Autonomous and Semi-Autonomous Intersection Management: A Survey

TL;DR

This survey reviews autonomous intersection management (AIM) techniques, highlighting their potential to reduce delays and accidents by coordinating vehicle crossings without traffic lights, and discusses future research directions.

Contribution

It provides a comprehensive overview of AIM designs across multiple disciplines, analyzing key aspects and proposing realistic evaluation scenarios.

Findings

AIM can eliminate stopping at intersections in ideal conditions.

Current AIM schemes face challenges in conflict detection and control complexity.

Future research should focus on realistic scenario testing and system robustness.

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.