An evacuation path planning method for multi-hazard accidents in chemical industries based on risk perception

Zhichao He, Kaixin Shen, Meng Lan and Wenguo Weng

Reliability Engineering and System Safety, 2024, vol. 244, issue C

Abstract: Evacuation path planning is an important research topic in emergency management of chemical accidents. Facing the challenges of the continuous increase in the frequency of multi-hazard chemical accidents including fires, explosions, and toxic releases, the requirement to improve the evacuation path planning method considering the dynamic and multi-hazard characteristics of the accidents has become increasingly urgent. In order to address the shortcomings of the static, single-hazard, and passive evacuation path planning methods, this paper proposes an evacuation path planning method for multi-hazard accidents in chemical industries based on advance and on-site risk perception. This method applies dynamic and comprehensive risk analysis as the equivalent distance criterion to improve the D* path planning algorithm. A chemical park in Guangzhou, China, is adopted as a case study to verify the effectiveness of the proposed method and quantitatively demonstrate the effect of the method in improving evacuation efficiency. This paper further discusses the flexibility of the proposed method in considering environmental factors, evacuation preferences, and emergency response requirements. The evacuation path planning method proposed in this paper is expected to contribute to the optimization of emergency management of multi-hazard accidents and provide guidance for the enhancement of safety and loss prevention in chemical industries.

Keywords: Emergency evacuation; Multi-hazard accident; Risk analysis; Chemical industry; D* algorithm (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:244:y:2024:i:c:s0951832023008268

DOI: 10.1016/j.ress.2023.109912

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