Trajectory planning for autonomous intersection management of connected vehicles

Bing Liu, Qing Shi, Zhuoyue Song*, Abdelkader El Kamel

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

67 Citations (Scopus)

Abstract

This paper proposes a cooperative scheduling mechanism for autonomous vehicles passing through an intersection, called TP-AIM. The main objective of this research is to ensure safe driving while minimizing delay in an intersection without traffic lights. Firstly, an intersection management system, used as an info-collecting-organizing center, assigns reasonable priorities for all present vehicles and hence plans their trajectories. Secondly, a window searching algorithm is performed to find an entering window, which can produce a collision-free trajectory with minimal delay, besides backup windows. Finally, vehicles can arrange their trajectory individually, by applying dynamic programming to compute velocity profile, in order to pass through intersection. MATLAB/Simulink and SUMO based simulations are established among three types of traffic mechanisms with different traffic flows. The results show that the proposed TP-AIM mechanism significantly reduces the average evacuation time and increases throughput by over 20%. Moreover, the paper investigates intersection delay, which can be reduced to less than 10% compared to classical light management systems. Both safety and efficiency can be guaranteed in our proposed mechanism.

Original languageEnglish
Pages (from-to)16-30
Number of pages15
JournalSimulation Modelling Practice and Theory
Volume90
DOIs
Publication statusPublished - Jan 2019

Keywords

  • Autonomous intersection management
  • Dynamic programming
  • Intelligent transportation systems
  • Trajectory planning
  • V2X communications

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