Blue phase: Optimal network traffic control for legacy and autonomous vehicles

With the forecasted emergence of autonomous vehicles in urban traffic networks, new control policies are needed to leverage their potential for reducing congestion. While several efforts have studied the fully autonomous traffic control problem, there is a lack of models addressing the more imminent transitional stage wherein legacy and autonomous vehicles share the urban infrastructure. The authors address this gap by introducing a new policy for stochastic network traffic control involving both classes of vehicles. The authors conjecture that network links will have dedicated lanes for autonomous vehicles which provide access to traffic intersections and combine traditional green signal phases with autonomous vehicle-restricted signal phases named blue phases. The authors propose a new pressure-based, decentralized, hybrid network control policy that activates selected movements at intersections based on the solution of mixed-integer linear programs. The authors prove that the proposed policy is stable, i.e. maximizes network throughput, under conventional travel demand conditions. They conduct numerical experiments to test the proposed policy under varying proportions of autonomous vehicles. The authors' experiments reveal that considerable trade-offs exist in terms of vehicle-class travel time based on the level of market penetration of autonomous vehicles. Further, the authors find that the proposed hybrid network control policy improves on traditional green phase traffic signal control for high levels of congestion, thus helping in quantifying the potential benefits of autonomous vehicles in urban networks.

• Record URL:
  https://doi.org/10.1016/j.trb.2019.11.001
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0191261518306271
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01912615
• Supplemental Notes:
  • © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Rey, David
  • Levin, Michael W
• Publication Date: 2019-12

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 105-129
• Serial:
  • Transportation Research Part B: Methodological
  • Volume: 130
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0191-2615
  • Serial URL: http://www.sciencedirect.com/science/journal/01912615

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Highway traffic control; Mixed integer programming; Networks; Signalized intersections; Traffic signal control systems; Urban areas
• Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01723785
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 27 2019 10:36AM