English

Autonomous and Semi-Autonomous Intersection Management: A Survey

Multiagent Systems 2020-11-03 v3

Abstract

Intersection is a major source of traffic delays and accidents within modern transportation systems. Compared to signalized intersection management, autonomous intersection management (AIM) coordinates the intersection crossing at an individual vehicle level with additional flexibility. AIM can potentially eliminate stopping in intersection crossing due to traffic lights while maintaining a safe separation among conflicting movements. In this paper, the state-of-the-art AIM research among various disciplines (e.g., traffic engineering, control engineering) is surveyed from the perspective of three hierarchical layers: corridor coordination layer, intersection management layer, and vehicle control layer. The key aspects of AIM designs are discussed in details, including conflict detection schemes, priority rules, control centralization, computation complexity, etc. The potential improvements for AIM evaluation with the emphasis of realistic scenarios are provided. This survey serves as a comprehensive review of AIM design and provides promising directions for future research.

Keywords

Cite

@article{arxiv.2006.13133,
  title  = {Autonomous and Semi-Autonomous Intersection Management: A Survey},
  author = {Zijia Zhong and Mark Nejad and Earl E. Lee},
  journal= {arXiv preprint arXiv:2006.13133},
  year   = {2020}
}

Comments

16 pages, 10 figures

R2 v1 2026-06-23T16:33:44.417Z