{"title":"An Agent Based Approach for Balancing Commuter Traffic","authors":"Martin Carpenter, N. Mehandjiev","doi":"10.1109/WETICE.2010.12","DOIUrl":null,"url":null,"abstract":"Transport congestion within cities represents an omnipresent yet increasingly serious problem. Traditionally the main method of control available to combat it has been the efficient control of traffic lights. The recent rise of intelligent mobile devices carried by road users offers an additional point of control, potentially enabling the manipulation of the routes that people take within the city. The current paper combines the use of such devices with intelligent agents representing different transport segments within the city, including roads, trams, busses and trains. It fuses them in a novel technique which attempts to evenly spread the traffic load throughout the different transport options within the city. In addition the system is capable of rebalancing this load dynamically in response to any events which reduce the capacity of a given transport segment within the city. The system complements the existing work on traffic light control.","PeriodicalId":426248,"journal":{"name":"2010 19th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 19th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WETICE.2010.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Transport congestion within cities represents an omnipresent yet increasingly serious problem. Traditionally the main method of control available to combat it has been the efficient control of traffic lights. The recent rise of intelligent mobile devices carried by road users offers an additional point of control, potentially enabling the manipulation of the routes that people take within the city. The current paper combines the use of such devices with intelligent agents representing different transport segments within the city, including roads, trams, busses and trains. It fuses them in a novel technique which attempts to evenly spread the traffic load throughout the different transport options within the city. In addition the system is capable of rebalancing this load dynamically in response to any events which reduce the capacity of a given transport segment within the city. The system complements the existing work on traffic light control.