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Dynamic Travel Time Prediction Models for Buses Using Only GPS Data

International Journal of Transportation Science and Technology 2015年第4期4卷 353-366页

作者： Wei Fan zegeye gurmu Associate Professor Department of Civil and Environmental EngineeringThe University of North Carolina at CharlotteEPIC BuildingRoom 32619201 University City BoulevardCharlotteNC 28223 Traffic Engineer-Teague Nall&Perkins Inc.1100 Macon StreetFort WorthTexas 76102

Providing real-time and accurate travel time information of transit vehicles can be very helpful as it assists passengers in planning their trips to minimize waiting *** purpose of this research is to develop and compare dynamic travel time prediction models which can provide accurate prediction of bus travel time in order to give realtime information at a given downstream bus stop using only global positioning system(GPS)*** Average(HA),Kalman Filtering(KF)and Artificial Neural Network(ANN)models are considered and developed in this paper.A case has been studied by making use of the three *** results are obtained from the case study,indicating that the models can be used to implement an Advanced Public Transport *** implementation of this system could assist transit operators in improving the reliability of bus services,thus attracting more travelers to transit vehicles and helping relieve *** performances of the three models were assessed and compared with each other under two criteria:overall prediction accuracy and *** was shown that the ANN outperformed the other two models in both *** conclusion,it is shown that bus travel time information can be reasonably provided using only arrival and departure time information at stops even in the absence of traffic-stream data.

关键词： operators attracting conclusion

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