High Performance Pavement Markings Enhancing Camera and LIDAR Detection Rik Nuyttens Sr Regulatory Affairs Manager EMEA Transportation Safety Division
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Introduction ➢ Future vehicles will also rely on machine vision to assist the driver and help to move into higher levels of automation. ➢ Lane Keeping (LKS) and Lane Departure Warning (LDWS) Systems depend on the detection of the road design ( #lanes ) ➢ International studies point to the crucial relationship between these ADAS and road marking visibility and quality ▪
Austroads / iRAP study : ▪
Better quality and maintained longitudinal lines needed
▪
Socio-economic benefits >3:1 (crash reduction vs road marking cost)
▪
Various studies (TTI US, Swarco EU, ….) ▪
Visibility and detection depend on good contrast and brightness of the marking
▪
Rainy conditions dramatically reduce the reliability of LKS (up to 80%)
➢ Road marking performance and Camera/LiDAR detection.
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3rd Mobility Package EU to improve Road Safety Annual road fatalities
Reality
Target
LKA and LDWS rely on good visible markings! https://ec.europa.eu/transport/modes/road/news/2018-05-17-europe-on-the-move-3_en
LKA Study TRL UK : “An fully optimized LKA system could avoid 3500 fatalities and 21000 serious injured/yr”
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Socio-economic benefits : 10.500 lives – 60.000 Injured 4
Visibility of Pavement Markings at Night Dry
Wet
30 m
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60 m
90 m
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Standard Measurement Geometry EN 1436
Test Methods in EN 1436 ‚wet-reflectivity‘ Class RW
Bucket Method ‚after the rain‘
‚rain-reflectivity‘ Class RR
Study Vedecom – 3M
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Datacollection
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Vedecom Study (2021) : Road Markings for ADAS
X4 Weather Condition / Use Case ✓ ✓ ✓ ✓ ✓
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Day Night Dusk Mild Rain Heavy Rain
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Performance according EN1436
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Vedecom Study : Data Collection
12 km/h
12 km/h
Data fusion -
Visual Images (1920*700) RGB values (luminance) at 15m Vehicle CAN bus data LiDAR data & GPS data to optimize marking detection (not possible with commercial LKA !)
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IMU + GPS-RTK + Speed Off line processing
Weather 11
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Off-line Data Processing
<-
15m
->
ADAS
Weber Contrast BDD
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Human Detection (1) : Day
- Main characteristic Qd (whiteness) - Contrast determined by road surface
- Mirror effect by sun - Black masking may become visible (negative contrast filtered out)
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Human Detection (2) : Night
Disturbance by reflections of nearby road furniture (Workzones during rain) Non-reflective matte contrast markings provide solution
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Detection Rate per Marking Material Leading to confidence for ADAS function ▪ Daytime correlates with Qd ▪ Night-time correlates with Retroreflection ▪ ‚Challenging‘ Nighttime (wet and rain) clearly differentiates pavement markings
Results : Weber Contrast values
Distance = 15m → Wc = ƒ (Qd,RL)
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Pavement Markings: detection by LiDAR (Dry) Testdeck at University Dresden: (White lines) •
High RL according EN1436 translates to high signal response by LiDAR and look ahead distance
•
Day and Night performance both relate to retro-reflective performance as LiDAR emits its own N-IR laser beams.
•
Daytime luminance Qd/CapY does not impact LiDAR detection.
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Wet Reflectivity and LiDAR (1) Structured Road marking tape with 1,9 and 2,4 R.I. beads :
• •
LiDAR detection of the tape possible for all situations. Similar to “RW” and “RR” performance according EN1436
Test set up: • N-IR scans(lines) covering range of 6 to 10m distance. (Detection angles around 7°) • Velodyne Puck 16 & 64 lines (905 nm N-IR laser light)
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Dry
Humid (RW)
Immerged (RR)
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Wet Reflectivity and LiDAR (2) Pavement markings with good “RR” properties : (Raintest according EN1436) • •
Provide good detection by LiDAR during rain or when fully immersed in water. Performance similar to visible light where beads with R.I. 2,4 provide the “RR” properties and beads with R.I. 1,5 till 1,9 only create the correct light return when dry.
Test conditions : • All samples fully immerged in water • Detection angle : 24° - Distance : 3m • LiDAR Velodyne Puck 16 lines – 905nm laser
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Conclusions Detection by Video camera :
Detection by LiDAR:
▪ Contrast based : line vs road surface
▪ Reflection of N-IR laser light
▪ Better detection :
▪ Better detection :
▪ High Qd = Needed for day time ▪ High RL (dry, wet and rain) = Needed for night time
▪ High RL (dry, wet and rain) = Needed for day and night time
▪ Dark road surface (asphalt vs concrete)
▪ No impact by Qd (marking)
▪ Black masking tape remained mostly undetected (exceptions glare by sun or rainy night) ▪ Special beads RI = 2,4 provide strong benefit for rainy night contrast (RW and especially RR performance)
CEN TC226 WG2/WG12 : ▪ Adjust EN1436 to mention importance of “contrast” for current LKA systems (video camera) ▪ Develop a more practical “RR”-test method.
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