Modelling of Emergency Vehicles Route Choice with Use of Trajectory Data

Bieker-Walz, Laura; Flötteröd, Yun-Pang; Sohr, Alexander

doi:10.1109/mtits.2019.8883323

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Distance is commonly measured by Euclidean distance and Manhattan distance [24][25][26]. For emergency travel time, most studies have been derived from Global Information System or estimated from scenario settings [27][28][29][30]. However, little research has been done on the problems arising from the performance of dynamic road networks, and there is a research gap of combining resource allocation with path planning.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Emergency Resource Allocation under the Natural Disaster Chain with Path Planning

Wang

Xie

Liu

et al. 2022

IJERPH

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Public safety and health cannot be secured without the comprehensive recognition of characteristics and reliable emergency response schemes under the disaster chain. Distinct from emergency resource allocation that focuses primarily on a single disaster, dynamic response, periodic supply, and assisted decision-making are necessary. Therefore, we propose a multiobjective emergency resource allocation model considering uncertainty under the natural disaster chain. Resource allocation was creatively combined with path planning through the proposed multiobjective cellular genetic algorithm (MOCGA) and the improved A* algorithm with avoidance of unexpected road elements. Furthermore, timeliness, efficiency, and fairness in actual rescue were optimized by MOCGA. The visualization of emergency trips and intelligent avoidance of risk areas were achieved by the improved A* algorithm. The effects of logistics performance, coupling of disaster factors, and government regulation on emergency resource allocation were discussed based on different disaster chain scenarios. The results show that disruption in infrastructure support, cascading effect of disasters, and time urgency are additional environmental challenges. The proposed model and algorithm work in obtaining the optimal solution for potential regional coordination and resilient supply, with a 22.2% increase in the total supply rate. Cooperative allocation complemented by political regulation can be a positive action for successfully responding to disaster chains.

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