Decentralized cooperative crossing at unsignalized intersections via vehicle-to-vehicle communication in mixed traffic flows

Connected Autonomous Vehicles (CAVs) are going to share the road environment with human drivers until their full market deployment achievement. In this context, this paper tackles and solves the problem of decentralized crossing at unsignalized intersections for mixed traffic flows, composed of both connected human-driven vehicles (CHVs) and CAVs. To this aim, a novel cooperative fully-distributed control protocol for CAVs is proposed, augmenting the Adaptive Cruise Control (ACC) action based on proximity sensors measurements, with an additional networked protocol exploiting Vehicle-to-Vehicle (V2V) information for the cooperative evaluation of the Time-to-Intersection of all incoming vehicles within the communication range. This further collaborative action automatically adapts the CAVs motion at intersection avoiding both collisions with other vehicles and intersection deadlocks, while improving the intersection throughput. Safety and mobility performances are evaluated via the purposely designed Virtual Testing platform - Mixed Traffic Simulator (MiTraS)- combining the Matlab/Simulink environment with the SUMO traffic simulator. The analysis is carried out for an exemplary two-lane four-way unsignalized intersection considering both different traffic demands and different CAVs penetration rates. The unavoidable presence of variable delays in information delivery due to the wireless communication network has been also explicitly accounted for in both control design and validation. The extensive simulation analysis confirms how the inclusion of CAVs, equipped with the proposed control algorithm, within the mixed traffic flow strongly improves both the safety and mobility performances of the intersection. Lastly, the authors disclose how the benefits of the proposed controller increase with CAV penetration.

• Record URL:
  https://doi.org/10.1080/15472450.2022.2124868
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/15472450
• Supplemental Notes:
  • © 2022 Taylor & Francis Group, LLC. Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Bifulco, Gennaro Nicola
  • Coppola, Angelo
  • Petrillo, Alberto
  • Santini, Stefania
• Publication Date: 2024-3

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 211-236
• Serial:
  • Journal of Intelligent Transportation Systems
  • Volume: 28
  • Issue Number: 2
  • Publisher: Taylor & Francis
  • ISSN: 1547-2450
  • EISSN: 1547-2442
  • Serial URL: http://www.tandfonline.com/loi/gits20

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Connected vehicles; Decentralization; Unsignalized intersections; Vehicle mix; Vehicle to vehicle communications
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01909957
• Record Type: Publication
• Files: TRIS
• Created Date: Feb 27 2024 10:09AM