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Prediction based traffic management in a metropolitan area

Journal of Traffic and Transportation Engineering(English Edition) 2020年第4期7卷 447-466页

作者： Suresh Chauhan Pallapa Venkataram Automotiue Research Center Vellore Institute of TechnologyVellore 632014India Department of Electrical Communication Engineering Indian Institute of ScienceBangalore 560012India

In recent years,modern metropolitan areas are the main indicators of economic growth of *** metropolitan areas,number and frequency of vehicles have increased tremendously,and they create issues,like traffic congestion,accidents,environmental pollution,economical losses and unnecessary waste of *** this paper,we propose traffic management system based on the prediction information to reduce the above mentioned issues in a metropolitan *** proposed traffic management system makes use of static and mobile agents,where the static agent available at region creates and dispatches mobile agents to zones in a metropolitan *** migrated mobile agents use emergent intelligence technique to collect and share traffic flow parameters(speed and density),historical data,resource information,spatio-temporal data and so on,and are analyzes the static *** emergent intelligence technique at static agent uses analyzed,historical and spatio-temporal data for monitoring and predicting the expected patterns of traffic density(commuters and vehicles)and travel times in each zone and *** static agent optimizes predicted and analyzed data for choosing optimal routes to divert the traffic,in order to ensure smooth traffic flow and reduce frequency of occurrence of traffic congestion,reduce traffic density and travel *** performance analysis is performed in realistic scenario by integrating NS2,SUMO,OpenStreatMap(OSM)and MOVE *** effectiveness of the proposed approach has been compared with the existing approach.

关键词： Traffic management Traffic prediction Travel time prediction Agent emergent intelligence Swarm intelligence

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