{"title":"基于遗传算法的城市交通应急车辆控制","authors":"M. Pătrașcu, Vlad Constantinescu, Andreea Ion","doi":"10.3384/ECP17142243","DOIUrl":null,"url":null,"abstract":"Emergency officers could often benefit from a route planning system that is based on constant traffic monitoring and complex decision making, seeking to give victims another breath of hope by assisting emergency units with reaching them on time. The main challenge is providing responses in a continuously evolving environment within a prescribed time frame, while using limited resources and information that is often incomplete or uncertain. This paper presents a route control concept for emergency vehicles through urban traffic. The proposed genetic controller is designed to dynamically reassess the route while the vehicle passes through the road network, continuously generating new routes based on current traffic. The algorithm is tested in an agent based simulation model that includes both traffic participants and a distributed traffic control system.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":"96 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Controlling Emergency Vehicles in Urban Traffic with Genetic Algorithms\",\"authors\":\"M. Pătrașcu, Vlad Constantinescu, Andreea Ion\",\"doi\":\"10.3384/ECP17142243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Emergency officers could often benefit from a route planning system that is based on constant traffic monitoring and complex decision making, seeking to give victims another breath of hope by assisting emergency units with reaching them on time. The main challenge is providing responses in a continuously evolving environment within a prescribed time frame, while using limited resources and information that is often incomplete or uncertain. This paper presents a route control concept for emergency vehicles through urban traffic. The proposed genetic controller is designed to dynamically reassess the route while the vehicle passes through the road network, continuously generating new routes based on current traffic. The algorithm is tested in an agent based simulation model that includes both traffic participants and a distributed traffic control system.\",\"PeriodicalId\":56990,\"journal\":{\"name\":\"建模与仿真(英文)\",\"volume\":\"96 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"建模与仿真(英文)\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.3384/ECP17142243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"建模与仿真(英文)","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.3384/ECP17142243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Controlling Emergency Vehicles in Urban Traffic with Genetic Algorithms
Emergency officers could often benefit from a route planning system that is based on constant traffic monitoring and complex decision making, seeking to give victims another breath of hope by assisting emergency units with reaching them on time. The main challenge is providing responses in a continuously evolving environment within a prescribed time frame, while using limited resources and information that is often incomplete or uncertain. This paper presents a route control concept for emergency vehicles through urban traffic. The proposed genetic controller is designed to dynamically reassess the route while the vehicle passes through the road network, continuously generating new routes based on current traffic. The algorithm is tested in an agent based simulation model that includes both traffic participants and a distributed traffic control system.