Improving Intersection Safety through Variable Speed Limits for Connected Vehicles

Details

• Creators:
  Levin, Michael W. ; Chen, Rongsheng ; Liao, Chen-Fu ; Zhang, Tab
• Corporate Creators:
  University of Minnesota. Dept. of Civil, Environmental, and Geo-Engineering
• Corporate Contributors:
  Roadway Safety Institute (UTC) ; University of Minnesota. Center for Transportation Studies
• Subject/TRT Terms:
  • Algorithms
  • Autonomous vehicles
  • Intelligent transportation systems
  • Signalized intersections
  • Traffic flow
  • Traffic speed
  • Variable speed limits
  • Variable speed limits
  • Intersections
  • Connected vehicles
  More +
• Publication/ Report Number:
  CTS 19-12
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report
• Corporate Publisher:
  Roadway Safety Institute (UTC)
• Abstract:
  Autonomous vehicles create new opportunities for innovative intelligent traffic systems. Variable speed limits, which is a speed management systems that can adjust the speed limit according to traffic condition or predefined speed control algorithm on different road segments, can be better implemented with the cooperation of autonomous vehicles. These compliant vehicles can automatically follow speed limits. However, non-compliant vehicles will attempt to pass the moving bottleneck created by the compliant vehicle. This project builds a multi-class cell transmission model to represent the relation between traffic flow parameters. This model can calculate flows of both compliant and non-compliant vehicles. An algorithm is proposed to calculate variable speed limits for each cell of the cell transmission model. This control algorithm is designed to reduce the stop-and-go behavior of vehicles at traffic signals. Simulation is used to test the effects of VSLs on an example network. The result shows that VSL is effective at reducing the energy consumption of the whole system and reduce the likelihood of crash occurrence.
• Format:
  PDF
• Funding:
  DTRT13-G-UTC35
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/42704/dot_42704_DS1.pdf
• File Type:
  [PDF - 1.51 MB]
• Collection(s):
  Autonomous Vehicles ; US Transportation Collection
• Main Document Checksum:
  urn:sha-512:daa7f831bcb579a5ef33c0e015cc09d94f040fb0e0ded49853a589a363ac8d8d75258ca0a01fa0b9a30668fd52f898dc0ff69af97e413973d1c5152d20afc6eb