Optimal Mandatory Lane-Changing Location Planning for CAV Based on Cell Transmission Model

If dedicate a lane to connected autonomous vehicle (CAV) on a multilane road, the traffic congestion and safety risks remain a major problem but in a different style. Random and disorderly mandatory lane-changing behaviour before approaching the next ramp or intersection would have a disturbing effect on the following vehicles of the traffic flow. This paper mainly establishes the optimal mandatory lane-changing location matching model for each target vehicle in the dedicated CAV lane environment. The aim is to minimizing the total travel time, which could take the disturbing effect into account. This model nests the cell transmission model (CTM) to describe vehicle running. The constraints include the relation between target CAV lane-changing cell and the corresponding behaviour start time, the updating of the flow, and occupancy for varied cells. The authors use the Ant Colony Optimization (ACO) algorithm to solve the problem. Through the case study of a basic two-lane road scenario in Ningbo, the authors acquire the convergence results based on the ACO algorithm. The authors' optimal lane-changing location matching scheme can save 5.9% total travel time when compared to the near-end location lane-changing scheme. The authors test the authors' model by increasing the total number of upstream input vehicles with 4%, 11%, 15%, and the mandatory lane-changing vehicles with 60%, 200%, respectively. The testing results prove that out optimization method could deal with varied road traffic flow situations. Specifically, when the traffics and mandatory lane-changing vehicles increase, the authors' method could perform better.

• Record URL:
  https://doi.org/10.1155/2024/9411726
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/5121625
• Supplemental Notes:
  • © 2024 Gao Gao et al.
• Authors:
  • Gao, Gao
  • Huang, Zhengfeng
  • Ji, Wei
  • Zheng, Pengjun
• Publication Date: 2024-3

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: Article ID 9411726
• Serial:
  • Journal of Advanced Transportation
  • Volume: 2024
  • Publisher: John Wiley & Sons, Incorporated
  • ISSN: 0197-6729
  • EISSN: 2042-3195
  • Serial URL: http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2042-3195
• Publication flags:

  Open Access (libre)

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Connected vehicles; Lane changing; Traffic flow; Traffic models
• Geographic Terms: Ningbo (China)
• Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01919684
• Record Type: Publication
• Files: TRIS
• Created Date: May 28 2024 9:19AM