Study Based on Industry Stakeholder Interviews Recommends Tightening Uniformity of Traffic Control Devices to Meet the Needs of Automated Vehicles.
Key Stakeholders and Industry Experts Provide their Feedback Pertaining to AV Impacts, Constraints, and Recommended Changes on Roadway Infrastructure.
Made Public Date
07/27/2021
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Identifier
2021-L01042

Impacts of Automated Vehicles on Highway Infrastructure

Background

This study presents the lessons learned from a comprehensive literature review, engagement with highway infrastructure owners and operators (IOOs) and summary of interviews with industry experts and key stakeholders to document the potential impact of automated vehicles (AVs) on highway infrastructure. The study identifies the state of the practice among IOOs, gaps in knowledge, agency-preparedness levels for AVs as well as several aspects of roadway infrastructure including the quality and uniformity of traffic control devices and the potential impact on the infrastructure and street design. For this research, studies on the impact of Automated Driving Systems (ADS) were used to understand how the infrastructure may support the deployment of AVs. National stakeholder engagement workshops were held in conjunction with the American Association of State Highway and Transportation officials (AASHTO) Committee on Maintenance Workshop in Grand Rapids, MI, on July 17, 2019, and the Transportation Research Board (TRB) Automated Vehicle Symposium in Orlando, FL, on July 18, 2019.

Lessons Learned

This project identified the following research needs and suggestions from stakeholder interviews concerning uncertainties regarding AV deployment and the potential mix with human-driven vehicles.

  1. Tighten Traffic Control Devices (TCD) uniformity for AVs and develop Manual on Uniform Traffic Control Devices (MUTCD) material to support AV deployment. There’s a need to evaluate how standards such as MUTCD might evolve to meet the development needs of AVs and to allow for more rapid updates to the MUTCD than the current method allows. Tightening uniformity in these areas will help provide more robust marking detection and fewer false positives and will represent an initial step in preparing roadways for AV technologies.
  2. Attain machine-vision standards for TCDs regarding size, color, daytime appearance, and nighttime appearance to help support sensor recognition for current Advanced Driver Assistance Systems (ADAS) and future Automated Driving Systems (ADS).
  3. Update and maintain pavement markings for today’s ADAS as well as for the future. It is important to quantify the return-on-investment of making national changes (in design and/or maintenance) to any physical infrastructure element but particularly pavement markings.
  4. Apply a safe-systems approach to AV deployment for roadway safety since there will be a mixed fleet of human-driven vehicles, including those with ADAS and ADSs using the roadways for decades.
  5. Establish AV test scenarios with representative infrastructure conditions. Current testing is conducted under ideal conditions with uniform and dry pavement and clear and dry weather conditions, while in reality, testing conditions for AV technologies should be representative of the existing roadway network that those AV technologies are expected to be used (including adverse conditions).
  6. Assess AV readiness by developing a national traffic-control inventory and condition-assessment protocol.
  7. Develop Road safety audits (RSAs) to identify opportunities for improvements in safety for all road users. It is important to consider how AVs differ from human-led vehicles and how to accommodate those needs in the training and support material for RSAs.
Goal Areas