Lane Management in the Era of CAV Deployment

Smaller headways between vehicles provide an opportunity to address traffic congestion and its attendant adverse impacts. Connected and autonomous vehicle (CAV)-dedicated lanes can help reduce headway. However, building new lanes for CAV use is costly. Such cost can be reduced by redistributing/reallocating existing roadway space to HDV and CAV lanes. In doing this, however, the road agency must address planning-level questions on the influence of CAV market demand on CAV dedicated lane deployment feasibility and sustainability impacts, and operations-level issues regarding the impacts of the value of time, early/late arrival penalties on departure time choices of CAV and HDV commuters and congestion. This research first incorporates CAV market size uncertainties and width differentials between CAV and HDV lanes. The research develops and tests a solution algorithm on real road networks. Secondly, this project addresses a specific but common context of highway operations – a road section that has limited capacity and multiple lanes, commuters using either CAV or HDV during the morning peak period, with identical desired arrival times, early/late arrival penalty but different values of time.

• Record URL:
  https://ccat.umtri.umich.edu/research/purdue/lane-management-in-the-era-of-cav-deployment/

Language

• English

Project

• Status: Completed
• Funding: $200000
• Contract Numbers:

  69A3551747105

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  Center for Connected and Automated Transportation

  University of Michigan Transportation Research Institute
  Ann Arbor, MI  United States  48109
• Project Managers:

  Tucker-Thomas, Dawn

  Bezzina, Debra

• Performing Organizations:

  Purdue University, Lyles School of Civil Engineering

  550 Stadium Mall Drive
  West Lafayette, IN  United States  47907
• Principal Investigators:

  Labi, Samuel

  Miralinaghi, Mohammad

  Sundaram, Shreyas

• Start Date: 20220401
• Expected Completion Date: 20230331
• Actual Completion Date: 20240102
• USDOT Program: University Transportation Centers Program

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Congestion management systems; Connected vehicles; Highway design; Lane distribution; Market penetration; Traffic lanes
• Subject Areas: Design; Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01846013
• Record Type: Research project
• Source Agency: Center for Connected and Automated Transportation
• Contract Numbers: 69A3551747105
• Files: UTC, RIP
• Created Date: May 21 2022 8:02AM