{"title":"Research on Public Vehicle Evacuation Path Planning Model Based on Spatiotemporal Network","authors":"Wenxuan Zhang, Zhengwei Lin, Ziyang Wang, Yipu Huang, Haoyuan Shi, Ying Li","doi":"10.56028/aetr.9.1.826.2024","DOIUrl":null,"url":null,"abstract":"This study aims to improve the efficiency of public vehicle evacuation during large-scale disasters by minimizing travel and waiting times for individuals and vehicles. To accomplish this, an S-curve behavior model was used to estimate evacuation demand, and a network model was developed to consider temporal and spatial factors of gathering points. A hybrid genetic algorithm and simulated annealing approach were utilized with an \"enumerate then optimize\" strategy and a step to temporarily retain optimal solutions for refinement. The effectiveness of the proposed model and algorithms was demonstrated in a case study of a typhoon evacuation in Chikan District, providing valuable insights for urban evacuation planning.","PeriodicalId":355471,"journal":{"name":"Advances in Engineering Technology Research","volume":"15 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Engineering Technology Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56028/aetr.9.1.826.2024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This study aims to improve the efficiency of public vehicle evacuation during large-scale disasters by minimizing travel and waiting times for individuals and vehicles. To accomplish this, an S-curve behavior model was used to estimate evacuation demand, and a network model was developed to consider temporal and spatial factors of gathering points. A hybrid genetic algorithm and simulated annealing approach were utilized with an "enumerate then optimize" strategy and a step to temporarily retain optimal solutions for refinement. The effectiveness of the proposed model and algorithms was demonstrated in a case study of a typhoon evacuation in Chikan District, providing valuable insights for urban evacuation planning.
本研究旨在通过最大限度地减少个人和车辆的旅行和等待时间,提高大规模灾难期间公共车辆疏散的效率。为实现这一目标,使用了 S 曲线行为模型来估计疏散需求,并开发了一个网络模型来考虑聚集点的时间和空间因素。利用混合遗传算法和模拟退火方法,采用 "先枚举后优化 "的策略,并暂时保留最优解以进行改进。通过对赤坎区台风疏散的案例研究,证明了所提模型和算法的有效性,为城市疏散规划提供了有价值的见解。