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Road Markings for Machine Vision NCHRP Project 20-102(6) Update to AASHTO SCOTE June 2016

Road Markings for Machine Vision NCHRP Project 20 …sp.scote.transportation.org/Documents/2016 SCOTE Meeting/Tuesday... · NCHRP Project 20-102 • Impacts of Connected Vehicles

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Page 1: Road Markings for Machine Vision NCHRP Project 20 …sp.scote.transportation.org/Documents/2016 SCOTE Meeting/Tuesday... · NCHRP Project 20-102 • Impacts of Connected Vehicles

Road Markings for Machine VisionNCHRP Project 20-102(6)

Update to AASHTO SCOTE

June 2016

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NCHRP Project 20-102

• Impacts of Connected Vehicles and Automated Vehicles on State and Local Transportation Agencies– 20-102(01) Policy and Planning Actions to Internalize Societal Impacts

of CV and AV Systems into Market Decisions – 20-102(02) Impacts of Regulations and Policies on CV and AV

Technology Introduction in Transit Operations– 20-102(03) Challenges to CV and AV Application in Truck Freight

Operations– 20-102(05) Strategic Communications Plan for NCHRP Project 20-102– 20-102(06) Road Markings for Machine Vision– 20-102(07) Implications of Automation for Motor Vehicle Codes– 20-102(08) Dedicating Lanes for Priority or Exclusive Use by CVs and

AVs– 20-102(09) Providing Support to the Introduction of CV/AV Impacts

into Regional Transportation Planning and Modeling Tools

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Cameras to Detect Markings

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Adaptive Headlights

• Potential

Benefit

• Demonstrated

Benefit

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Lane Departure Warning

• Potential

Benefit

• Demonstrated

Benefit

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Highway Safety Statistics

• Roadway departure crashes account for over half of all fatal crashes (51%)

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Potential LDW Safety

• Decrease fatalities by 7,529 fatal per year in the US– Journal of Accident Analysis & Prevention, Vol 43, 2011

• Reduce roadway departure crashes 26.1%– NHTSA

• Reduce serious injuries 20.7%– NHTSA

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LDW Experiences

• Not effective as other vehicle safety technologies (IIHS 2014)

• “we don’t see any evidence that these systems are helping drivers avoid being in crashes” (IIHS 2014)

• 2/3 of Honda owners turn off their LDW feature (IIHS 2016)

– Annoying warnings

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Early TTI Studies

• Simulated Conditions

– Sun glare

– Wet conditions

• Flat v. structured markings

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Machine Vision

video

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Challenging Conditions

• Uniform road marking maintenance thresholds• Preventive pavement maintenance treatments• Horizontal curves• Roadway lighting• Nighttime conditions• Wet conditions• Snow conditions• Debris• Poor marking removal

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Historic Coordination

HighwayInfrastructure

Industry

Vehicle Industry

Standards Standards

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Needed Coordination

Standards

HighwayInfrastructure

Industry(FHWA, AASHTO)

Vehicle Industry(NHTSA,

SAE)

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NCHRP 20-102(6)

• Road Markings for Machine Vision

• Objectives

– develop information on the performance characteristics of pavement markings that affect the ability of machine vision systems to recognize them

– provide data and recommendations that the AASHTO/SAE Working Group can use to quickly develop guidelines and criteria

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Work Plan

• Kick-Off Meeting

• Review Policies & Machine Vision Technologies

• Identify Testing Conditions

• Conduct Closed-Course Testing

• Analyze Results

• Prepare Reports

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Current Testing Requirements

• ISO 17361:2007 – No requirements on types of road markings – Lane markings must be in good condition and in accordance

with the nationally defined visible lane markings std– No requirements on the environmental conditions – Visibility range must be greater than 1 km

• NHTSA– High contrast and uniform pavement– Lane marking specifications adhering to MUTCD– Avoiding tests in inclement weather including rain, fog, snow,

hail, smoke, or ash

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Field Data

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Texas A&M RELLIS Campus

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Markings (Level 1)

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Markings (Level 2)

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Markings (Level 3)

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Markings (Level 4)

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Markings (Level 5)

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Test Markings

• Possible Markings

– Continuous white

– Continuous yellow

– Skip white

– Skip yellow

– Contrast markings

– Raised retroreflective pavement markers

– Raised non-retroreflective pavement markers

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Test Conditions

• Daytime

– Weather (dry, wet)

• Nighttime

– Conditions (dry, wet)

– Continuous roadway lighting (on or off)

– Vehicle lighting (tungsten-halogen, LED, other)

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Next Steps

• Identify and obtain vehicle industry data

• Synthesize all data sources

• Develop up to 5 marking levels

– Color and retroreflectivity

• Provide 3M and Ennis-Flint specifications

• Install markings at RELLIS

• Conduct testing

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Sensor-Enhanced Markings

• Pilot testing of enhanced detection technologies

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Making It Happen