 2012
1,418
Rochester, NY
[I-590 @ Winton Rd.]
Sept. 11, 2012
Survey (before)
May 2012
98
Survey (after)
June 2013
133
Date DCD
Opened
Alcoa, TN
[US129 @ Bessemer St.]
DCD Site [Freeway @ Arterial]
Source: Details on the designs and operations of the five interchanges studied for this paper are available in the
FHWA project technical report: Cunningham, C.M., B.J. Schroeder, J.E. Hummer, C. Yeom, C. Vaughan, and K.
Salamati. Field Evaluation of Double Crossover Diamond Interchanges. Washington, DC: Transportation Research Board,
2013 (report in progress).
36
The research team employed focus groups and surveys to ask standard questions and gain insight
into public perceptions regarding DCDs. The focus groups were led by a facilitator to develop a
deeper discussion of questions related to the DCD with a small number of participants. Focus
group discussion provided participants the opportunity to engage with and build upon each other’s
responses. In contrast, surveys allowed the team to reach a larger number of participants, but with
no opportunity to build on other responses. Survey respondents and focus group participants had
the opportunity to be more expressive through open-ended questions provided within each topic
category, with the exception of the Lexington, KY, survey, which only provided one opportunity to
give open-ended comments. A comparison of “before” and “after” surveys conducted online gives
insight into public attitudes regarding DCDs prior to and postconstruction, with the understanding
that limited inferences can be drawn due to a high likelihood of sampling bias.
Surveys
An analysis of responses from two online surveys is presented in this paper. The first was a User
Satisfaction Survey conducted by the Kentucky Transportation Center for the DCD constructed in
Lexington, KY.7 The second survey was conducted by the research team for the DCD in Rochester, NY.
The Lexington, KY, survey was completed by participants over a 1-month period following
construction of the DCD. Three methods were used for survey outreach. First, attendees that had
participated in a public meeting prior to the survey were provided the survey in online and traditional
mail formats. Second, the survey was advertised on variable message boards in the corridor. Third, a
link to the survey was given to a variety of government, news, and social media pages. In total, 1,421
responses were received, with 954 unique open-ended responses.
The surveys of the Rochester, NY, DCD consisted of a “before” and “after” analysis to allow
comparisons of public perceptions prior to and following construction of the DCD. The survey
was distributed to public meeting attendees via email and posted to the project website, where
respondents could provide feedback to questions with regard to safety, congestion, avoidance,
travel behavior, complexity of the interchange, and user comfort when walking, biking, or accessing
transit. The online survey was open for a period of 1 month in the “before” and “after” periods,
with the latter survey taking place 6 months after the official opening of the DCD. Surveys given in
the “before” and “after” periods did not track opinions of the same respondent, although “before”
survey respondents who elected to receive the “after” survey were notified when it became available.
A total of 98 and 133 survey participants responded to the “before” and “after” surveys, respectively,
and 159 and 184 unique comments were provided, respectively.
Respondent demographic information from the Rochester “before” and “after” survey is provided in
Table 2. No demographic information was collected with the Lexington-based survey. Respondent
gender type was fairly consistent before and after construction of the DCD. The vast majority of
respondents during both time periods were between the ages of 36 and 65 years. Most respondents
were from professional, scientific, and technical service backgrounds, with retired individuals and
the health care and education professions following close behind.
37
Table 2. Rochester survey respondent demographic information.
Before
Respondents’ Information
Gender
Age Group
Profession
After
Respondents
%
Respondents
%
Male
47
52.8
66
60.0
Female
42
47.2
44
40.0
16–25
3
3.4
6
5.4
26–35
10
11.2
11
9.9
36–50
26
29.2
35
31.5
51–65
37
41.6
44
39.7
66–75
8
9.0
12
10.8
Over 75
5
5.6
3
2.7
Transportation and warehousing
4
4.5
5
4.5
Information
6
6.7
7
6.3
Finance and insurance
5
5.6
4
3.6
Professional, scientific, and technical
services
27
30.3
39
35.2
Educational services
6
6.7
9
8.1
Health care and social assistance
14
15.7
7
6.3
Other services (except public
administration)
5
5.6
8
7.2
Retired
14
15.7
13
11.7
Others
8
9.2
19
17.1
Focus Groups
For focus groups, flyers and open-ended phone calls were utilized to gather a group of individuals
from the community surrounding the DCD. Where possible, subjects were recruited by corresponding
transportation agencies from contact lists made during public involvement meetings. In the focus
group meetings, primary questions for each category were asked first and supplementary categorical
questions were asked if time allowed for a more in-depth discussion of the topic. Since focus groups
require face-to-face meetings, a conference room was utilized, where a member of the research team
facilitated the discussion among the participants. Figure 2 illustrates the room setup and group setting.
Figure 2. Discussion at a DCD focus group.
38
Participants generally lived or worked in the immediate vicinity of the DCD. All participants were
18 years or older and possessed a valid driver’s license. At the focus group meeting, each participant
provided baseline information including location of residence, where they were employed, how
often they utilized the DCD interchange, and for what purpose they used the DCD. The types of
participants represented at a typical focus group are presented in Table 3, which shows the breakdown
of attendees at the Maryland Heights Focus Group.
Table 3. Typical focus group participation.
Approximate
Distance from
Interchange
(miles)
Respondent
Work Type
Type of Work
Quadrant
Primary Reason for
Driving through
Interchange
R1
Receptionist
Public
NW
Work
0.3
R2
Receptionist
Public
NW
Private, lives in area
0.3
R3
Manager
Retail
NW
Work
0.5
R4
Cashier
Retail
NW
Work
0.5
R5
Manager
Hotel
NE
Work
0.1
R6
Manager
Hotel
SE
Work
0.1
Topic Categories
In the focus groups and surveys, questions were centered on five specific topic categories. Questions
addressed general knowledge of the DCD, opinions related to safety, opinions related to its design
and operation, and finally concerns over bike/pedestrian and transit issues. Categories were utilized
to ensure consistency in questioning and reporting and to ensure the appropriate themes were
covered. These categories and related questions included:
■■
■■
■■
General knowledge and perception of the DCD
●●
Have you ever heard of a DCD before this meeting?
●●
What is a DCD? How is it intended to work? What is the purpose of a DCD (what problem does
it solve)?
●●
What are your reasons for driving through the interchange? Why use it instead of other roads?
Opinions related to safety
●●
How safe do you feel while driving through the DCD?
●●
What kinds of roadway design, marking, signage, and roadway maintenance situations do you
feel make the DCD safe and easy to navigate?
●●
What driving behaviors do you feel are major causes of crashes at the DCD? Which ones do you
think are a bigger problem on the DCD than on other roads?
Operations and design
●●
Do you feel the DCD is kept in good repair?
●●
Do you ever encounter problems seeing lane markings and other pavement markings at the
DCD? Under what conditions?
39
■■
Walking, bicycling, and accessing transit
●●
■■
A question about the safety of bicyclists and pedestrians was asked at the focus groups if time
permitted, but the quality of responses depended on the level of discussion.
Solutions
●●
Participants were encouraged to give comments that built upon an idea or improved it, starting
with the problem that most participants identified as being important.
Focus group and survey methods were used to obtain public opinion; therefore, some questions were
slightly modified to fit the format. For instance, for the two surveys conducted in Lexington and
Rochester, many questions were presented in a 1 through 5 format instead of an open dialogue as in
the focus groups. In addition, survey respondents from Rochester were provided an opportunity to
offer solutions to perceived problems both verbally and through a specific open comment section.
No opportunities to offer solutions or specific questions regarding walking, bicycling, or accessing
transit were given in the Lexington survey, as this survey was developed prior to the funding of this
research effort. Even so, some comments from Lexington regarding those topic areas were recorded
in the one open-ended section that was provided.
Before And After Survey Comparisons: Rochester, NY
The team conducted “before” and “after” surveys at the Winton Road/I-590 interchange in Rochester,
NY, to gauge respondents’ opinions of the interchange project in regards to the topics previously
presented in Table 3. The “before” survey was conducted while the interchange was still in a standard
diamond configuration. The “after” survey was conducted 6 months after the DCD interchange
opened to allow users time to acclimate. Since this was the only public outreach effort that spanned
the “before” and “after” periods of the construction of a DCD, it will be discussed in more detail than
previous considerations noted only after construction of the facility.
Demographic information was requested at the end of the online survey but is presented at the
beginning of the discussion to establish a comparison of the survey samples (see Table 2). As the
research team understands the issues with self-selection and the potential for stakeholder bias from
comparing two convenience samples, the following comparisons are not intended as generalized
results. These results are important, however, as this is the first type of survey of its kind regarding
the comparison of public opinion of a DCD in the “before” and “after” conditions of a construction
project. There is interest from professionals in understanding what type of shift in perception
might occur between existing conditions (traditional diamond interchange) and the subsequent
unconventional design (DDI). An effort has been made to ensure that outreach was conducted in a
similar manner in each condition.
The New York DOT advertised the survey using contacts from a list developed from previous
planning and preconstruction meetings with the public. Most of the responses were collected by
an electronic survey system, and paper copies that were submitted were recorded in the online
format. A total of 98 participants were surveyed in the “before” condition and 133 in the “after”
condition. Of the 98 who participated in the survey distributed during the “before” condition, 55
provided their email addresses and were contacted with an opportunity to participate in the survey
distributed in the “after” condition. While there is a potential for survey bias typical with online
surveys, respondents had similar characteristics in terms of gender, being primarily male, and had
a similar stratification of age (see Table 2). Of those who responded, 30 percent (“before” survey)
and 35 percent (“after” survey) were in the professional, scientific, and technical services, which may
indicate a large amount of interest from professionals related to the project (Question 18 [Q18] on
the survey). Retired persons were the second highest group of respondents in both surveys.
40
General Knowledge and Perception of the DCD
Each “before” and “after” survey asked four questions to document overall understanding of the
interchange before and after implementation and to see how frequently the interchange was used,
any changes in general travel patterns through the interchange, and reasons for potential avoidance
behavior. The four questions are summarized in Table 4.
Table 4. General knowledge and perception survey results
Q1. How often do you travel through the interchange at Winton Rd. and I-590?
Answer Options
Pre-DCD [Diamond]
After [DCD]
Never
1
1.0%
0
0%
A few times
10
10.2%
38
28.6%
Once or twice a week
23
23.5%
44
33.1%
Most days
12
12.2%
13
9.7%
Almost every day
52
53.1%
38
28.6%
Total answered
98
100%
133
100%
Q2. How often do you travel through the interchange during rush hour?
Answer Options
Pre-DCD [Diamond]
After [DCD]
Never
6
6.1%
19
14.3%
A few times
27
27.6%
55
41.3%
21
21.4%
24
18.1%
Most days
10
10.2%
24
18.1%
Almost every day
34
34.7%
11
8.2%
Total answered
98
100%
133
100%
Q3. How often do you take a longer alternate route (avoid the interchange at Winton Rd/I-590) to get
to your destination?
Answer Options
Pre-DCD [Diamond]
After [DCD]
Never
48
49.0%
90
67.6%
A few times
35
35.7%
29
21.8%
3
3.1%
7
5.3%
Most days
9
9.2%
3
2.3%
Almost every day
3
3.1%
4
3.0%
Total answered
98
100 %
133
100%
Q4. If you sometimes take an alternate route to avoid the interchange at Winton Rd/I-590, what reason
is most applicable?
Answer Options
Pre-DCD [Diamond]
After [DCD]
Rush hour traffic
41
41.8%
21
15.8%
Collision
8
8.2%
5
3.8%
Not applicable
41
41.8%
86
64.6%
Other (please specify)
8
8.2%
21
15.8%
Total answered
98
100%
133
100%
Generally speaking, respondents were more frequent users in the “before” period than the “after”
period, with 88.8 percent using the existing diamond interchange at least once or twice a week,
compared to 71.4 percent who used the new DCD with the same frequency. When asked how often
they used the interchange during rush hour (Q2), 76.3 percent and 44.4 percent said they used the
41
interchange at least once or twice during the “before” and “after” periods, respectively. It is unclear
to what extent behaviors have been altered by the construction or the exact routes taken by those
surveyed, but respondents surveyed indicated that a lower percentage of them used the DCD with
some frequency after construction (Q2). Further, fewer reported taking alternate routes to avoid the
interchange postconstruction (Q3). After DCD construction, 67.6 percent of respondents said they
never avoided the interchange, compared to only 49 percent with the old design. Lastly, respondents
were much more likely to take an alternate route due to rush hour traffic prior to construction of the
DCD. Of the 21 who responded that they did take an alternate route in the “after” condition for a
reason not listed, 13 respondents (approximately 62 percent) specified that it was due to the design
or operation of the new interchange (Q4).
Opinions Related to Safety
Safety at DCDs is one of the primary concerns for designers and the driving general public and
is regularly brought up in public meetings. The research team surveyed how drivers in Rochester
recognized the overall safety of the interchange before and after DCD implementation during
different times of the day and for different turning movements. The results are presented in Table 5.
Table 5. Safety survey results.
Q5. Using a scale of 1 to 5, with 5 being safest, rate the safety of the Winton Rd./I-590 Diverging Diamond
interchange during the following times. Select N/A if you never drive through the interchange at that time.
