Pre-siting of UAV stations for traffic accident assessment considering road dispersion

Sizhe Wang and Yanying Shang

PLOS ONE, 2025, vol. 20, issue 2, 1-24

Abstract: This paper investigates the issue of pre-site selection for drone stations with the aim of enhancing the rapid assessment capability of urban road traffic accidents. Firstly, the influence of traffic accidents on urban traffic is analyzed, and the potential application of drones in rapid response at the accident scene is explored. A minimization model is constructed with the goal of minimizing the cost of accident handling and reducing traffic congestion. To solve this problem, we improved the simulated annealing algorithm by combining the multi-neighborhood strategy, adaptive neighborhood size, and adding a taboo list, and verified the effectiveness of the algorithm. The validity of the model is tested through simulation examples, and the impact of the drone coverage radius and the distribution of accident points on the model performance is explored through sensitivity analysis, providing management insights for the pre-site selection of drone stations.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0316431

DOI: 10.1371/journal.pone.0316431

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