Proactive vehicular traffic rerouting for lower travel time

Juan Pan, Iulian Sandu Popa, Karine Zeitouni, Cristian Borcea

Research output: Contribution to journalArticlepeer-review

69 Scopus citations

Abstract

Traffic congestion causes driver frustration and costs billions of dollars annually in lost time and fuel consumption. This paper presents five traffic rerouting strategies designed to be incorporated in a cost-effective and easily deployable vehicular traffic guidance system that reduces travel time. The proposed strategies proactively compute individually tailored rerouting guidance to be pushed to vehicles when signs of congestion are observed on their route. The five proposed strategies are the dynamic shortest path (DSP), the A* shortest path with repulsion (AR*), the random k shortest path (RkSP), the entropy-balanced kSP (EBkSP), and the flow-balanced kSP (FBkSP). Extensive simulation results show that the proposed strategies are capable of reducing the travel time as much as a state-of-the-art dynamic traffic assignment (DTA) algorithm while avoiding the issues that make DTA impractical, such as the lack of scalability and robustness, and high computation time. Furthermore, the variety of proposed strategies allows tuning the system to different levels of tradeoffs between rerouting effectiveness and computational efficiency. In addition, the proposed traffic guidance system can significantly improve the traffic even if many drivers ignore the guidance or if the system adoption rate is relatively low.

Original languageEnglish (US)
Article number6509488
Pages (from-to)3551-3568
Number of pages18
JournalIEEE Transactions on Vehicular Technology
Volume62
Issue number8
DOIs
StatePublished - 2013

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

Keywords

  • Proactive driver guidance
  • Traffic load balancing
  • Vehicular congestion avoidance
  • Vehicular networks

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