Answer Options
Pre-DCD [Diamond]
After [DCD]
Average
Standard Deviation
Average
Standard Deviation
Morning rush hour
3.3
1.2
4.0
1.1
Lunch rush hour
3.6
1.2
4.1
1.1
Afternoon rush hour
2.7
1.3
3.9
1.1
Weekend
4.2
0.9
4.4
1.0
Total answered
98
117
Q6. Using a scale of 1 to 5, with 5 being safest, rate the safety of each of the following movements at
the interchange. Select N/A if you never drive through that part of the interchange.
Answer Options
Pre-DCD [Diamond]
Average
Average
Standard Deviation
1.16
4.13
1.03
2.95
1.23
4.34
1.06
3.35
1.14
4.31
1.10
Driving through the
interchange on Winton
Road
3.67
Turning left from Winton
Road onto I-590 ramp
Turning left after exiting
I-590 onto Winton Road
Total answered
Standard Deviation
After [DCD]
98
117
Respondents rated the safety of the diamond and DCD interchanges on a scale of 1 to 5, with 5 being
the safest. The results indicate that, overall, the DCD interchange was rated safer than the previous
diamond interchange. When looking at specific periods of the day (Q5), the afternoon rush hour
showed the greatest improvement in safety. Respondents generally reported that the morning and
lunch periods were safer than before, though not as much as the PM peak.
Respondents rated the safety of the through movement and two left turn movements on a scale of 1
to 5, with 5 being the safest. Comparing “before” and “after” periods, the team found that the overall
42
safety perception related to each movement changed between the two interchange configurations. In
the “before” survey, of the three movements, through movements were rated the safest. This response
was likely due to the fact that vehicles turning left onto the freeway queued up significantly under
the bridge at the second interchange signal. For the left turn movement off the freeway, traffic had
to cross a conflicting movement at the downstream signal. In contrast, responses after construction
of the DCD interchange rated the through movement as the least safe compared to the left turn
movements. This may be attributed to the fact that the left turn onto the freeway is now a free-flow
movement and is therefore perceived as safer. Overall, respondents rated all movements as safer in
the after condition than the before condition.
Lastly, with regard to safety, respondents were provided the opportunity to express written
opinions of the old and new interchange designs (Q7). The most common response in the “before”
survey for the conventional diamond interchange was difficulty with traveling northbound on
Winton Road and making a right turn onto the ramp to I-590 eastbound. A total of 14 comments
described a stressful merging situation when attempting to complete this right turn maneuver. In
some instances, comments described drivers not respecting a right turn only lane upstream of the
interchange, using it as a right turn lane for a turn onto the ramp at the interchange. Also, the
heavier right turn movement was required to yield to a lighter left turn maneuver onto the freeway
from the northbound approach. The low volume of conflicting traffic from this left turn often led
right-turning drivers to forget to yield, resulting in conflicts. Another seven comments referred to
issues at an adjacent intersection, with a few comments regarding aggressive drivers, and a wide
variety of other operational considerations.
In the “after” survey, the most frequent responses were the 22 comments related to driver confusion
or lack of comfort—most reporting observations of others being confused (including wrong-way
maneuvers) and several reporting that they experienced confusion traveling through the interchange.
There were 14 generally positive comments regarding the design, 10 comments regarding issues at
an adjacent intersection, and 7 comments regarding a desire for a change in signal timing. There
were two comments for each of the following: issues with right turns onto the freeway, lack of safe
bicycling infrastructure, and desire for a reduction in speed limit.
Operation and Design
Improved operation is often a primary motivation for considering a DCD. Table 6 presents results
for the Rochester survey questions related to congestion, maintenance, and perceived complexity of
driving through the interchange before and after implementation of the DCD.
43
Table 6. Operation and design survey results.
Q8. The current interchange is generally kept in good repair and does not encounter maintenance problems.
Answer Options
Pre-DCD [Diamond]
Strongly agree
8
Agree
Neutral
After [DCD]
8.3%
61
52.1%
51
53.1%
39
33.3%
24
25.0%
16
13.7%
Disagree
11
11.5%
1
0.9%
Strongly disagree
2
2.1%
0
0%
96
100%
117
100%
Total answered
Q9. Using a scale of 1 to 5, with 5 being least congested, rate the ease with which you are able to drive
through the current interchange in the following scenarios:
Answer Options
Pre-DCD [Diamond]
After [DCD]
Average
Standard
Deviation
Average
Standard
Deviation
Driving through the
interchange on Winton
Road
3.3
1.3
3.9
1.5
Turning left from Winton
Road onto I-590 ramp
3.0
1.3
4.1
1.5
Turning left after exiting
I-590 onto Winton Road
3.2
1.3
4.1
1.5
Total answered
96
117
Q10. Using a scale of 1 to 5, with 5 being least complex, rate your understanding of the interchange in its
current configuration when you drive through it to get to your destinations.
Answer Options
Understanding of driving
through interchange
Total answered
Pre-DCD [Diamond]
After [DCD]
Average
Standard
Deviation
Average
Standard
Deviation
4.2
1.7
4.3
1.7
96
117
With regard to maintenance, survey respondents generally agreed that the new interchange was in
good repair (Q8), with 85.4 percent of respondents agreeing the interchange was well maintained.
Although the previous conventional diamond interchange received a lower rating of 61.4 percent in
these two categories, this would be expected as the previous interchange was decades old compared
to the new interchange.
Survey participants were asked to rate the level of congestion for each of three movements on a scale
of 1 to 5, with 5 being the least congested (Q9). Each movement was rated as less congested in the
“after” condition than in the “before” condition. There was a shift in which movement was regarded
as the most congested of the three listed. In the before survey, through movements were regarded as
the least congested, whereas in the after survey, turning movements were rated as the least congested.
Similarly, the survey asked users to rate the complexity of driving through the interchange (Q10)
on a scale of 1 to 5, with 5 being the least complex. The average complexity rating for the existing
diamond interchange was 4.21, whereas the average rating for the DCD interchange was 4.25,
indicating little difference in the perception of complexity with the new DCD interchange.
Respondents were given an opportunity to provide additional comments regarding operations at
the interchange (Q11). Of the 19 comments provided in the “before” survey, issues at an adjacent
44
intersection received 5 comments, followed by 2 comments each for topics covering lane configuration,
drainage, issues with the survey itself, and no improvements needed at the interchange. A single
comment was also given for issues with sight distance, backups, and hesitation regarding the new
interchange.
Following DCD implementation, of the 35 comments given regarding operations in the “after”
survey, signal-related concerns were the chief issue expressed, with 9 comments regarding signal
phasing adjustments at the DCD and 7 comments that discussed issues at an adjacent intersection
(primarily due to signalization issues), where 7 were primarily positive comments and 4 were chiefly
negative comments; 2 comments were related to each of the following: additional signage, driver
confusion, and inadequate bicycle facilities. Other comments given were either neutral or related to
avoidance of the interchange.
Walking, Bicycling, and Accessing Transit
Accommodations for bicyclist and pedestrians can also be a concern when implementing an
unconventional design. The survey asked respondents to rate how comfortable they were traveling
on Winton Road during three activities: walking, bicycling, and accessing transit. The results are
shown in Table 7.
Table 7. Walking, bicycling, and accessing transit survey results
Q12. Using a scale of 1 to 5, with 5 being the most comfortable, please rate your comfort when traveling
on Winton Road during the following activities:
Answer Options
Pre-DCD [Diamond]
Average
After [DCD]
Standard Deviation
Average
Standard Deviation
Walking
2.0
1.1
2.5
1.4
Bicycling
1.8
1.0
2.7
1.5
Accessing transit
2.5
1.2
3.2
1.5
Total answered
94
115
The team asked respondents to rate their comfort level during the three activities (Q12) on a scale from
1 to 5, with 5 being the most comfortable. The overall comfort perception for all activities—walking,
bicycling, and accessing transit—improved following DCD construction; however, it should be noted
that facilities for pedestrians were incomplete during both the “before” and “after” conditions.
Rating averages ranged from 1.75 for bicycling to 2.48 for accessing transit in the “before” survey,
indicating the majority of respondents were not comfortable. In the “after” survey, averages ranged
from 2.72 for bicycling to 3.17 for accessing transit. Although the range shows some improvement,
the results suggest that there is still a general lack of comfort when bicycling or walking.
Respondents were given an opportunity to provide additional comments regarding walking, biking,
or accessing transit at the interchange in both the “before” and “after” conditions. Although response
rates were higher after DCD installation, a review of comments provided in Q13 appears to show
little shift in public opinion regarding the safety or provision of bicycle and pedestrian facilities at
the interchange. In the “before” survey, of the 14 comments that were given, there were 10 comments
noting a dangerous or unsafe environment for bicyclists and/or pedestrians, 2 comments about
inadequate facilities, and 2 comments about issues at the ramps. In the “after” survey, of the 27
comments that were given, 8 were to the effect that they did not use the facilities in this way or that
they had no additional comment to provide. Of the remaining 19 comments, 11 comments noted a
dangerous or unsafe environment and 5 comments noted inadequate facilities for bicycling and/or
45
walking. Other comments discussed inadequate maintenance (snow removal), failure to yield at the
on-ramps, and circuitous/long routes for pedestrians to cross the roadway. There was one positive
comment stating that the interchange looked like a “bicycle-friendly touring route.”
Suggested Solutions
In Q14, respondents were asked to provide “any additional comments about your experience at the
interchange or suggestions on how to improve the interchange.” Due to the potential for multiple
discreet comments in one response, these numbers do not always add up to the total. In the “before”
survey, 19 comments were given on a very wide variety of topics, 9 of which did not offer suggestions
for improving the interchange. The most common solution (4 comments) was related to making
improvements at an adjacent intersection. Three comments about planning or making improvements
for nonmotorized traffic were also given. Other comments included installing a DCD interchange,
reducing the speed limit, and improving sight distance. In the “after” survey, after removing those
that offered no additional comment, 28 responses were given, 13 of which offered solutions. Seven
respondents reported positive feedback and offered no changes. Conversely, four respondents
reported negative feedback and/or requested a “normal” interchange. Of the comments that were
given offering solutions or pointing out issues, six were related to changes regarding timing of the
lights through the interchange, five were related to adjacent intersection issues, four were related to
improved signage, and two were related to driver confusion. A comment was also given on making
a crossing improvement for pedestrians. These responses suggest general satisfaction by motorists
with the new DCD interchange, with the majority of changes suggested pointing toward an interest
in operational improvements.
Analysis of Public Outreach Responses from Focus Groups and
Supplemental Surveys
The following sections provide summaries of the general findings from focus group and survey
efforts based on the topic categories outlined above. These findings, especially those from the focus
groups, often explain inconsistencies in results from the more quantitative surveys, along with
providing more details about specific positive and negative outcomes of the DCD interchange. The
general findings are reported by the four primary topic areas discussed earlier in the paper.
General Knowledge and Perception of the DCD
Participants were typically knowledgeable about the DCD. Many respondents indicated that the
interchange was intended to assist with the flow of traffic and aid in traffic congestion, although
some indicated little understanding of the specific details surrounding the design or operation of
the interchange.
The general perception of the DCD obtained through varied outreach methods was mixed; however,
the vast majority of the discussion and comments were cautiously positive. Concerns were expressed
for a wide variety of reasons; however, individuals most frequently expressed reservations about:
■■
Driver confusion, inattentiveness, and unfamiliarity with the interchange;
■■
Wrong-way maneuvers (fear of meeting drivers head-on in the interchange);
■■
Need for exposure/experience with the interchange; and
■■
Concern for queuing and signal timing at adjacent intersections.
A few of the general respondent perceptions from the sites are discussed in the following section.
46
The large sample size in the survey conducted in Lexington, KY, allowed more insight about
how local travelers versus commuters felt about their experience traveling through the DCD. In
Lexington, daily drivers of the DCD were more likely to identify benefits in safety and operations
from the project, while infrequent users were more likely to remain undecided (though more than
50 percent still identified benefits). When asked if it was easy to understand how to drive through the
interchange, 86 percent of frequent (everyday) drivers agreed it was easy to navigate, while 73 percent
of infrequent drivers agreed.
The majority of DCDs studied implemented signal timing that prioritized peak directional
movements, such as left turns to and from the freeway. For this reason, it is likely that negative
impacts to travel were more often cited by individuals traveling locally to destinations on the minor
roadway as opposed to those commuting through the area to and from the freeway. Respondents
living in and around the DCD often expressed that the new design had a negative impact on trips
that required turns at adjacent roadways.
Focus group participants in Alcoa, TN, perceived an overall increase in problems after the installation
of the DCD. The participants were particularly concerned with a lack of consideration for access
to neighborhoods adjacent to the DCD, which resulted in limited access to right-in, right-out
movements at the neighborhood entrance.
Respondents in the Rochester, NY, “before” and “after” survey indicated driving through the
interchange was not complex, even when compared with the previous diamond interchange. Survey
responses from both Lexington and Rochester indicate that traveling through the DCD interchange
is somewhat of a learned task and requires exposure before drivers are truly comfortable, especially
at those sites that have significant populations who do not use the facility regularly.
Opinions Related to Safety
The majority of participants agreed that the interchange was safer following construction of the
DCD. Some expressed some concern when the interchange was first installed. Many comments
were given regarding safety, and although there is no way to distinguish perceived versus real safety
concerns, for the purposes of reporting user opinion, primary safety concerns most often provided
by respondents include:
■■
Wrong-way maneuvers;
■■
Illegal U-turns at the crossovers;
■■
Red light running; and
■■
Sight distance issues.
