Access Control at Major/Minor Road Intersection Through CAV in Mixed Traffic

Details

• Creators:
  Yi, Ping
• Corporate Creators:
  University of Akron. Department of Civil Engineering ; Center for Connected and Automated Transportation (CCAT)
• Corporate Contributors:
  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
  • Autonomous vehicles
  • Traffic flow
  • T intersections
  • Probability
  • Simulation
  • Gap Creation
• Publication/ Report Number:
  UA-CETran 2023-01
• DOI:
  https://doi.org/10.5703/1288284317738
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (July 2018 – December 2022)
• Corporate Publisher:
  University of Michigan. Center for Connected and Automated Transportation
• Abstract:
  Roadway intersections are among the major causes of traffic congestion besides lane reduction bottlenecks. When a major road intersects a minor road at an unsignalized intersection without the control of a traffic signal, the mainline vehicles are given priority over the minor road vehicles to go through the intersection, and the latter can only enter or cross the intersection when there is a sufficient gap between successive vehicles on the major road. Connected and automated vehicles (CAV) are packed with tracking and lane-keeping assistance and adaptive speed control to ensure that vehicles do not collide while reducing traffic congestion. This research aims to utilize CAVs to help generate usable gaps for minor road vehicles to enter the intersection without interrupting the mainline traffic flow. A probability function is developed to study the probability in which CAVs can create additional usable gaps for the minor road vehicles based on the headway distribution of the mainline vehicles.
• Format:
  PDF
• Funding:
  69A3551747105
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/73985/dot_73985_DS1.pdf
• File Type:
  [PDF - 8.49 MB]
• Collection(s):
  Autonomous Vehicles ; University Transportation Centers
• Main Document Checksum:
  urn:sha-512:9476a0eab5d16aaa6ad95e359cff4e5a30eaa9d66f65e98b1fe18e532f80490d5b5af4002407b750ffbfde3e2c7b4be3818f5b1e30c080668e816adb454aaa79