{"title":"Multiagent system architecture and method for group-oriented traffic coordination","authors":"Jana Görmer, J. Müller","doi":"10.1109/DEST.2012.6227949","DOIUrl":null,"url":null,"abstract":"Next-generation traffic management systems will make use of on-board intelligence and communication capabilities of vehicles and traffic infrastructure. In this paper, we investigate a multiagent approach allowing vehicle agents to form groups in order to co-ordinate their speed and lane choices. Our hypothesis is that a decentralized approach based on a co-operative driving method can contribute to higher and smoother traffic flow, leading to higher speeds and less delays. Our focus is on automated vehicle decision models. We develop a group-oriented driving method with vehicle agents that perceive their environment and exchange information. The paper proposes decentralized dynamic vehicle grouping algorithm, a conflict detection and global coordination method, and defines individual driving strategies for vehicles. For validation, we compare our method with a driving method implemented in the commercial traffic simulation platform AIMSUN. Experimental results indicate that group formation and group coordination methods can improveme traffic network throughput.","PeriodicalId":320291,"journal":{"name":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 6th IEEE International Conference on Digital Ecosystems and Technologies (DEST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEST.2012.6227949","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Next-generation traffic management systems will make use of on-board intelligence and communication capabilities of vehicles and traffic infrastructure. In this paper, we investigate a multiagent approach allowing vehicle agents to form groups in order to co-ordinate their speed and lane choices. Our hypothesis is that a decentralized approach based on a co-operative driving method can contribute to higher and smoother traffic flow, leading to higher speeds and less delays. Our focus is on automated vehicle decision models. We develop a group-oriented driving method with vehicle agents that perceive their environment and exchange information. The paper proposes decentralized dynamic vehicle grouping algorithm, a conflict detection and global coordination method, and defines individual driving strategies for vehicles. For validation, we compare our method with a driving method implemented in the commercial traffic simulation platform AIMSUN. Experimental results indicate that group formation and group coordination methods can improveme traffic network throughput.