Comments regarding wrong-way maneuvers were due to apprehension about driving through
the DCD and encountering a vehicle head-on. Focus group participants felt this issue was likely
more prevalent with visitors to the area or infrequent or distracted drivers. With regard to personal
driving concerns, many participants mentioned that increased experience driving through the DCD
interchange alleviated hesitation.
Respondents from two of the sites noted that red light running was a serious problem at their
interchanges after DCD construction. At one focus group, this was discussed for a significant period
of time before the moderator finally changed subjects. In the Rochester survey, respondents expressed
that red light running was due to the duration of the two lights for the through traffic on the DCD
being too short or timed improperly. It was reported that motorists could not make it through the
DCD in one signal cycle, so frustrated drivers often ran the second light.
47
During the focus group in Alcoa, TN, participants discussed concerns with the height of two fill
sections (berms), which caused sight distance issues: 1) on the southbound off-ramp turning left
onto the cross street (Bessemer Street), where traffic coming straight through the preceding crossover
was difficult to see, and 2) at the northbound off-ramp where right-turning vehicles merged with
through traffic along Bessemer Street. As shown in Figure 3, material from the berms was removed
after the opening of the DCD interchange to allow for better sight distance.
Figure 3. Sight distance issues caused by dirt fill were remedied after construction
of a DCD in Alcoa, TN.
Source: Map data ©2014 Google Imagery ©2014 DigitalGlobe, U.S. Geological Survey, USDA Farm Service Agency.
At the Dorsett Road DCD in Maryland Heights, right-turning vehicles at the freeway off-ramps
were allowed to turn right on red. Based on feedback, there seem to have been quite a few conflicts
involving these movements due to the close proximity of the off-ramp right turn movement to the
DCD crossover. This effect was also noted during a parallel field data collection effort, where the
ramp alignment, along with the raised median barrier, provided poor sight distance under the bridge.
Operation and Design
With the exception of the Alcoa site, participants’ comments generally stated that the interchange
operated better than the previous diamond configuration. This may be due to the fact that the
Alcoa DCD was constructed in anticipation of future build out and its original design was not a
diamond interchange.
Concerns and areas for improvement in regards to operation and design were noted most often in
responses from the focus groups and surveys in the following areas:
48
■■
Ease of through movement at DCD;
■■
Coordination of signals at adjacent intersections;
■■
Queues and congestion at adjacent intersections;
■■
Opportunities for right turn on red (RTOR); and
■■
Positioning of advance signage.
Rochester survey respondents provided feedback on the complexity of overall driver paths with
regard to congestion and noted that the through movement was slightly more difficult than the left
turns on and off the freeway ramps. Several survey respondents expressed dissatisfaction with the
signal operation limiting protected left turns to a side road movement adjacent to the DCD.
Several participants at all sites noted that coordination of signals seemed counterintuitive. Because
the primary movements at four of the five sites surveyed are left turns off and onto the freeway,
the downstream signal coordination provided less than normal bandwidth for through movements.
This often caused drivers from upstream through movements to stop at the second downstream
signal of the DCD. As noted in the safety issues, this may be the cause of red light running and has
been reported to contribute to driver frustration.
Survey respondents from Lexington noted a significant problem with the closely spaced intersection
to the south at Beaumont Centre Parkway. Respondents noted severe congestion at this particular
intersection during the AM and PM peak periods, with queues backing up upwards of “a mile or
more” through the DCD in the AM peak hour. In Rochester, respondents clearly noted problems
with the two closely spaced intersections to the south. Respondents’ comments generally said, “It
would be nice if we had better signal timing or synchronization with adjacent signals,” meaning they
recognized that there were queue issues at the adjacent signals that had less mainline capacity than
the DCD. Some participants indicated systemic issues, notably that while the capacity of the DCD
interchange has improved, the adjacent intersections have now become problematic.
Survey respondents at the Lexington, KY, site noted that the no-RTOR condition on the eastbound
off-ramp caused significant queuing at the site during the PM period. Respondents noted that the
original design allowed a free-flow right turn movement. According to survey respondents, this
restriction now caused significant queuing back to the freeway. Right turns at the freeway offramp were discussed at all sites, particularly as RTOR was prohibited at the majority of sites. The
Kansas City site had a particularly interesting scenario because it was signed as no RTOR during
the transition period immediately following construction. However, during the focus group session,
which took place 6 months after the opening, the southbound right turn configuration was changed
to a channelized right turn. Participants favored the free-flow channelized right turn lane but called
out issues with weaving as vehicles tried to access driveway entrances on the opposing side of the
road after making this right turn.
Participants were generally satisfied with signage at the sites. Respondents noted that the advance
signing was instructive, but in some cases it should have been installed further back. Queues during
peak periods along the arterials often spill back far enough that some drivers were not able to preposition by the time they saw the signing—especially drivers wanting to turn left onto the freeway.
This left turn movement sometimes leads to heavy left lane utilization at the first DCD signal. For
instance, it was noted in Kansas City, MO, that trucks sometimes had problems with pre-positioning
and stopped under the bridge, blocking through traffic as they tried to merge into the left turn lane
to access the freeway on-ramp.
49
Walking, Bicycling, and Accessing Transit
Concerns for pedestrians were brought up at two of the focus groups. Feedback on bicycling
(including transit) was generated primarily from the surveys, and feedback was primarily negative
with the exception of the Kentucky DCD, where a paved bicycle and pedestrian pathway provided on
the outside of the roadway was well received by the majority of commenters. It should be noted that
the layout of the pedestrian facilities differed among the sites and that the Kentucky site is the only
site that provided full access through the DCD on a separate facility. Issues that were highlighted in
the surveys include:
■■
Placement and use of the walkway in the median;
■■
Long distances to crosswalks;
■■
Drivers disregarding pedestrian right-of-way at on-ramps or stopping in the crosswalk;
■■
Concern for bicyclist safety through an underpass facility due to space constraints;
■■
Snow removal from sidewalks; and
■■
Placement of “trail-sized” stop signs at crosswalks.
At the Kansas City site, pedestrians use the center median walkway to travel through the DCD.
Participants discussed issues with the pedestrian facilities at this site in some detail. They noted that
most pedestrians use the center walkway provided under the bridge but leave this facility prior to
the intersection, choosing to negotiate walking along the side of the roadway rather than using the
sidewalk that continues down the middle of the travel lanes to the next adjacent signal. They seemed
to believe that a crosswalk location across the “y-line” at the actual DCD intersection might have
been a better idea, as these users seemed to want to cross back over meeting pedestrian expectations.
In Alcoa, there were no pedestrian facilities installed with the DCD, which focus group participants
noted as a safety concern.
In Lexington, the Kentucky Transportation Center survey yielded 956 open feedback submissions on
the DCD interchange. Among those, 17 comments were related to walking and bicycling conditions.
Ten comments provided favorable feedback, mostly praising the new asphalt path providing access for
bicyclists and pedestrians where none existed before. On the other hand, there were five unfavorable
comments, which included three basic areas of concern. The primary shortfalls, according to
respondents, were short pedestrian walk phases, drivers encroaching into the crosswalk, and issues
regarding the use of trail-sized stop signs at crosswalks where pedestrians have the right-of-way.
In Rochester, 27 survey respondents provided specific feedback about pedestrian, bicycle, and transit
facilities. Most respondents indicated that bicycling or walking through this interchange would be
uncomfortable or dangerous, and comments were typically critical. One respondent noted motorists
often ignore pedestrian right-of-way at the on-ramps to the freeway where pedestrian facilities are
provided along the outside of the cross street. Areas of significant concern noted by bicyclists were
the limited amount of space though a crossover next to a barrier wall and that a bicycle lane ends
abruptly at a splitter island at the entrance to the interchange (Figure 4).
50
Figure 4. Issues with bicycle facilities at the Rochester DCD. Left: Bike lane ending
at splitter island on the approach to the DCD interchange. Right: Barrier wall and
inside shoulder limits bicycle operating space.
Conclusions and Recommendations
The team drew several conclusions from the focus groups and surveys conducted at the five DCD
interchanges regarding changes to DCD interchanges as a result of public perception through the
focus groups and survey strategies used. At four of the five sites, surveys and focus groups were
conducted following DCD implementation while a “before” and “after” survey was conducted at the
Rochester, NY, location.
Scope of Project
When designing a DCD, the impact of the design on the surrounding intersections, commercial
centers, and neighborhoods should be fully considered. Many focus group and survey participants
noted that local access at all hours may have been sacrificed to improve the experience for commuters,
particularly in the peak hours. It was suggested that a broader scope of impact should be considered
prior to final design and construction. Although the general reception of the DCDs by motorists
was positive, the design may need context-specific modification elsewhere given concerns related to
access, bicycle/pedestrian accommodations, signage, traffic signal timing, number of lanes, signal
treatment at adjacent intersections, education, and solutions to aid potential driver confusion,
which can cause wrong-way maneuvers.
Operation and Safety
Participants typically clustered safety and operations comments together, which is understandable
considering the complexity of many of the traffic scenarios described. Overall, participants were
generally supportive of the DCD at each site location, and it was generally agreed that overall safety
and operations had improved, although numerous respondents indicated that the interchange was
confusing, especially for infrequent drivers. Many of the comments pointed out issues that persisted
at adjacent intersections for turning motorists and frustration with signal timing both in the
interchange and at adjacent intersections. Education and enforcement were recommended as the
treatment for most problems. Law enforcement was cited as a way to increase driver compliance with
speeds and could possibly deter illegal maneuvers.
Driver Understanding
Respondents generally reported that driving through a DCD interchange was no more complex
than a conventional diamond interchange, although the comments from the surveys indicate
51
that observations of driver confusion were common. This finding suggests that the experienced
commuters responding to the survey were not likely to experience driver confusion; however, novice
drivers with less exposure may initially have problems. Many concerns related to driver confusion are
often touted, and more research may be needed to understand to what extent this is true.
Effects on Nearby Intersections
The majority of negative comments given by survey or focus group participants were related to
nearby intersections. Left-turning issues at adjacent signals were identified as creating long waits
and queuing at some approaches of the adjacent intersection. Issues with adjacent intersections were
identified at almost every location surveyed, suggesting that this problem was not as prevalent with
the previous design. Field observations found this was a noticeable problem at some DCDs due to
the efficient two-phase signal operation at the interchange providing additional thru traffic that
adjacent intersections were not able to readily process.
Turning Movements
The problem with right turns at the off-ramps was brought up multiple times at all sites. Participants
noted at four of the five sites that they could no longer turn right on red and that queues at many
off-ramp locations backed up much farther than at the conventional diamond interchange. At the
one site studied that allowed RTOR, participants noted a serious safety concern that needed to be
addressed: that right-turning vehicles were frequently making poor decisions about when to turn
on red. Focus group participants recommended moving the right turns at the off-ramps farther
away from the primary intersection or providing channelized right turns with an acceleration lane to
alleviate RTOR conflict and add additional capacity. In theory, these ideas sound promising; however,
these movements will require additional right-of-way and some consideration on how to address the
quick weaving maneuver to get to the left turn at an adjacent intersection in close proximity to the
interchange. Safety for bicyclists and pedestrians would also need to be considered at any location
where facilities for nonmotorized travelers may cross a free-flow ramp or channelized right turn lane,
creating additional conflict points or the potential for more serious crashes.
In Rochester, left turn movements on and off the freeway were considered much safer than at the
previous conventional diamond interchange. Respondents’ views on the safety and operation of the
three primary movements (a through, a left onto the freeway, and a left off the freeway) switched
after installation of the DCD. Instead of left turn movements being the problem, respondents now
perceived through movements as the most congested.
Pedestrian and Bicycle Facilities
The majority of participants in the focus groups didn’t use the pedestrian and bicycle facilities,
but the comments from the surveys expressed some concerns and problem areas in the design
of facilities. If the pedestrian walkway is designed to use the center of the road, designers should
recognize that pedestrians will immediately want to go back to the left or right side of the road once
they are past the crossover. Care should be taken to make sure that these facilities have good sight
distance for pedestrians and drivers, and if sufficient gaps are not available, signalization or some
other treatment may be necessary to make sure pedestrians and bicyclists who use the sidewalk are
safely accommodated. Lastly, if bicycle lanes are added to the roadway, adequate operating space
must be provided adjacent to any barrier on the right-hand side of the roadway between the two
DCD intersections. Bicycle lanes should not end abruptly at the crossovers.
52
Public Outreach
It is highly recommended that agencies installing a DCD conduct similar focus groups or surveys.
This provides the public an opportunity to express their opinions, and these viewpoints often
provide real issues and practical opinions that should be considered, especially as designs are vetted.
Focus groups take more effort to organize due to the need to find a location and participants. As
the research team learned through this effort, willing participants do not always attend. Conducting
a similar comparison survey prior to and after the installation of unconventional interchanges is a
potential way for designers and engineers to qualitatively estimate how new types of interchanges
are perceived. A variety of free services exist for agencies to create and disseminate a public survey
online. It is recommended that an outreach plan be established to increase response rates within a
community and gain a wider sample of public opinion. If transit stops are located near an interchange,
a targeted strategy may be needed to get a response from transit users.
