Impacts of Connected Vehicles and Automated Vehicles on State and Local Transportation Agencies--Task-Order Support. Road Markings for Machine Vision

The objective of the research was to develop information on the performance characteristics of pavement markings that affect the ability of machine vision systems to recognize them. This information is expected to be useful to the AASHTO/SAE Working Group as they develop guidelines and criteria. Markings to be studied are center lines [Manual on Uniform Traffic Control Devices (MUTCD) Section 3B.01], no-passing zone markings [MUTCD 3B.02], lane lines [MUTCD 3B.04, including dotted extensions for ramps], and edge lines [MUTCD 3B.06]. Factors to be considered include pavement marking presence, type of marking (flush, raised [MUTCD 3B.11, 3B.12, 3B.13, 3B.14], recessed, or temporary [MUTCD 6F.77, 6F.78, 6F.79]), contrast between the pavement and the marking during daytime conditions (including contrast markings, different angles of the sun, and the effects of shadows), retroreflectivity of the marking during nighttime conditions (including the effect of illumination) and different weather conditions (rain, fog, etc.), pavement uniformity (including sealed cracks and patching), vehicle speed, and the impact of other substances on the road such as snow, sand, salt, and water. It is intended that the work include a range of forward-facing machine vision systems so that the current technologies and those on the horizon can be accommodated. The Contractor's Final Report is available and is being used by the joint AASHTO SAE Working Group. TASKS: Task 1. Conduct a kick-off meeting with the panel on June 1, 2016 at SAE headquarters in Troy, Michigan. Task 2. Review policies and specifications that relate to the performance of pavement markings relative to machine vision systems. Task 3. Identify the specific testing conditions that will be used in Task 4. Task 4. Conduct testing to generate the data needed to meet the project objective. Task 5. Process the data from the Task 4 field study and conduct the analyses to establish the results needed to identify performance characteristics of pavement markings that affect the ability of machine vision systems to recognize them. Task 6. Prepare the final documents, which will include: (1) Performance data on the machine vision recognition of different marking approaches for lane departure warning (LDW) and line keeping applications (LKA) that clearly lays out the assumptions and limitations of the research approach and the level of confidence in the results; (2) Prioritized list of marking characteristics that are important to the LDW and LKA performance of machine vision systems; (3) Insofar as practical, recommendations for good pavement marking practices that do not degrade the performance of the markings for human vision; (4) Estimation of the costs and safety impacts that could be expected through implementation of the various pavement marking recommendations; (5) If appropriate, recommended changes to the MUTCD; and (6) Gaps in research that still need to be addressed. Task 7. Finalize the deliverables of the project based on the panel review.

Record URL:

Language

English

Project

Status: Completed
Funding: $200000
Contract Numbers:
Project 20-102(06)
Sponsor Organizations:
Federal Highway Administration

1200 New Jersey Avenue, SE
Washington, DC United States 20590

National Cooperative Highway Research Program

Transportation Research Board
500 Fifth Street, NW
Washington, DC United States 20001

American Association of State Highway and Transportation Officials (AASHTO)

444 North Capitol Street, NW
Washington, DC United States 20001
Project Managers:
Derr, B
Performing Organizations:
Texas A&M Transportation Institute, College Station

Texas A&M University System
3135 TAMU
College Station, TX United States 77843-3135
Principal Investigators:
Pike, Adam
Start Date: 20160713
Expected Completion Date: 20180812
Actual Completion Date: 0
Source Data: RiP Project 40143

Subject/Index Terms

TRT Terms: Connected vehicles; Contrast; Glare; Highway safety; Intelligent vehicles; Machine vision; Periods of the day; Retroreflectivity; Road markings
Identifier Terms: American Association of State Highway and Transportation Officials; Society of Automotive Engineers
Subject Areas: Highways; Operations and Traffic Management; Safety and Human Factors; Vehicles and Equipment;

Filing Info

Accession Number: 01571785
Record Type: Research project
Source Agency: Transportation Research Board
Contract Numbers: Project 20-102(06)
Files: TRB, RiP
Created Date: Jul 30 2015 1:00AM