Optimizing emergency rescue and evacuation planning with intelligent obstacle avoidance in a chemical industrial park

Peizhu Chen, Guohua Chen*, Liangwang Wang, Genserik Reniers

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)

Abstract

A major chemical accident has the characteristics of being destructive, and potentially provoking a great loss of lives and property damage in any Chemical Industrial Park (CIP). Emergency rescue and evacuation are essential parts of emergency decision-making for enhancing the capacity and effectiveness of emergency handling and reducing the potential loss of accidents. Most of current literature concentrates on one-way route planning of emergency rescue and evacuation, and applies different models, optimization objectives and algorithms. However, when applying the one-way route planning model in a CIP, a road conflict is possible due to the inherent weak traffic capacity. Therefore, a new method of two-way route planning of emergency rescue and emergency evacuation which considers intelligent obstacle avoidance, is proposed in the paper. The method we developed integrates three modeling components: (i) a dynamic grid environment model to simulate the interaction between the road network and the time-varying location of emergency rescue and evacuation. (ii) a two-way route planning model to simultaneously optimize routes of emergency rescue and routes of emergency evacuation. (iii) an intelligent obstacle avoidance model to prevent potential road conflicts. The results illustrate that the proposed model is able to generate a set of two-way optimum routes and overcomes possible road conflicts successfully.

Original languageEnglish
Pages (from-to)119-127
Number of pages9
JournalJournal of Loss Prevention in the Process Industries
Volume56
DOIs
Publication statusPublished - 2018

Keywords

  • Chemical industrial park
  • DNV Phast 7.21
  • Dynamic grid method
  • Emergency evacuation
  • Emergency rescue
  • Route planning

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