Suggestions for Future Research
In order to break down the barriers to the use of DCD interchanges, public support and acceptance
is an important area of future research. Similar before and after studies—using a method that can
show a statistically significant result using the same respondents, or a survey that obtains a larger
convenience sample—should be conducted to determine the success of a DCD project as perceived
by the public and obtain results that can be more readily generalized. It is important to collect
demographic information in order to understand the types of respondents who complete the survey
(and to see if they are representative of the general population) and understand the bias that might
be prevalent in the users’ opinions if a convenience sample is used. To gain a deeper understanding
of respondent opinions, any method of outreach should give an opportunity for guided open-ended
responses. These methods indicate areas in which to improve the DCD to gain public acceptance.
These public outreach methods indicate that specific changes could be made to increase support
for DCD interchanges and increase user satisfaction with the project. These include broadening the
project scope to include adjacent interchanges, making timing adjustments with signal operations,
and including facilities to accommodate both bicyclist and pedestrian travel. Additionally, further
research could be conducted to determine the real and perceived effect of driver confusion and
potential for wrong-way maneuvers at a DCD interchange.
Acknowledgments
The study on which this paper is based was funded by the Federal Highway Administration under
project DTFH61-10-C-00029. The authors would like to thank FHWA for their support throughout
this project. The authors also thank all of the participants in the focus groups and surveys, along
with the officials at the five DCD sites. The views and opinions in the paper are those of the authors
only. The authors are fully responsible for any errors or omissions.
53
Works Cited
1. Hughes, W., R. Jagannathan, D. Sengupta, and J.E. Hummer. Alternative Intersections/Interchanges:
Informational Report (AIIR). FHWA-HRT-09-060. Washington, DC: U.S. Department of Transportation
Federal Highway Administration, 2010.
2. Missouri Department of Transportation. Missouri’s Experience with a Diverging Diamond Interchange—
Lessons Learned. Report OR 10-021. May 2010.
3. Chlewicki, G. “Learning from Six (Plus) Operational DDIs in the US.” In 2012 ITE Midwestern
District Conference and TRB 4th Urban Street Symposium, 2012.
4. Shumaker, M.L., J.E. Hummer, and L.F. Huntsinger. “Barriers to Implementation of Unconventional
Intersection Designs: A Survey of Transportation Professionals.” Public Works Management & Policy,
Vol. 18, No. 3 (2013): 244–262.
5. Hummer, J.E., R.L. Haley, S.E. Ott, R.S. Foyle, and C.M. Cunningham. Superstreet Benefits and Capacities. 2010.
6. Bared, J.G., T. Granda, and A. Zineddin. Drivers’ Evaluation of the Diverging Diamond Interchange. Federal
Highway Administration, 2007.
7. Kirk, A. US 68 & KY 4 Double Crossover Diamond Evaluation. Lexington, KY: Kentucky Transportation
Center, University of Kentucky, 2012.
Kristy Jackson is a research associate in the Bicycle and Pedestrian Program at the Institute
for Transportation Research and Education at North Carolina (N.C.) State University. She has
provided support on a wide range of multimodal projects and has experience in research on
bicycle and pedestrian modes, development of educational materials for bicycling and walking,
and facilitating public involvement. She contributes to the advancement of bicycling and
pedestrian data collection in GIS and traffic monitoring. She holds a master’s degree in urban planning from
the University of Wisconsin-Milwaukee and a B.S. from the University of Wisconsin-Madison.
Christopher M. Cunningham, P.E., is a program manager in the Highway Systems Group at
the Institute for Transportation Research and Education (ITRE) in Raleigh, NC, USA. He
specializes in operational analysis of transportation systems, applications of traffic analysis
tools, safety analysis, and custom traffic engineering studies. He holds a bachelor of science
and a master’s degree in civil engineering from N.C. State University.
Chunho Yeom is a research assistant at the Institute for Transportation Research and
Education (ITRE) in Raleigh, NC, USA. He is studying for a Ph.D. at N.C. State University,
participating in a diverging diamond interchange and freeway work zone capacity project.
He holds a master’s degree in civil engineering from N.C. State University.
Joseph E. Hummer, Ph.D., P.E., is professor and chair of the Department of Civil and
Environmental Engineering at Wayne State University in Detroit, MI, USA. He has specialized
in research on alternative intersections and interchanges for 25 years. He has a Ph.D. from
Purdue and an M.S. and B.S. from Michigan State University. He is a member of ITE.
Adam Kirk, Ph.D., P.E., PTOE, AICP, is a principal research engineer with the Kentucky
Transportation Center at the University of Kentucky. In that role he manages the Center for
Advanced Transportation Solutions Laboratory (CATSLab), a state-of-the-art traffic engineering
laboratory used to direct academic and professional engineering learning and applied research.
He holds a B.S. and a Ph.D. from the University of Kentucky and an M.S. from the University of
Washington. He is a member of ITE.
54
A Methodology Using GPS to Inventory
University Campus Parking
By Brian Maleck, Wayne A. Sarasua, Ph.D., P.E., Jennifer Ogle, Ph.D., P.E., and Kweku Brown
Global positioning systems (GPSs) have been used by both public and private entities to
collect the locations of transportation assets and other spatial data including traffic signs, bus
stops, bridges and culverts, and incident locations. In combination with geographic information
systems, GPS data enable asset managers to track changes in assets and conduct “what if ”
assessments to aid in improved system management. This research explores the use of GPS
to inventory individual parking space data, and subsequently generate a geospatial parking
management system for Clemson University. On a growing college campus, with new buildings
now occupying former surface parking lots and peak parking utilization rates reaching 95
percent, accurate and aggressive management of this commodity is a priority.
While handheld GPS data collection devices provide opportunities to locate individual
parking spaces for development of comprehensive space-by-space parking inventory maps,
most published parking inventory studies have been conducted with pen and paper, limiting
data to counts by lots or street segments. Collecting GPS locations for individual parking
spaces provides a unique challenge due to the relative proximity of one space to another.
Even small spatial errors that are inherent in GPS data collection not only are apparent but
could compromise effective use of the data. This research combines the use of Wide Area
Augmentation System–enabled GPS with digital aerial/satellite imagery and computeraided design (CAD) as-built drawings to locate and inventory individual parking spaces. A
methodology was developed to enhance the GPS locations to match the underlying CAD and
aerial maps.
55
Introduction
Clemson University is a land grant institution located in the South Carolina, USA foothills, with more
than 19,000 students and growing. Along with the recent growth in the student population, new
building construction has replaced some of the existing surface lots, and the demand for parking has
become a significant issue—especially for major permit holders including student commuters and
residents and employees. As these lots have been taken for new construction, the occupancy rates
on campus have. Most parking managers agree on the 85 percent occupancy rule of thumb: “When
parking occupancy exceeds 85 percent capacity, parking supply becomes constrained.”1 According
to the 2012 Clemson University parking utilization study, the overall parking occupancy during
weekday morning hours is 86 percent of available capacity. The highest occupancy rate on campus
was 95 percent, and was observed for both student commuter and resident permit holders. Employee
lots were not far behind at 89 percent occupancy. With this overall level of parking utilization, it is
imperative to ascertain if there are any underutilized spaces on campus. Thus, the campus parking
manager can ensure efficient use of all resources before making capital investments in new parking
facilities. Not only are parking lots expensive, but they take up significant green space on campus
at roughly 300 square feet per space.2 If parking garages are required, capital investments increase
substantially, with an average per-space price tag of $30,000.2
Given the plethora of construction activities on campus over the last few years, the Parking and
Transportation Services Office has been placed in a reactive position. The parking situation is
further exacerbated by monumental demand for parking during Clemson home football games. The
loss of spaces—particularly those central to campus—has necessitated significant shifts in permit
designations for numerous lots along with changes in transit services and the adoption of several
transportation demand management strategies (i.e., car-sharing, carpool, bike programs, etc.). The
reconfiguration and re-marking of many parking lots has wreaked havoc on the campus parking
inventory, because there was no formal method in place to track the individual space changes. In
some instances, the permit type for whole lots has changed; for other lots, only a portion of the
spaces have been redesignated. In some lots there were even additional spaces added to the lot during
re-marking. Regardless, the actual number of parking spaces by permit type for a number of lots was
uncertain going into this study. In addition to the sheer quantity of spaces by permit type, Clemson
Parking and Transportation Services Office was interested in knowing precise details about all of the
spaces on campus including:
■■
Exact location (latitude and longitude);
■■
Unique identifier (lot/street, row, space number);
■■
Space dimensions (length and width);
■■
Parking type (perpendicular, parallel, or angled);
■■
Permit/space designation (commuter, resident, employee, motorcycle, service vehicle, Americans
with Disabilities Act [ADA], low emission vehicle [LEV], WeCar, carpool, etc.);
■■
If designated ADA, ADA compliance (cross-slope, running slope, ramp access to adjacent sidewalk,
signage, markings, etc.); and
■■
Comments on problems (drainage issues, potholes, faded/missing paint or markings, etc.).
A detailed spatial inventory of spaces would allow for efficient work orders to be processed by lot
or by problem type. However, with more than 12,000 parking spaces on campus, inventory data
collection was viewed as a daunting task. Further, researchers were uncertain if the spatial aspects
could be accurately collected with pen and paper, and the likelihood of data entry errors increases
56
with each successive processing step. Thus, researchers decided to attempt to use a mapping-grade
global positioning system (GPS) receiver with a touch-screen data entry interface to conduct the
inventory. This technology was chosen as the primary geocoding tool because the research team
had experience using the device to assist in the collection of transit data and campus bike rack
locations. This paper discusses the development and implementation of a methodology for using
GPS to conduct the Clemson campus parking inventory. Various issues of concern related to GPS
data collection are covered, along with recommendations for successfully adopting these methods
at other sites. The final system is envisioned as a tool for future campus planning activities as well as
for aiding in better management of the parking assets.
Literature Review
Asset management is a strategic method of allocating resources to operate and maintain infrastructure
for optimal performance.3 Strategic implies that there are goals, objectives, and performance targets to
be met with respect to the infrastructure, and that all decisions for funding distributions would refer
to this guidance to ensure the most efficient use of resources to attain the goals. Asset management
systems improve efficiency, increase productivity, add accountability, and increase the ease of use of
assets. These benefits come from a data-focused approach to managing systems.4
Advancements in technology have made data collection easier and more efficient (i.e., paper and
pen–based collection to electronic collection, survey to GPS, etc.).5 More efficient collection allows
more comprehensive and accurate data to be collected, but if the agencies are not prepared to use the
data by linking them to decision-making at all levels, the data may not be worth the investment. In
some cases high-level performance data such as overall parking occupancy rate may be enough data
to make a decision at the system-monitoring level. However, in a capacity-constrained environment,
such as the one that Clemson University is operating in now, more data are needed to best utilize
all available parking infrastructures and select projects that will extend the life of the existing
infrastructure. An example is capturing the occupancy rate for specific transportation demand
management spaces (i.e., carpool, motorcycle, and even bicycle parking).
Many departments of transportation (DOTs) have realized the capabilities of GPSs to collect the
locations of numerous transportation assets such as signs, bridges, transit infrastructure, and
roadway conditions. North Carolina, USA, and Louisiana, USA, DOTs have employed GPSs to
collect sign inventory data to comply with regulations.6,7 These states cite that GPS was highly
effective in combination with a geographic information system (GIS) to map signs in the state. GPS
accurately provides the location of the signs, and GIS can display the locations along with associated
attributes, such as retro-reflectivity, condition, and type of sign. GPS has also been used to collect
information on bus stops in Atlanta, Georgia, USA, prior to the 1996 Summer Olympic Games. In
this study, handheld GPS devices combined with postprocess differential correction for enhanced
spatial accuracy were used to collect location information. A user interface on a notebook computer
was used to collect bus stop attributes such as marker type, whether or not a shelter was present, and
if access to the bus stop was ADA accessible.8 GPS and GIS have also been used to inventory large
sections of pavement for condition assessments, as well as siting bicycle parking facilities.9,10
While handheld GPS data collection devices have been used since the mid-90s for various asset
management applications, they have not been widely adopted for parking asset management. Most
published parking inventory studies only record the location and type of parking facilities down to
lot/garage level for off-street spaces, and down to street block level for on-street spaces. While much
of this is collected by pen and paper, some GISs have been developed to visualize and analyze the
zonal data.11,12 A variety of parking studies have been conducted in the last few years that focused on
downtowns.1,2,13–23 The typical goal of these studies is to determine the supply and demand for parking
in the downtown area to ensure adequate parking is available for all users. It should be noted that all
57
of these studies were conducted using paper forms, and inventories were usually collected just prior
to the utilization data collection—indicating that most cities do not have a formal parking asset
management system. There are a number of differences between downtown parking management
studies and those conducted for college campuses. For example, university campuses are often selfcontained and all parking is on university property, so ownership data are not necessary. Further,
universities usually provide permits to regular users (employees and students), and thus only visitors
may need to park in pay lots, so the cost of the parking is typically tied to the permit. In downtowns,
parking is usually inventoried by lot or street; however, on a university campus with broad zone
parking, users buy a certain type of permit and park in spaces designated for that permit. This is
the type of parking system that Clemson University employs. From an inventory perspective, this
can be complicated because there may be 2 service vehicle spaces, 20 faculty spaces, 2 ADA spaces,
80 student spaces, 1 carpool space, and 2 LEV spaces in one parking lot. Thus, inventory data and
tracking at the individual space level are important.
