Title: A Collaborative Work Platform for Dynamic Travel Information Service with Short-term Traffic Prediction
Abstract: Implementing convenient traveling information service is a crucial task for carrying out the strategy of intelligent transportation system and developing location-based services.At present,most of the domestic traveling information service systems only provide relatively static information which can't reflect the possible short-term changes of traffic,and result in very limited practical use.Although there have emerged some car navigation products and other applications involving real-time traffic information,considering the rapid change of city traffic situation,these products and applications still face practical difficulties for all the information received real-timely will get outdated within a few minutes,which makes the so called dynamic applications basically time-slice limited static ones.This paper presents a practical short-term traffic prediction approach in real-time conditions by integrating historical traffic based statistical reasoning with back propagation neural network based analytical model,and commercial microscopic traffic simulation software.The historical traffic based statistical reasoning utilizes the inherent traffic rules by identifying the general spatial-temporal distribution pattern,and ignores any inputs that don't contribute to the output during the training process,including the gross error in the collected traffic data.The commercial microscopic traffic simulation software process the traffic abnormities that always exist in big cities,and has no requirement for the collected real-time traffic information to cover the whole road network,hence provides an effective supplement for short-term traffic forecast.Then an approach is developed combining GIS server,traffic prediction server and database management system to implement dynamic route guidance.The traffic prediction server receives real-time traffic information obtained from floating vehicles and achieves short-term forecasting results for the whole road networks,then fed the results back into the database management system and GIS server,so that a time-dependant optimal routing can be conducted through a dynamic least traveling time algorithm developed in this study.A prototype fulfilling the above aspects has been developed and validated with a city road network and real-timely collected traffic information.The approach presented in this paper is argued to provide a practical solution for real-time public traveling information service and dynamic web maps.
Publication Year: 2009
Publication Date: 2009-01-01
Language: en
Type: article
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Cited By Count: 1
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