A Novel Intelligent Intersection Management Scheme Focusing on Cooperative Trajectory Planning of Connected Automated Vehicles

Bikang Hua, Hankun Jiang, Runqi Chai, Jinning Zhang, ISHRAK MD FARHAN, Yuanqing Xia, Senchun Chai

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

In the context of rapid development of the digital era, connected automated vehicle (CAV) technology brings revolutionary changes to the transportation field. This paper aims to study a novel intelligent traffic intersection management scheme, which focuses on the cooperative trajectory planning problem of a group of CAVs driving at the intersection. First, we model the intelligent intersection management scheme, which incorporates ethical and social considerations to align it more closely with real-world needs and challenges. Second, to address the complex challenges presented by the model during the optimization process, we propose an efficient adaptive dynamic optimization (ADO) strategy to simplify the solution process and accelerate the convergence speed of the optimal solution. In addition, the studied intelligent intersection management scheme is sufficiently flexible and scalable for handling traffic flow. Through simulations and experiments, the effectiveness of the entire intelligent intersection management scheme is verified. This paper provides a scientific and reliable basis for urban traffic planning in the real world.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalIEEE Transactions on Intelligent Vehicles
DOIs
Publication statusAccepted/In press - 2024

Keywords

  • CAV
  • cooperative motion planning
  • Ethics
  • intersection control
  • optimal control
  • Optimization
  • Planning
  • Real-time systems
  • Roads
  • trajectory optimization
  • Trajectory planning
  • Transportation

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