Some cities, such as Bloomington, Indiana, USA, actually have GIS layers with individual parking
spaces identified, but the data were digitized from existing drawings and design files.24 So individual
space data exist, but they were not collected via GPS. Today, new technologies exist that can provide
real-time parking space occupancy on a space-by-space basis using an embedded sensor. An added
benefit of these technologies is that they are tied to GISs and can wirelessly transmit data to populate
online map applications used by drivers to navigate to available parking.25 Unfortunately, there is
limited application of the new technologies, and most have been used for special parking situations
like accessible parking spaces and visitor parking spaces.
Collecting GPS locations for individual parking spaces provides a unique challenge due to the
relative proximity of one space to another. Even small spatial errors that are inherent in GPS data
collection are not only apparent but could compromise effective use of the data. In addition, vehicle
occupancy within the parking space precludes a data collector from obtaining the centroid of
the space using GPS. The accuracy of GPS points can be absolute or relative. Absolute accuracy
compares the data that a GPS collects to the actual location on the earth. Relative accuracy refers to
the relative positioning of collected points in reference to one another. Using the GPS coordinates of
two collected points, the distance is easily calculated. If the actual distance is equal to the calculated
distance, then the relative accuracy of the two points is good. It is possible for points to have good
relative accuracy but have poor absolute accuracy if the cluster of points is systematically shifted
from their true location. Relative accuracy is just as important (and maybe more so) than absolute
accuracy because of the relative proximity of parking spaces.
A standard GPS device such as a smartphone or GPS device in a car can have an absolute accuracy
of about 15 meters. This is accurate enough for many applications; however, this would not be
sufficient to identify individual parking spaces. Extra accuracy can be achieved using a process called
differential correction. This method of improving accuracy relies on two receivers, one at a known
location and another collecting data. The station at a known location calculates ranging parameters
based on satellite signals and compares this information to actual ranging parameters between the
known location of satellites and the known location of the station. Differences in ranging parameters
are calculated and applied to the data being received by the second device. This will correct for a
variety of errors and increase accuracy to within a few meters.26
A very convenient type of differential correction that only requires one receiver is provided through
the Federal Aviation Administration’s Wide Area Augmentation System, or WAAS. WAAS works via
25 ground stations that monitor satellite data. These stations compare the data to those of reference
stations and correct for orbit, atmospheric, ionospheric, and clock drift errors. This corrected
message is sent to one of two satellites in a fixed position over the equator. These satellites broadcast
the corrections, which are processed by compatible GPS receivers in real time. The result of this
58
correction is accuracy of less than 3 meters.27 Actual performance measurements of the system at
specific locations have shown that it typically provides better than 1.0 meter laterally throughout
most of the contiguous United States and large parts of Canada and Alaska, USA.28 WAAS correction
is available without cost to anyone using a WAAS-enabled GPS receiver.
Real Time Kinematic (RTK) GPS can enhance GPS quality even further. This method of improving
accuracy also relies on two receivers, one at a known location and another collecting data; however,
these units use precise measurements of the phase of the GPS signal’s high-resolution carrier wave,
rather than the low-resolution GPS code contained in the signal. Surveying-quality RTK GPS can
provide sub-centimeter-level accuracy in real time; however, these receivers can cost many thousands
of dollars and at least two are needed to achieve the specified accuracy.29
This research combines the use of GPS with digital aerial/satellite imagery and computer-aided
design (CAD) as-built drawings to locate and inventory individual parking spaces. A methodology
was developed to enhance the GPS locations to match the underlying CAD and aerial maps. The GPS
receiver used in this research is WAAS enabled. There are several other potential errors associated
with GPS data collection that will be discussed further in the Results section of this paper.
Methodology
The GPS device chosen for the parking inventory was acquired from PinPoint GeoTech, LLC,
specifically designed for public works inventory applications. The device is a mapping-grade unit
with enhanced accuracy through WAAS real-time differential correction. This device was chosen over
a surveying-grade unit because of its ease of use and relatively low cost (~$3,000). Another benefit is
that PinPoint’s offices are located in Clemson, close to campus. This provided timely local customer
support for any problems with the GPS device. Further, the PinPoint device’s customizable interface
facilitated creating a user interface that would simplify data collection.
Initial Field Test
One of the initial steps in preparing for the inventory was to determine if the PinPoint GPS would be
practical. A test was conducted on a sample row of parking spaces to ensure that the GPS would give
acceptable accuracy for the collection and be suitable for collecting the related parking space attributes.
Parking spaces provide a unique challenge due to the relative proximity of one space to another. Even
small spatial errors that are inherent in GPS data collection are apparent. Prior to conducting the test,
the interface was edited to simplify the collection of parking attribute data related to each space. The test
data were collected in June 2012. The collected data were downloaded from the PinPoint GPS and were
transferred to a GIS for display and analysis. The mapped GPS points were overlaid onto a Bing digital
orthophoto, and comparisons were made with regard to a point’s location and the underlying parking
space displayed on the map. Clemson standard perpendicular and angled parking spaces are typically
8.5 feet wide, and location data were collected at an approximate midpoint between the parking space
lines for each space. Thus, an error of +/- 4 feet, which is possible with a WAAS-enabled GPS, should
theoretically fall within the parking space lines. Upon inspection, initially none of the GPS points fell
within the parking spaces displayed in the orthophoto. However, the relative distance between each
collected point was 8.5 feet on average. Thus, the relative accuracy of the PinPoint GPS was quite good.
The absolute accuracy was actually better than first believed, because it was later found that the Bing
map was shifted slightly from nearby ground control points. Moving the digital orthophoto so that
one of the points fell within its corresponding parking space resulted in all of the points falling within
their corresponding parking spaces.
59
Campus-wide Data Collection
After the successful test, the researchers proceeded to collect field data in each parking lot on campus.
Because GPS satellites orbit the earth twice a day, satellite coverage varies continuously. A measure of
satellite coverage is known as position dilution of precision (PDOP). A PDOP of 1 is the best value
possible. Values under 3 are very good. Figure 1 shows an example of mission planning charts during
one of the collection days. The top figure shows how PDOP varied throughout the day, deteriorating
after 12:00 p.m. and recovering at about 1:30 p.m. The sky plot on the bottom left shows how all
seven available satellites are clustered above an elevation angle of 30 degrees, resulting in a PDOP of
4.7. Only an hour later, there were 11 satellites at or above the 10-degree mask angle and the PDOP
improved to 1.5. This illustrates the importance of conducting mission planning prior to doing a
GPS survey to maximize accuracy.
Figure 1. GPS mission-planning PDOP and Skyplot charts.
60
Clemson University does not have parking garages but does have varied cover in the parking lots.
Most lots have some spaces that are near or under trees, or nearby buildings that can degrade PDOP
below the maximum value possible identified during mission planning. The buildings can also cause
multipath error, further degrading accuracy.
Office Processing
After the parking space data were collected, they were transferred to a desktop computer using
PinPoint GeoTech software. The data upload process was completed after every data collection
session to minimize risk of data loss. Once a data set was moved from the device to the computer, it
was exported into a format that could be opened in Microsoft Excel. The data were initially saved by
lot name but were eventually merged into a single spreadsheet containing totals for each lot and for
the entire campus. The data were also converted to AutoCAD and ArcGIS.
The next step was to check attribute information to make sure all of the fields were populated
correctly. PDOP values were reviewed to make sure they were acceptable and matched the missionplanning values. Some values were higher, but this was expected due to the tree canopies and nearby
buildings in some areas of the parking lots.
AutoCAD As-built Map Update
Once all data were collected and exported from the PinPoint software into Microsoft Excel, the data
were used to update the CAD map of campus. The Clemson University Facilities Department maintains
an AutoCAD as-built map of campus. This map includes buildings, roads, utility lines, and lighting.
However, a glaring omission from this map was parking spaces. The outlines of parking lots, including
curb area, are included in the Facilities map. Therefore, using the row and space number attribute
information collected during the inventory, each parking lot row can be filled in with the appropriate
number of parking spaces. The number of parking spaces in each row was obtained using the countif
function in Microsoft Excel. Knowing the number of spaces in each row, an array of spaces was drawn
in AutoCAD using common dimensions and accounting for the wider handicap spaces. Figure 2 shows
an updated as-built map before and after the parking spaces were added.
Figure 2. AutoCAD as-built map before and after parking spaces were added.
61
The original as-built map from Campus Facilities was geo-referenced to South Carolina State Plane
coordinates. This made it easy to import into ArcGIS and align with a background digital orthophoto
from Bing Maps. Both the AutoCAD map and the digital orthophoto map had to be adjusted based
on control points to ensure that the two maps matched and were spatially accurate. Figure 3 shows
the corrected overlay for one of the parking lots. The figure shows that the CAD parking lot lines
lined up reasonably well with the digital orthophoto lines. In some cases it was necessary to adjust
some of the CAD parking lot lines because the parking space width was not always uniform.
Figure 3. Overlay of adjusted orthophoto and CAD maps.
62
Displaying and Adjusting GPS Points
The GPS point data were imported into the GIS using longitude and latitude coordinates (WGS84
Datum). When the data were first imported, it was found that the individual spaces did not match
exactly with the AutoCAD map. While it was expected that there were going to be absolute positional
errors, the relative positioning errors were greater than anticipated. Figure 4 shows a plot of the
GPS points overlaid onto the AutoCAD drawing. Errors are clearly evident; however, one-to-one
correspondence between GPS points and the parking lot spaces was not difficult for a number of
reasons. First, the majority of the collected data were relatively close to the actual spaces. Second,
because there was usually reasonable separation between parking lot rows, it was relatively easy to
determine what spaces were associated with each row. In all cases, the number of spaces collected
for a row matched the number of spaces in the CAD map. Note that the orthophoto map could not
be used for this because some spaces were entirely covered by trees. Third, included in the collected
attributes were the row numbers as well as parking space numbers. The researchers were careful to
collect spaces in order along a row; thus, the space number could be used to check if the positional
errors caused spaces to be out of order. In order to correct the positional errors, the editor tool in
ArcGIS was used. Each space was moved on the display to match a particular parking space drawn
in AutoCAD. This process was repeated for all of the lots on campus. Figures 4 and 5 show raw and
corrected point data for one of the lots.
Figure 4. GPS point data before correction.
63
Figure 5. GPS point data after correction using the ArcGIS edit tool.
GPS Errors
The research team did an investigation on the cause of errors to see why the relative (and absolute)
positioning of the point data was not as anticipated. PDOP was the first measure that was checked.
Note the area circled in Figure 4. A few of the points at this location seem to have experienced
greater relative error than other points. Initially, the researchers were confident that this was due
to an instantaneous change in PDOP and satellite availability; however, this was found not to be
the case. In fact, the PDOP values for the entire lot were all under 2.5 and were actually in the 1.5
to 1.7 range in the area circled in Figure 4. The satellite availability also did not change in that area.
The next possible cause of relative error was thought to be GPS multipath error. While this parking
lot has trees in the medians, there are no nearby buildings that would extend above the 10-degree
mask angle. Further, there are relatively few trees in the vicinity of the circled area; thus, multipath
problems did not seem logical for this location. One other possibility was that the WAAS differential
correction was not applied to these points. Unfortunately, the PinPoint device did not include an
attribute on whether or not a data point was corrected, so there was no way of telling if this was the
case. Some other problem had to exist.
Data Collection Unit Truncated Decimals
Table 1 shows a sample of the GPS data collected for one of the parking lots. The attributes shown
are those that are collected by the GPS unit (i.e., Point ID, Positional Dilution of Precision, Latitude,
Longitude, and Number of Satellites Visible [SV]). Other attributes, such as those collected by the
researcher in the field, are not shown. Upon exploring the data from the PinPoint device, it was
evident that some of the coordinates for some of the points were truncated. It was not clear why this
64
happened—even after talking to the PinPoint representative—except that it likely had something to
do with zeroes after the decimal point. In the worst cases, some coordinates were truncated to only
four decimal places, while others were truncated after the fifth decimal and still others after the
sixth decimal place. It was calculated that truncating to four decimal places could potentially lead
to coordinate errors of +/- 40 feet or more depending on whether both the longitude and latitude
values were truncated. Likewise, truncating to five decimal places could potentially lead to coordinate
errors of +/- 4 to 6 feet. The circled points in Figure 4 had truncated coordinates, which explains the
relative error problems with the points at that location.
Table 1. PinPoint device sample attributes.
Point
PDOP
Date and Time
Latitude
Longitude
No of SV
25
2.0
6/19/2012 12:59
34.67293667
-82.83529833
7
26
2.0
6/19/2012 13:00
34.67291833
-82.835295
7
27
2.0
6/19/2012 13:01
34.67288
-82.835305
7
28
2.8
6/19/2012 13:01
34.67285667
-82.83532
7
29
2.8
6/19/2012 13:02
34.672845
-82.83533833
7
30
2.8
6/19/2012 13:02
34.67279333
-82.83529
7
31
2.8
6/19/2012 13:03
34.67283
-82.83526
7
32
2.8
6/19/2012 13:03
34.67287167
-82.83525833
7
33
2.9
6/19/2012 13:04
34.67289333
-82.83523833
6
34
2.9
6/19/2012 13:04
34.67290667
-82.83522333
6
35
2.9
6/19/2012 13:05
34.67293
-82.83522
6
Testing with a Different GPS Unit
Because of the systematic errors associated with the PinPoint device, the researchers decided to
collect additional data with a different WAAS-enabled GPS unit. In this experiment, a slightly more
expensive (~$5,000) Trimble GeoExplorer 6000 XT was used. The GeoExplorer is also capable of
collecting a customizable set of attributes. The locations of the raw data overlaid onto a CAD asbuilt map are shown in Figure 6. For the most part, the points shown in Figure 6 line up nearly
perfectly with the underlying parking spaces shown on the CAD layer. The PDOP values for all of
the points were less than 3 except for the three points on the west side of the map that had PDOP
values of more than 6. Higher PDOP values resulted in these points being farther from their correct
locations (as shown by the arrows). These high PDOP values were due to the research team purposely
blocking part of the receiver’s antenna so that some satellites would not be in view of the receiver.
