{"title":"Real-Time Pedestrian Evacuation Planning during Emergency","authors":"T. Hadzic, Kenneth N. Brown, C. Sreenan","doi":"10.1109/ICTAI.2011.95","DOIUrl":null,"url":null,"abstract":"We develop a set of solution techniques for real-time evacuation guidance of pedestrians during emergency, focusing on evacuation from buildings during a fire. We model the problem as an extension of a dynamic network flow by allowing for nodes and edges to expire over time. This captures evacuation situations where the spreading hazard renders parts of the network unavailable. We formally state the problem, analyze its complexity, develop a set of heuristic approaches and compare their performance against a number of most relevant alternative approaches. We experimentally demonstrate that our heuristics outperform the alternatives and are suitable for real-time use even for large networks.","PeriodicalId":332661,"journal":{"name":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"25","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE 23rd International Conference on Tools with Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAI.2011.95","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 25
Abstract
We develop a set of solution techniques for real-time evacuation guidance of pedestrians during emergency, focusing on evacuation from buildings during a fire. We model the problem as an extension of a dynamic network flow by allowing for nodes and edges to expire over time. This captures evacuation situations where the spreading hazard renders parts of the network unavailable. We formally state the problem, analyze its complexity, develop a set of heuristic approaches and compare their performance against a number of most relevant alternative approaches. We experimentally demonstrate that our heuristics outperform the alternatives and are suitable for real-time use even for large networks.