Safe autonomous lane changes and impact on traffic flow in a connected vehicle environment

Despite the recent advancements in autonomous vehicle technologies, performing safe lane changes and merging in dense traffic environments remains an open challenge. One important question is how to find a space to merge into without placing any vehicle in a collision-prone situation. Moreover, what is the traffic flow impact of doing so? To tackle this issue, the authors start by adopting a safety definition based on a worst-case braking scenario. The authors then propose a decentralized controller-agnostic cooperative approach for lane changes that relies only on Vehicle-to-Vehicle communications and guarantees safety. In the authors' method, the merging vehicle operates as having two possible leaders, one in its own lane and one in the destination lane, till the lane change maneuver is completed. Furthermore, the future following vehicle in the destination lane cooperates by acting as if the merging vehicle has already changed lanes. The merging vehicle only performs the lane change maneuver when the gaps are safe. Vehicle-level simulations are used to evaluate the approach in detail for a single lane change maneuver. Then, the method’s impact on highway safety and traffic flow is assessed using microscopic traffic simulations based on the commercial software VISSIM. The authors simulate three types of vehicles: adaptive cruise control equipped vehicles, autonomous vehicles, and connected and autonomous vehicles. The various simulations allow the authors to identify which improvements are brought by cooperative lane changes. Results indicate that connected and autonomous vehicles can achieve almost zero collision risk in congested and uncongested scenarios while improving traffic flow by 26% in the congested case. However, energy consumption increases significantly in the uncongested scenario. Moreover, the authors' method outperforms an existing cooperative lane-changing method regarding safety and traffic flow. The authors' simulations with mixed traffic suggest that the proposed method is advantageous only at high penetrations of autonomous vehicles or in congested situations.

• Record URL:
  https://doi.org/10.1016/j.trc.2023.104138
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0968090X23001274
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/0968090X
• Supplemental Notes:
  • © 2023 Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Monteiro, Fernando V
  • 0000-0002-6188-6971
  • Ioannou, Petros
• Publication Date: 2023-6

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 104138
• Serial:
  • Transportation Research Part C: Emerging Technologies
  • Volume: 151
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0968-090X
  • Serial URL: http://www.sciencedirect.com/science/journal/0968090X

Subject/Index Terms

• TRT Terms: Autonomous intelligent cruise control; Autonomous vehicles; Connected vehicles; Energy consumption; Lane changing; Merging traffic; Microsimulation; Traffic congestion; Traffic flow; Traffic safety
• Identifier Terms: VISSIM (Computer model)
• Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01890236
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 19 2023 3:06PM