Table 2 shows sample attribute data from the GeoExplorer. The coordinate data collected by the
GeoExplorer were projected into South Carolina State Plane cordinates, with the units being feet. The
data were collected to three decimal places. As can be seen, the values here are not rounded, resulting
in more precise coordinates. Note that one of the attributes shown in the table is “Correction Type.”
SBAS stands for satellite-based augmentation system. WAAS is classified as an SBAS. Not only did the
erroneous points in Figure 6 have high PDOP values, but they were also classified as uncorrected, which
would also explain their error relative to the other points. The test of the GeoExplorer demonstrates
the effectiveness of a WAAS-enabled GPS device for collecting parking data assets. Data points with
low PDOP are very accurate and can be used for inventory and asset management purposes.
65
Figure 6. GPS points collected with a Trimble GeoExplorer 6000 with associated
PDOP values (note that higher PDOP values indicate greater positional error).
Table 2. Sample GeoExplorer attribute data.
Point
PDOP
Date
Time
Northing
Easting
Correction Type
45
1.9
7/1/2013
09:56:16 am
1040178.808
1449124.477
Real-time SBAS Corrected
46
2.1
7/1/2013
09:56:37 am
1040181.224
1449133.494
47
1.9
7/1/2013
09:57:07 am
1040182.858
1449143.438
48
1.9
7/1/2013
09:57:34 am
1040183.782
1449152.066
49
2.0
7/1/2013
09:58:01 am
1040185.299
1449160.697
50
3.5
7/1/2013
09:59:08 am
1040180.286
1449178.754
Uncorrected
51
3.5
7/1/2013
10:00:38 am
1040200.819
1449207.964
Uncorrected
52
6.9
7/1/2013
10:01:10 am
1040207.840
1449221.468
Uncorrected
53
6.6
7/1/2013
10:01:35 am
1040194.587
1449242.878
Uncorrected
55
2.5
7/1/2013
10:04:31 am
1040203.266
1449230.731
56
2.5
7/1/2013
10:04:49 am
1040206.634
1449238.363
Conclusions and Recommendations
This paper investigated the use of multiple WAAS-enabled GPS units to inventory parking asset data
on Clemson University’s campus. Using underlying CAD as-built and digital orthophoto maps, the
GPS data were easily geocoded so that the points corresponded to the underlying parking spaces.
The lower-cost unit experienced errors in the GPS data caused by coordinates being rounded or
truncated by either the GPS unit or by the processing software. The second, more expensive WAASenabled GPS unit was tested, and its accuracy was found to be much better than that of the first
GPS unit. Only a very minor correction was needed for a small percentage of points. The ability to
collect parking space data using mapping-quality GPS receivers shows that much more expensive
surveying-quality units are not necessary. Surveying-quality receivers are also more time-consuming
66
to use, because they require a base station to be set up for differential correction (unless continuously
operating reference station [CORS]/online positional user service [OPUS] is used). While the second
GPS unit proved to be much more accurate than the first, it still had issues in locations where the
GPS and/or the WAAS signals were blocked. Even these erroneous points could be located accurately
by examining the initial maps and the associated attributes.
The techniques used in this research should be easily transferable to other locations. While digital
orthographic maps are available at a reasonable scale throughout the United States, the quality of
these maps may not be as good outside the United States. One of the advantages of using Clemson
University as a test bed for this application is the availability of CAD as-built maps. CAD map coverage
is not widespread, even in the United States. However, the editing of collected GPS points could have
been done almost as efficiently using just digital orthophotos as reference. It is noteworthy that
using digital orthophotos to conduct the inventory without the use of GPS in the field would have
resulted in a significant number of missed parking spots due to the tree canopy and the difficulty of
clearly identifying parking lot lines.
With the completion of this parking inventory system, Clemson University now has an accurate
count of spaces, designations, and accompanying utilization data. Spot utilization studies have been
conducted on spaces that had lower than average utilization rates to determine if these would best
serve the campus transportation system under a different permit designation. Several areas have
been converted to provide additional spaces for commuter/residential and employee permit holders
to bring these utilization rates down from 95 percent and 89 percent, respectively. While this is likely
not a long-term solution given campus expansion plans, the short-term provision of redesignating
spaces to meet demand does relieve the problems temporarily to buy time for longer-term solutions
to be studied and funded. A key aspect of the inventory system was a fully documented change order
system to identify when changes are made to add or remove spaces or redesignate spaces to ensure
an accurate portrayal of Clemson’s parking supply. Several options are on the table for long-term
planning, such as building a new surface lot, disallowing freshman from bringing cars to campus,
and setting up off-campus park and ride lots, as well as a host of other transportation demand
management strategies. However, it is clear that Clemson University will make every last space count
along the way.
Works Cited
1.
“City of Bozeman, Montana Parking Study.” Bozeman Unified Development Ordinance. City
of Bozeman, Montana, January 30, 2010.
2.
Denver Strategic Parking Plan. City of Denver, CO, October 2010.
3.
Asset Management Primer. Washington, DC: U.S. Department of Transportation, Federal
Highway Administration, Office of Asset Management, 1999.
4.
Asset Management Data Collection for Supporting Decision Processes. Washington, DC: U.S.
Department of Transportation, Federal Highway Administration, 2006.
5.
Bonsall, P.W. “The Changing Face of Parking-Related Data Collection and Analysis: The Role
of New Technologies.” Transportation, Vol. 18, No.1 (1991): 83–106.
6.
Vereen, S., J. Hummer, and W. Rasdorf. A Sign Inventory to Assess and Control Liability and Cost.
FHWA/NC/2002-017. Raleigh, NC: North Carolina Department of Transportation, 2002.
7.
Wolshon, B. Louisiana Traffic Sign Inventory and Management System. Report No. 381. Baton
Rouge, Louisiana: Louisiana Transportation Research Center, 2003.
67
8.
Sarasua et al. “Design and Development of a Bus Stop Inventory to Support an Intelligent
Transportation System: The Marta Experience.” Journal of Public Transportation, Vol. 1, No. 4 (1998).
9.
Huang, B., T.F. Fwa, W.T. Chan, and S.B. Liu. “Implementation of GIS/GPS-Based Airport
Pavement Management System: A Case Study.” 6th International Conference on Managing
Pavements, Vol. 10, Queensland, Australia, October 2004.
10. Leigh, C., J. Peterson, and S. Chandra. “Campus Bicycle-Parking Facility Site Selection:
Exemplifying Provision of an Interactive Facility Map.” Proceedings of Surveying & Spatial Sciences
Institute Biennial International Conference, Vol. 28, September 2009.
11. Dunn, M., R. Shields, and W. Yue. “The Application of GIS in CBD Parking Management.”
Journal of the Eastern Asia Society of Transportation Studies, Vol. 3, No. 3 (September 1999).
12. Lau, Wilfred W.T., et al. “The Hong Kong Second Parking Demand Study.” Proceedings of the ICETransport, Vol. 158, No.1 (2005): 53–59.
13. Rich and Associates. “City of Billings Downtown Parking Plan.” City of Billings, Montana,
January 2010.
14. Carl Walker, Inc. and Crandall Arambula. “Task Report: Current Parking Program Assessment
& Supply/Demand Summary.” City of Missoula, Montana, 2008.
15. Carl Walker, Inc. “City of Atascadero Parking Utilization and Management Study.” City of
Atascadero, California, 2006.
16. Rich and Associates. “City of LaCrosse Parking Study.” City of LaCrosse, Wisconsin, May 2009.
17. Desman Associates. “City of Meadville Parking Study.” City of Meadville, Pennsylvania,
December 2008.
18. Wilbur Smith Associates. “Menlo Park Downtown Parking Study.” Menlo Park, California,
August 2010.
19. Rick Williams Consulting. “Downtown Oregon City Parking Study.” Oregon City, Oregon,
April 2009.
20. Rick Williams Consulting. “Downtown Springfield Parking Study.” Springfield, Oregon,
March 2010.
21. Rick Williams Consulting. “Downtown Redmond Parking Study.” Redmond, Washington,
January 2008.
22. Walker Parking Consultants. “Parking Study, Downtown Valparaiso.” City of Valparaiso,
Indiana, January 2010.
23. Rich and Associates. “Village of Westmont Parking Study.” Village of Westmont, Illinois,
November 2008.
24. City of Bloomington. “GIS Parking Lot Spaces Layer Metadata.” (2001) [Online]. Available:
http://bloomington.in.gov/documents/viewDocument.php?document_id=804.
25. Waten, G., D. Musiega, and C. Ndegwa. “A GIS Based Parking Management and Dissemination
System.” International Journal of Science and Research, Vol. 2, No. 7 (July 2013).
26. Hofmann-Wellenhof, B. and H. Lichtenegger. Global Positioning System: Theory and Practice, 5th
ed. Springer, 2008.
68
27. Federal Aviation Administration. Navigation Programs-Wide Area Augmentation System
(WAAS). [Online]. Available: www.faa.gov/about/office_org/headquarters_offices/ato/service_
units/techops/navservices/gnss/waas/. [Accessed July 2013.]
28. National Satellite Test Bed (NSTB). Wide-Area Augmentation System Performance Analysis Report,
July 2006. FAA/William J. Hughes Technical Center, NSTB/WAAS T&E Team, Atlantic City
International Airport, NJ [Online]. Available: www.nstb.tc.faa.gov/REPORTS/waaspan17.pdf.
[Accessed July 2013.]
29. Bossler, J., R. McMaster, C. Rizos, and J. Campbell. Manual of Geospatial Science and Technology,
2nd ed. CRC Press, 2010.
Brian Maleck, E.I.T., received his B.S. in civil engineering from Rensselaer Polytechnic
Institute in 2011 and his M.S. in civil engineering from Clemson University in 2013.
He was an active member of ITE while at Clemson, and was the first Communications
Chair of the organization. He is currently pursuing a career in the parking industry.
Wayne A. Sarasua, Ph.D., P.E., is an associate professor in civil engineering at Clemson
University. He is a past president of the South Carolina Section of ITE and is currently
a co-advisor of the Clemson ITE Student Chapter. He has chaired, co-chaired, or
participated in numerous conferences and committees for the Southern District and
the Georgia and South Carolina Sections of ITE. Wayne was the 2012 recipient of the
Southern District ITE Excellence in Transportation Engineering Education Award. His specialties are
in planning and design of transportation systems, transportation asset management, and spatial
data analysis. He is a member of ITE.
Jennifer H. Ogle, Ph.D., P.E., is an associate professor in the Glenn Department of
Civil Engineering at Clemson University. She is currently a co-advisor of the Clemson
ITE Student Chapter and former recipient of the ITE Dan Fambro Paper Award. Her
research interests focus on transportation infrastructure management, highway design,
transportation safety, and pedestrian accessibility.
Kweku Brown, E.I.T., received his civil engineering M.Sc. from the University of
Connecticut. He is currently a doctoral candidate at Clemson University. He is a past
president of the Clemson ITE Student Chapter and a member of the South Carolina
Section. He was the recipient of a 2013 Dwight Eisenhower Graduate Fellowship. His
research focuses on transportation safety utilizing geographic and spatial analysis
methods. He is a member of ITE.
69
The Effect of Additional Lane Length on
Double-Lane Roundabout Operation
By Samuel Hammond, Christopher Hunter, Ph.D., and Kevin Chang, Ph.D., P.E.
The purpose of this paper is to provide insight as to how additional lane length on an
approach and/or departure affects roundabouts. Currently, there is no United States guideline on
how additional lane lengths affect roundabout operation, so most transportation professionals refer
to studies conducted overseas that do not necessarily translate directly to domestic roundabout
design and operation. As the number of modern roundabouts in the United States continues to
increase, the desire is to provide effective information to professionals on roundabout operation and
design for conditions suitable for their jurisdiction. Using delay as the measure of effectiveness, a
hypothetical four-leg, double-lane roundabout with additional lane length design at both entry and
exit was analyzed, and the additional lane lengths were varied at both the entry and exit. Similar length
variations were applied to an existing roundabout with known data after calibration and validation.
The findings from this study are intended to provide transportation professionals with the quantitative
means of improving existing roundabout operational performance and also help design future
roundabouts with appropriate additional lane lengths that yield better performance. While the design
of an additional lane differs from a flared entry, findings from this study can also be applied to flare
lengths if they are designed to operate in a similar fashion as additional lane entry.
