Safe and Efficient Automated Freeway Traffic Control-Phase 3 Final Report

Details

• Creators:
  Coifman, Benjamin ; Liu, Yuan
• Corporate Creators:
  Ohio State University. Department of Civil and Environmental Engineering and Geodetic Science
• Corporate Contributors:
  Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC) ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • Connected vehicles
  • Intelligent vehicles
  • Freeway management systems
  • Traffic congestion
  • Traffic safety
  • Highway capacity
  • Lane changing
  • Rear end crashes
  • Traffic control
  • Traffic platooning
  More +
• Publication/ Report Number:
  575
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (July 1, 2025 - July 31, 2026)
• Corporate Publisher:
  Carnegie Mellon University. Traffic21 Institute. Safety21 University Transportation Center (UTC)
• Abstract:
  The goal of this work is to eliminate unexpected stops to improve safety with the added benefit of reducing accelerations to improve fuel efficiency. Congested traffic is characterized by signals and waves propagating upstream through the queued traffic. Freeway drivers do not expect to encounter abrupt drops in speed or stopped traffic, as a result, shockwaves sharply increase the accident rates, particularly in the context of rear end collisions. This work seeks to use connected and automated vehicles (CAV) to smooth out traffic disturbances on a freeway. Prior work in Phase 1 developed a method for a single CAV to integrate the instantaneous state information from the downstream vehicles to forecast the trajectory of the CAV's leader and proactively respond to changes in state that have not yet reached the lead vehicle. Phase 2, extended the methodology to a platoon of 15 CAV's, leading to greater smoothing than the single CAV results. This study, Phase 3, extended the methodology to address several key aspects. First, to use multiple platoons to buffer against capacity fluctuations and provide finer control. Second, extending the methodology to accommodate lane change maneuvers so that they do not disrupt platoons. Third, develop contingency plans to accommodate situations when the state evolution deviates from forecasts. In this way, the research anticipates and develops the management strategies needed to maintain smoothly flowing queued traffic with CAV's.
• Format:
  PDF
• Funding:
  69A3552344811 ; 69A3552348316
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/93512/dot_93512_DS1.pdf
• File Type:
  [PDF - 6.51 MB]
• Collection(s):
  Autonomous Vehicles ; University Transportation Centers
• Main Document Checksum:
  urn:sha-512:ab306f66a4052b29e744e0b9c60be380c3a3e51d49d0ae749387de516914c6b8f5d9e92c9d717cc8b02185865ab5feb3bc3f1f3fd0a488217e2ab3819fcadd3f