Autonomous and Semiautonomous Intersection Management: A Survey
Intersections are 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, which provides additional flexibility. AIM can potentially eliminate stopping in intersection crossings due to traffic lights while maintaining a safe separation among conflicting movements. In this article, the state-of-the-art AIM research among various disciplines (e.g., traffic engineering and 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 detail, including conflict detection schemes, priority rules, control centralization, computation complexity, and so on. Potential improvements for AIM evaluation with the emphasis on realistic scenarios are provided. This article serves as a comprehensive review of AIM design and provides promising directions for future research.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/19391390
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Supplemental Notes:
- Copyright © 2021, IEEE.
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Authors:
- Zhong, Zhangdui
- Nejad, Mark
- Lee, Earl E
- Publication Date: 2021
Language
- English
Media Info
- Media Type: Web
- Features: Figures; References;
- Pagination: pp 53-70
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Serial:
- IEEE Intelligent Transportation Systems Magazine
- Volume: 13
- Issue Number: 2
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1939-1390
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5117645
Subject/Index Terms
- TRT Terms: Advanced vehicle control systems; Highway traffic control; Intelligent agents; Intersections; Traffic engineering
- Subject Areas: Highways; Operations and Traffic Management; Vehicles and Equipment;
Filing Info
- Accession Number: 01779380
- Record Type: Publication
- Files: TRIS
- Created Date: Aug 24 2021 10:35AM