Introduction
The modern roundabout has become an increasingly popular form of intersection control in the
United States due to its effectiveness in improving safety and reducing traffic congestion. Since the
first modern roundabout was built in Nevada in 1990, the number has increased significantly, and
as of December 2012, more than 2,000 have been constructed.1
71
As roundabouts have become increasingly popular in the United States, it is very important to establish
some means of improving their performance in the near future when vehicle demand nears or exceeds
capacity. At signalized intersections, U.S. transportation professionals regularly consider parameters
such as green time, cycle length, and number of lanes in order to improve traffic operation. However,
there has not been much research performed domestically that addresses how to vary different geometric
parameters to improve operations for a roundabout when analysis shows that a nearby development
will impact traffic operation. Hence, most transportation professionals refer to studies conducted
overseas that do not necessarily translate directly to domestic roundabout design and operation.
One of the design requirements that needs further exploration is the entry approach. The entry can be
designed to increase capacity either by adding a full lane upstream of the roundabout or by widening
the approach gradually (flaring) through the entry geometry.2 Most of the studies on roundabout entry
design have been looking at the widening effect of the width of the approach lane. However, little
attention has been given to the length of the approach and its effect on roundabout operation.
The National Cooperative Highway Research Program (NCHRP) report on roundabout design neither
provides recommended lengths nor gives information on how long the entry lane needs to be widened
along the approach. The Federal Highway Administration (FHWA) roundabout guideline, which was
superseded by the NCHRP report, suggests a minimum flare length of 80 feet in urban areas and 130
feet in rural areas.3 It is not clear whether the suggested flare length also applies to additional lane
design, and the maximum flare length is not specified.
In general, the increasing popularity of roundabouts in the United States underscores the need for
more research on roundabouts in the United States to address the issues that traffic engineers face
in practice. The means of improving signalized intersections to meet specified demands have been
well researched and documented, and methods for predicting their performance are well established.
However, roundabouts lack such research on performance improvement. This research examines the
effect of additional lane lengths on a double-lane roundabout operation using delay as the primary
measure of effectiveness. The study is intended to provide transportation professionals with a means
of improving existing roundabout operational performance and to aid the planning and design stages
so that future roundabouts can be built with appropriate lane lengths to yield better performance.
Literature Review
When compared to signalized intersections, the research available on improving operations at roundabouts
due to increased traffic flow is comparably lacking. Signalized intersections usually implement several
modifications to improve safety and performance over time due to new developments or increases in
traffic flow. Since roundabouts handle traffic flow similarly to signalized intersections, it is possible for
the volume-to-capacity (v/c) ratio to approach or exceed 1.00. Under such conditions, long queues form
and delay increases at roundabouts. Such conditions require modifications to improve performance.
Earlier research on roundabout operation was conducted by the United Kingdom–based Transport and
Road Research Laboratory (TRRL), where numerous experiments and observations were performed on
existing roundabouts. Kimber incorporated findings from the TRRL studies and identified six geometric
parameters as having a significant effect on capacity: entry width, approach half-width, effective flare
length, flare sharpness, inscribed circle diameter, and entry radius.4,5 Out of the six parameters, entry
width, approach width, and flare length were determined to be the most relevant with regard to capacity.
The approach width, typically 12 feet in the United States, is the width of the traveled way in advance
of any entry flare; the entry width is the width of the traveled way at the point of entry. FHWA identifies
the entry width as the “largest determinant of a roundabout’s capacity.”3 The entry can be designed to
increase capacity by either adding a full lane upstream of the roundabout or by widening the approach
72
gradually (flaring) through the entry geometry.2 NCHRP recommends an entry width of 24 to 30 feet
for two-lane entry and 36 to 45 feet for three-lane entry. It does not, however, specify how far back
the additional lane or flaring should begin. In Europe, where flaring design is more common than
an additional lane design, the U.K. Department of Transport Design Manual recommends flare lengths of
about 82 feet (25 meters) for widening to effectively increase capacity.6 Flare lengths greater than about
328 feet (100 meters) result in higher speeds, which undermines the main purpose of the modern
roundabout configuration. The configuration of a modern roundabout reduces driver approach speeds
to improve safety and enhance traffic flow. Therefore, when increasingly long lane lengths are used, the
safety benefit of roundabouts may be forfeited. The 82-foot recommendation by the U.K. Department
of Transport Design Manual has not been tested in the United States, but some state agencies follow the
overseas guidelines, since data on the additional lane or flare length have not been provided. Interim
requirements and guidance on roundabouts by the New York Department of Transportation suggest
a flare length of 41 feet (12.5 meters) to 328 feet (100 meters) for urban areas and 66 feet (20 meters) to
325 feet (100 meters) for rural areas.7
The FHWA used a model developed by Wu in determining the capacity of a roundabout, whereby short
length widening at the approach is considered.3,8 Wu estimated the capacity of an unsignalized crossroad
and T-junction intersection by taking into account the length of the turn lanes. Wu later analyzed this
model at a roundabout intersection and introduced an enhancement/correction factor for determining
the capacity of a double-lane entry at a roundabout.9 Wu was able to identify the effect of entry length,
but the effect of the additional lane length at the exit was not mentioned, and it was assumed that
the capacities of both lanes were identical and the traffic flow in both lanes at the entry was equally
distributed. However, studies conducted on some double-lane roundabouts in the United States show
that the right lane is utilized more frequently than the left lane and thus is usually considered to be the
critical lane. For instance, one of the double-lane roundabouts in Brattleboro, Vermont, showed that
the right lane had about 70 percent of the entry total flow, so capacity in the Wu model appears to have
been overestimated.10 This research examines the effect of the flare/additional lane length on roundabout
operation using typical U.S. driving behavior, where the right lane is considered the critical lane and is
utilized more frequently than the left lane.
In order to model typical U.S. driving behavior, VISSIM was used for analysis purposes. VISSIM is a
microsimulation software from Germany in which vehicles are modeled using parameters such as driver
behavior, vehicle speeds, and vehicle type.11 VISSIM has the ability to control gaps and headways on a
lane-by-lane basis to accurately replicate vehicle operations at roundabouts. Numerous studies have used
VISSIM microsimulations to examine roundabout performance due to their unique ability to mimic realworld traffic operations. Trueblood and Dale considered VISSIM to be a very effective microsimulation
software package for roundabout performance analysis and used VISSIM to model existing roundabouts
in the state of Missouri.12 Bared and Afshar used VISSIM to model roundabouts for various ranges of
circulating and entry traffic volumes.13 They found that simulation results from VISSIM matched field
data more closely than those from the SIDRA analytical and RODEL empirical models.
Methodology
This section details how the research effort was conducted with respect to modeling the impact of
additional lane length on roundabout operation. In the flare design, a single lane is gradually widened
into two lanes at the entry (see Figure 1). In the additional lane length design, a full lane is added at the
entry and a taper of sufficient length is provided. Both design cases result in the widening of the entry
and increases the rate that vehicles enter the roundabout at a given time. This means that in terms of
operation, a single traffic stream separates into two streams for both the additional lane and flare designs.
The additional lane design was used in this research to examine the effect on a roundabout; the findings
applied to flared entry as well.
73
A hypothetical double-lane roundabout with four legs was modeled in VISSIM with varying additional
lane lengths at the entry and exit. For comparison purposes, similar variations were then tested on
an existing double-lane roundabout with data from NCHRP 572.10 In order to properly lay out the
roundabout correctly in VISSIM, guidelines developed by Trueblood and Dale and Li, et al. were used
to re-create the reduced-speed areas at the conflict points.12,14 These reduced-speed areas were kept at a
length of 17 feet and placed 8 feet from the yield line on each lane of the approach. Reduced-speed areas
were also placed in the circulatory roadway at a length of 17 feet before the entry areas. Travel speeds
of 20 miles per hour were used in the reduced-speed zones, as recommended by Trueblood and Dale.12
Since VISSIM is a stochastic model whose results vary depending on the random seed number used, the
model was run multiple times and the average results were used. For this study, 17 simulation runs with
a cumulative running time of 1 hour were analyzed in VISSIM to achieve a 95 percent confidence interval.
Figure 1. Flaring and additional lane design.
Source: FHWA Roundabout Guide.
For the hypothetical model, VISSIM default values for headway were used. Data collection points
used to capture delay data were placed at locations specified in NCHRP 572 to compare results.10
The travel time section in VISSIM was established starting at 250 feet from the yield line on the
approach and ending at the exit where the vehicle left the circulatory roadway. The roundabout
74
used for comparison was set up in VISSIM with data collection points placed at similar locations
to those used in NCHRP 57210; the model was then calibrated using field data from the same study.
The calibration effort began with the VISSIM default values and was gradually adjusted until the
reduced speed, driving behavior, yield bar placement, headway, and minimum gaps of the measured
field travel time data closely matched the VISSIM data. The field travel time data were the same data
used in NCHRP 572 and were obtained from Kittelson and Associates.
Hypothetical Double-Lane Roundabout
The roundabout used in this study focused on the six important parameters given by TRRL.5 The
design was based on the guidelines in NCHRP 672.2 As shown in Figure 2, the roundabout had two
circulatory lanes and four legs with single lanes that diverged into two lanes at the entry and merged
into one at the exit. An inscribed circle of 180 feet was used for this study, and the four approaches
were aligned at 90 degrees. This AutoCAD-designed layout was subsequently uploaded into VISSIM.
Figure 2. Hypothetical roundabout design.
Figure 2. Hypothetical roundabout design.
For the purposes of this analysis, no specific volume was assigned on a lane basis. Vehicles were
allowed to freely choose lanes, but the links and driving behavior assumptions were configured
75
such that the right lane would be used more frequently (about 70 percent usage was observed from
the simulation). The roundabout model mirrored real-life driving behavior, as vehicles were free to
change lanes when prevailing conditions were not favorable. One-quarter each of the traffic made a
right or left turn, and the remaining one-half proceeded straight through the roundabout. A degree
of saturation less than 0.80 was targeted based on the following assumptions:
■■
The major road was established in the north–south direction with a volume of 800 vehicles per
hour in each direction;
■■
The minor road was established in the east–west direction with a volume of 350 vehicles per hour
in each direction;
■■
The right lane was assumed to be the critical lane in all directions; and
■■
Fifteen percent of the volume consisted of heavy vehicles.
The v/c ratio for the northbound and southbound critical lane was 0.78, while the eastbound and
westbound critical lane was 0.41 using the analytical method presented in the Highway Capacity
Manual (HCM).
Starting with an additional lane length of zero (single lane entry and exit), the operational
performance of the roundabout was analyzed in VISSIM for 17 simulation runs, and the delay data
were averaged. Table 1 shows the different scenarios used for the hypothetical and existing model
analysis:
■■
Scenario 1: Only the entry additional lane length was varied, while the exit additional lane length
was kept at zero (single exit).
■■
Scenario 2: Both entry and exit additional lane lengths were varied.
Table 1. Model scenarios.
Variation 2
Exit
Entry
Exit
Entry
Exit
X
X
X
X
X
X
X
X
X
X
Existing Model Scenario 1
Existing Model Scenario 2
X
X
Exit
Entry
Exit
North
Entry
South
Exit
Exit
West
Entry
X
East
Exit
X
North
Entry
Exit
Entry
South
X
Entry
X
Exit
X
West
Entry
Variation 1
Exit
Entry
East
North
Entry
Exit
Entry
South
X
Variation 3
76
West
X
Location
Variation 2
X
East
X
Variation 3
Additional lane
Exit
X
North
Exit
X
South
Entry
X
Exit
Variation 1
West
Entry
Location
Exit
East
Entry
Additional lane
Hypothetical Model Scenario 2
Entry
Hypothetical Model Scenario 1
X
X
X
X
X
X
X
X
X
X
X
X
Under scenario 1, three variations were considered:
1. Additional lane lengths at the entry of all four legs were varied at the same time. This scenario was
represented by HA in this study, where H represents the hypothetical model and A represents all legs.
2. An additional lane at the entry with the highest volume (south leg) was varied. This scenario was
represented by HS, where H represents the hypothetical model and S represents the south leg.
3. An additional lane at the entry with the lowest volume (west leg) was varied. This scenario was
represented by HW, where H represents the hypothetical model and W represents the west leg.
Under scenario 2, three variations were considered:
1. Additional lane lengths at the entry and exit of all four legs were varied at the same time. This
scenario was represented by HAX in this study, where H represents the hypothetical model, A
represents all legs, and X represents the exit.
2. An additional lane at the entry and exit with the highest volume (south leg) was varied at the
same time. This scenario was represented by HSX, where H represents the hypothetical model, S
represents the south leg, and X represents the exit.
3. Only one additional lane at the entry and exit with the lowest volume (west leg) was varied at the
same time. This scenario was represented by HWX, where H represents the hypothetical model, W
represents the west leg, and X represents the exit.
The additional lane lengths that were analyzed in VISSIM for both scenarios included 0 feet, 150
feet, 250 feet, 350 feet, 450 feet, and 550 feet. The VISSIM lane closure feature was utilized to make
the zero foot length possible. While reducing the exit and entry lanes on a double-lane roundabout
to a single lane is not practical, it was done in this study to illustrate the extent of the delay effect up
to zero feet.
