Slides - AstaZero

RADAR REFLECTORS AND CLOUD DATA
– AN ENABLER OF ROBUST VEHICLE
AUTOMATION?
Alexey Voronov, Johan Wedlin, Cristofer Englund, Viktoria Swedish ICT
Johan Hultén, Sentient+, [email protected]
Follow us @ViktoriaSweICT
INTRODUCTION
• 
Vehicle positioning is important for traffic safety, maintenance and
autonomous driving
• 
Painted lane markings are not enough: they wear off, and are not visible in
snow and heavy rain
• 
GPS signal is not sufficient due to limited coverage, accuracy and
scrambling
• 
Landmarks-based positioning requires expensive 3D-scanned maps
• 
Autonomous driving requires high level of redundancy in order to not depend
on the driver as a backup
• 
Sentient+ initiated a pre-study Vehicle Positioning with Radar Reflectors.
The pre-study was financed by Swedish Department of Transportation
(Trafikverket) and performed in collaboration with Viktoria Swedish ICT
FUNCTIONS AND REQUIREMENTS
Function
Safety requirement
Comfort requirment
Lateral control:
lane-keeping
Keep within the lane markings.
No driver as a backup à stricter
requirements than for LKA (failoperational, backup)
Enough information for smooth
control (e.g. soften the curves)
Longitudinal control:
speed adjustment
Keep within the speed limits, do
not miss exits and position
properly on intersections
Enough information for smooth
control (e.g. slow down before a
curve)
Safe Stop
Find an appropriate spot without
GPS or camera
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TECHNOLOGY TODAY
Markings
Sensors
Pros
Cons
Painted lane markings
Camera
Cheap and simple
Paint wear; Camera can't handle
snow, rain, fog, glare, backlight
Snow pins (snökäppar)
Camera
Available, cheap, work in
snow
Flyttas lätt, inte lämplig på flerfilig
väg, kameraproblematik
Traffic sign
Camera (and partially radar)
Available, rich information,
useful for drivers
Few variants, require text
recognition, camera problems
QR-code (e.g. on poles) –
machine-readable sign
Camera
Much information on a
small area
Human driver can't interpret QR.
Camera problems.
Cat's eye in the asfalt and in Camera
the guardrail
Cheap, visible in the
darkness
Poorly visible in the daylight.
Cambera problems.
Guardrail
Added passive safety
Not applicable for muliti-lane road
Cheap?
Not applicable for muliti-lane road
Camera and radar
Delineator poles (kantstolpar Camera and radar
50 m)
Landmarks (curb, tree,
house/corner)
LIDAR, stereocamera, camera Lots of objects
+ Structure-From-Motion
Change often, complex algorithms
Laser reflector (e.g. SICK) –
a special landmark
LIDAR
Accurate
Expensive
Accurate positioning+
detailed 3D map
GPS (RTK Lantmäteriet) +
Sensor fusion + map
Lateral and longitudinal
position
Outdated maps,
dependency on GPS/GLONAS/...
Metal wire in asfalt
EM sensor
Simple
Not flexible, new equipment
Magnets
Hall-effect sensor
Snow plowable, do not
distract the driver
New equipmnet. EM noise
(bridges, trams, etc)
RFID
RF
Rich information, exist
passive och active
New equipment. Uncertain life
span and weather resistance
Radar reflectors
Radar
Existing equipment
Low accuracy? Need for new
algorithms.
A POSSIBLE SOLUTION
Pavement device/apparatus
•  Cat's eye with radar reflector
•  About 20 meters apart
•  Identifier for longitudinal positioning
•  A LED-light for manually-driven vehicles?
•  A magnet too?
Absolute positioning using cloud data
•  Computed from approximate (GPS) vehicle position and reflector data from the cloud
(positions, identification)
WHAT IS A RADAR REFLECTOR
Corner reflector
Reflectors can be oriented
differently
Aluminium can bottom
Guard rail poles
Several snow-plowable pavement markers from USA and Canada
REFLECTORS AND CAT'S EYES
DISTANCE BETWEEN REFLECTORS
• 
• 
Goal: stay about ±50 cm from centerline
Assume known reflector positions (±10 cm)
•  Measure with RTK GPS at installation, store in a
database (road authority or contractor)
• 
Lane: US: 2.7-4.6 m, Autobahn: 3.75 m
Assume good radar distance accuracy (±10 cm)
•  10 cm is radar accuracy at ca 10 meter
•  short range wide angle / side radar
• 
Driving only on the odometer and IMU (gyro
+accelerometer+compass), how far can we drive in the
wind and on the rough road before we lose the remaining
30 cm sideways?
•  Course deviation is about 1 cm/m --> max
distance 25 meter
60°
•  Shorter distance at the curves?
•  Varying distance for longitudinal coding/identification?
±20 cm
±50 cm
3m
Radar distance to the lane edge:
IDENTIFICATION FOR LONGITUDINAL POSITIONING
Safe Stop: find a parking or a roadside/shoulder (maybe known from the map)
•  We know roughly where we are, in the worst case up to 1km accuracy?
•  All we need is a unique reflector IDs (or their sequence) in this area
• 
• 
• 
1 km and 20 m distance -> 50 reflectors/km
50 unique ID within 1 km requires 6 bits (26 = 64)
ID can be spread out into a sequence of reflectors
1.  Different Radar Cross Section
2.  Polarization
3.  Distance-pattern
•  18-20-22 meter, mixed into "unique" sequence (------|----|-----|------|----|-----|-----)
•  Coding theory for the best sequence (012-012-012-012 or 120-201-020-221?)
•  Can distract drivers if distance variations are noticeable
4.  Camera-readable sign (e.g. QR-code or several cat's eyes per reflector)
•  Camera: 30° angle-of-view, 10 meters distance, 2000 pixels wide
•  10m * tan 30° / 2000pix = 2.8 mm/pix
4
5.  Several reflectors in a row
•  Radar resolution is a big limitation
3
ROADWORKS?
• 
Put a rubber mat with multiple
reflectors across the road in good
time for the roadworks ahead
• 
The mat marks the termination of
autonomous driving. Either the
driver takes over or Safe Stop is
performed (area for this should be
created)
SNOW?
Plowed snow
Road
Cat's eye
Snökäppar
Kantstolpar
POTENTIAL BENEFITS
• 
• 
• 
• 
• 
• 
• 
Important step towards allowing autonomous driving
Redundancy for safety functions in autonomous driving
Enhanced lane keeping
Reduced lane departure accidents
Allows narrower lane width
Reduced guard rail repairs
Reduced dependency on GPS / GLONAS (Civil Defense)
NEXT STEPS ?
•  So far research indicates that this is a promising direction. More
investigations are needed before we can say that this could work.
• 
Evaluate with actual radars
•  Accuracy of distance measurement; angular resolution
•  Size of the reflector, Radar Cross Section
•  Possibility of polarization
•  Water-repellent and snowplowable design; combination with cat's
eye/magnet/LED
•  Verify the minimum required distance between the reflectors
•  Longitudinal coding
•  Alt 1: Cat's eye every 5 meters, radar-reflector every other-third-forth
•  Alt 2: driver acceptance of varied distance (18-20-22 meter)
•  Best code ("the most unique" sequence, error correcting code/checksum)
•  Demonstrate prototype at AstaZero