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8 June 2024 The shortest path algorithm for urban rail transit based on spatio-temporal accessibility
Xuyang Song, Xiao Fang, Guanhua Liu, Shurong Pang, Cong Cao, Wensheng Yu, Ling Fan
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Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 1317105 (2024) https://doi.org/10.1117/12.3031924
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China
Abstract
Rail transit systems are an important part of public transportation in large cities. However, unforeseen emergencies such as floods, equipment failures, or large events can cause serious consequences such as traffic congestion and stranded passengers, thus affecting the normal operation of rail transit. To cope with these emergencies, this paper proposes a new algorithm that can query the latest reachable time under time constraints. A rail network model is developed to optimize Dijkstra's algorithm in emergency situations by using a new data structure. The study emphasizes the temporal complexity and spatio-temporal accessibility of the algorithm. Finally, the model and algorithm are validated using data from the Beijing Metro. The proposed shortest path planning emergency strategy for rail transit and the application of the algorithm are mainly aimed at the command center level of rail transit and solved practical problems.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Xuyang Song, Xiao Fang, Guanhua Liu, Shurong Pang, Cong Cao, Wensheng Yu, and Ling Fan "The shortest path algorithm for urban rail transit based on spatio-temporal accessibility", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 1317105 (8 June 2024); https://doi.org/10.1117/12.3031924
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KEYWORDS
Transportation
Detection and tracking algorithms
Algorithm development
Emergency preparedness
Mathematical optimization
Roads
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