Existing Double-Lane Roundabout
For analysis purposes, an existing roundabout was analyzed in a similar manner as the hypothetical
model. The roundabout chosen for this analysis was the Brattleboro roundabout in Vermont, since
it had a physical configuration comparable to the hypothetical model used in this study and was
one of the roundabouts included in the NCHRP 572 study.10 The data from the NCHRP 572 study
were used to calibrate and validate the hypothetical model in VISSIM. The Brattleboro roundabout
was a double-lane roundabout with four legs aligned at 90 degrees. Its inscribed circle diameter was
176 feet, and all legs had additional lane lengths greater than 100 feet. Figure 3, obtained from the
Vermont Transportation Agency, shows the different additional lane lengths on each approach. The
south, east, and north legs have exceptionally long taper lengths, and these lengths were included in
the model. The figure also shows new pavement markings where a three-lane alternative was being
considered for the northbound entry. This research study used the exiting configuration of a twolane entry, which represented the configuration when field data were collected for NCHRP 572.
77
Figure 3. Brattleboro roundabout design.
Source: Vermont Transportation Agency.
The field data collection determined that the volumes for the eastbound, westbound, southbound,
and northbound legs were 832 vehicles/hour, 441 vehicles/hour, 515 vehicles/hour, and 1,051
vehicles/hour, respectively. Using the HCM analysis, the v/c ratio for each critical lane (right lane)
was found to be 0.96, 0.58, 0.62, and 1.41, respectively. The field data used in NCHRP 572 did not
include delay records for southbound traffic, so travel time data were used to validate this VISSIM
model.10 Using a t-test, a two-tailed p-value of 0.764 was calculated, indicating no statistically
significant difference between the VISSIM and field travel time data. For calibration, the headway,
reduced-speed area, driving behavior, and link arrangement were adjusted until the VISSIM travel
time mirrored the field data. Figure 4 compares the field data with the final VISSIM trial that gave an
acceptable error. Individual movements are labeled showing the direction of travel; for example, W-S
indicates a movement entering from the west leg and exiting at the south leg.
78
Figure 4. Field and VISSIM travel time comparison.
After the model was validated, various lane lengths were analyzed following the same procedure
as described earlier for the hypothetical model (see Table 1). The additional lane length was varied
for the same two scenarios as for the hypothetical model, and only the additional lane lengths were
varied; all other parameters remained the same. For each scenario in the existing model, the letter E
was used to differentiate these scenarios from the hypothetical model, which used H. (As an example,
where additional lane lengths at the entry are varied at all four legs, this scenario was represented by
EA in this study, where E represents the existing model and A represents all legs.) For variation 3 of
the existing model, it should be noted that the volume from the north leg was used, as it represented
the leg with the lowest entering volume.
Since the existing model had varying additional lane lengths of 150 to 180 feet, the following lengths
were analyzed for both of the existing model scenarios: 0 feet, 50 feet, 100 feet, and the actual existing
length (see Figure 3). In addition, lengths of 100 feet, 200 feet, 300 feet, and 400 feet were added to
the existing additional lane lengths and analyzed in VISSIM to study the effect of longer lengths on
roundabout operation.
Results And Discussion
The delay and speed data for the hypothetical model are shown in Figure 5. The delay data represent
the difference between the measured travel time and free-flow travel time from a location of 250 feet
approaching the yield line on the entry leg to the exit point on the circulatory roadway. Figure 5 also
shows the average speed between these two locations. Data from the hypothetical model show that
the highest delay occurred when the model had a single lane (zero additional lane length) for each
scenario. There was no significant difference between scenarios 1 and 2, though the delay data were
slightly higher for scenario 2 (when the additional lane length at the entry and exit were varied at the
same time). Increasing the length up to approximately 150 feet was effective in reducing delay, but
beyond that point, there was no significant decrease. In general, an increase in lane length resulted in
an increase in vehicle speed, and the most effective length was between 50 feet and 150 feet.
79
The analysis of the different variations showed that increasing the length on all four legs at
the same time was more effective than just increasing the length on one leg. As the speed data
show, increasing the lengths caused the speed to increase at the entries; this decreased the
time required for vehicles to reach the circulatory roadway. When additional vehicles reach the
circulatory roadway within a short period of time, the conflicting flow increases and reduces the
likelihood of finding an acceptable gap. It is for this reason that the delay increases even though
approach speeds are increasing. Increasing the length on just one leg reduced the delay for that
entry but resulted in more vehicles in the circulatory roadway and increased the conflicting
flow for other entries. Increasing the length on the entry with the lowest volume (minor road)
increased the conflicting flow and caused delay on the major road. The delay on the minor road,
which had minimum effect on the intersection, was decreased, but the delay on the major road
increased, resulting in a slightly increased delay at the intersection overall. Increasing the length
on the entry with the highest volume was more effective than increasing the length on the entry
with the lowest volume, since the delay on the major road, which significantly contributes to
the delay of the entire intersection, was reduced. Increasing the length of just one entry (either
highest or lowest volume) was not as effective as increasing all four legs at the same time, as
increasing the length on all four legs reduced the delay on each approach, and thus reduced the
overall delay of the intersection.
Wu suggested balancing the exit and entry capacities so that the potential of widened entry
could be achieved and bottleneck effects at the exit could be avoided.9 Based on this analysis,
the double-lane exit did not affect delay at the intersection. The difference was more noticeable
within short intervals between zero and 150 feet; beyond 150 feet, increasing the exit length did
not result in any significant change in the delay. This could be due to the fact that low volumes
(or v/c ratios) were considered. It is also possible that the conflict at the exit was minimal because
the roundabout configuration was carefully laid out per NCHRP guidelines.2
The same variations were applied to the existing roundabout in Brattleboro, Vermont.
Observations during site visits (spring 2013) to this roundabout determined that some
adjustments to improve its operation during peak hours were needed. During off-peak hours, the
roundabout operated exceptionally well on all approaches. During peak hours, the northbound
approach exhibited long queues with delays up to about 23 seconds from approximately 250
feet upstream of the yield line. The high traffic in this direction was due to the increased
development of restaurants, offices, and other businesses south of this roundabout. Under
free-flow conditions, the travel time from approximately 250 feet upstream to the yield line
was measured to be about 7 seconds, but during peak hours this short interval took about
30 seconds of travel time. During the peak hour, the east, west, and north legs that operated
exceptionally well during off-peak hours also experienced an increase in delay.
In order to evaluate the operations at this roundabout, the length variation applied to the
hypothetical model was also applied to the Brattleboro roundabout model in VISSIM after
calibration and validation. The results in Figure 6 conform to the findings from the hypothetical
model. On the east, west, north, and south legs of this roundabout, about 180, 160, 150, and
180 feet of respective lane length existed at both entry and exit (Figure 3). For the analysis the
additional lane lengths were decreased so that all lengths were either zero (single lane), 50, or
100 feet using the above-stated scenarios. Shorter lengths within 100 feet on all legs resulted in
the most significant decrease in delay. Increasing the existing length by 100-foot increments at
all legs simultaneously resulted in less change in delay. Zero-foot lengths resulted in the highest
delay, and delay decreased as increasing lengths approached the existing lengths. As noticed
in the hypothetical model, adjusting just one leg was not as effective as adjusting all legs at
the same time. Adjusting only the leg with the lowest volume was the least effective means of
improving delay. There was no significant difference in varying the length of the exit lane; the
80
difference was more noticeable when the length was between zero and 150 feet, but beyond 150
feet, increasing the exit length did not result in any significant change in delay.
Figure 5. Delay and speed data for hypothetical model.
81
Figure 6. Delay and speed data for existing model.
Conclusion And Recommendations
The findings from this study are based on double-lane roundabouts with varying approach
geometries and additional lane length configurations. The delay values reported in this study were
measured from a distance of 250 feet from the yield line on the approach to the point where the
vehicle exited the circulatory roadway. Delays upstream of the 250 foot mark and beyond the exit
82
line were not recorded, though delays beyond these limits could add to the magnitude of the data
reported in this study. Understanding delay variability within this short interval under the assumed
conditions furthers the body of knowledge with regard to roundabout operations that was initially
presented in NCHRP 572.10
The analyses of the hypothetical and existing roundabout models indicate that very long additional
lane lengths were not effective in reducing delay at roundabouts. Shorter lengths of up to 150 feet
were determined to be most effective. This finding corroborates the results from the U.K. Department
of Transport Design Manual for Road and Bridges, which recommended shorter flare lengths of about
82 feet to effectively increase capacity and pointed out that longer flare lengths resulted in higher
speeds.6 The findings from this study can also be applied to flare designs. Where flaring is used,
additional analysis is needed if the flaring does not result in two entry lanes. At entries where two full
lanes are used, longer lengths will result in increased speed and reduced delay.
From an operations standpoint, shorter additional lane lengths between 50 and 150 feet at both the
entry and exit were most effective. While adjusting the lane length of all legs was determined to be
more beneficial than only adjusting one leg, at a location where only one leg can be modified, the
leg with the most volume should be adjusted and length variation should be within the 50- to 150foot range. If lengths of 150 feet already exist, other modification techniques need to be applied, as
longer lengths will be ineffective in reducing delay. Increasing the lane length allowed vehicles to
reach the circulatory roadway faster, but with more vehicles entering the roundabout, the likelihood
of conflicting flow increased as well. NCHRP identifies design procedures that balance entry,
circulatory, and exit flow through lane numbers and arrangements.2 Shorter lengths help regulate
the rate of entry at a slow but constant rate, but longer lengths can result in an instantaneous
increase in circulatory roadway flow with less capacity to handle the flow.
The findings from this study will help transportation professionals with regard to roundabout
design and operations. This study confirms that additional lane length can be varied in a manner
that effectively reduces delay while avoiding unnecessary lane design and construction; this study
can also be used during the planning and design stages of a new roundabout in order to determine
the appropriate additional lane length. Additional analysis is needed to determine the effect of
different lengths on safety, since this study has shown that increasing the lane length can increase
the approach speed at a roundabout, and this trade-off could undermine the operational benefits of
a modern roundabout facility.
Works Cited
1.
Kittelson & Associates. Modern Roundabouts Website, Inventory Activities [Online]. Available:
http://roundabouts.kittelson.com/. [Accessed December 2012.]
2.
National Cooperative Highway Research Program. NCHRP Report 672: Roundabouts: An
Informational Guide, 2nd ed. Washington, DC: Transportation Research Board, 2010.
3.
Federal Highway Administration. Roundabouts: An Informational Guide. FHWA-RD-00-06.
Washington, DC: U.S. Department of Transportation, Federal Highway Administration, 2000.
4.
Kimber, R.M. The Traffic Capacity of Roundabouts. TRRL Laboratory Report LR 942. Crowthorne,
England: Transport and Road Research Laboratory, 1980.
5.
U.K. Department of Transport. Design Manual for Roads and Bridges, Vol. 6, Section 2, Part 3. U.K.
Department of Transport, 2007.
83
6.
New York Department of Transportation. Roundabout: Interim Requirements and Guidance.
Albany, NY: New York Department of Transportation, 2000.
7.
Wu, N. “Capacity of Shared/Short Lanes at Unsignalized Intersections.” In Proceedings of the
Third International Symposium on Intersections without Traffic Signals, M. Kyte, ed. Portland, OR,
USA.: University of Idaho, 1997.
8.
Wu, N. “Capacity Enhancement and Limitation at Roundabouts with Double-Lane or Flare
Entries.” Proceedings of the 5th International Symposium on Highway Capacity and Quality of Service:
Technical Papers, Vol. 2. Yokohama, Japan: Japan Society of Traffic Engineers, 2006.
9.
National Cooperative Highway Research Program. NCHRP Report 572: Roundabouts in the United
States. Washington, DC: National Research Council, Transportation Research Board, 2007.
10. PTV. VISSIM User’s Manual 5.30. Karlsruhe, Germany: Planung Transport Verkehr AG, 2010.
11. Trueblood, M. and J. Dale. “Simulating Roundabouts with VISSIM.” 2nd Urban Street Symposium.
Anaheim, California: 2003.
12. Bared, J.G. and A.M. Afshar. Planning Capacity Models By Lane for 2- and 3-lane Roundabouts Using
Simulation. Washington, DC: Transportation Research Board, National Research Council, 2009.
13. Li, Z., M. DeAmico, M. Chitturi, A. Bill, and D. Noyce. Calibration of VISSIM Roundabout Model: A
Critical Gap and Follow-up Headway. Washington, DC: Transportation Research Board, National
Research Council, 2013.
14. Transportation Research Board. Highway Capacity Manual. Washington, DC: Transportation
Research Board, National Research Council, 2010.
Samuel Hammond is a graduate research assistant at the University of Rhode Island. His
research interests include roundabout operation, sustainable transportation planning,
traffic safety, traffic flow modeling, and simulation. Samuel has been the recipient of
the Tom Joyner Scholarship, Academic Achievement Award (two consecutive years), and
Dean’s Scholarship.
Christopher Hunter, Ph.D., is an associate professor in the Department of Civil &
Environmental Engineering at the University of Rhode Island, where he primarily teaches
courses in transportation and conducts research on traffic system operations and
traffic safety. He is a member of the Institute of Transportation Engineers, American
Society of Civil Engineers and the National Society of Black Engineers. He has been the
recipient of the Diversity Award for Faculty Excellence in Leadership and Service and the Edmund
and Dorothy Marshall Faculty Excellence Award for Outstanding Service and Excellent Teaching in
Civil Engineering.
Kevin Chang, Ph.D., P.E., is an assistant professor in the Department of Civil
Engineering and Center for Secure and Dependable Systems at the University of
Idaho. He is a graduate of the University of Washington and is registered as a
Professional Engineer in Washington and California. Kevin is the current chair of
the ITE Transportation Education Council and is a past president of the Washington
state section of ITE. He is a member of ITE.
84
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