Travel time information is a vital component of many intelligent transportation systems (ITS) applications. In recent years, the number of vehicles in India has increased tremendously, leading to severe traffic congestion and pollution in urban areas, particularly during peak periods. A desirable strategy to deal with such issues is to shift more people from personal vehicles to public transport by providing better service (comfort, convenience and so on). In this context, advanced public transportation systems (APTS) are one of the most important ITS applications, which can significantly improve the traffic situation in India. One such application will be to provide accurate information about bus arrivals to passengers, leading to reduced waiting times at bus stops. This needs a real-time data collection technique, a quick and reliable prediction technique to calculate the expected travel time based on real-time data and informing the passengers regarding the same. The scope of this study is to use global positioning system data collected from public transportation buses plying on urban roadways in the city of Chennai, India, to predict travel times under heterogeneous traffic conditions using an algorithm based on the Kalman filtering technique. The performance of the proposed algorithm is found to be promising and expected to be valuable in the development of APTS in India. The work presented here is one of the first attempts at real-time short-term prediction of travel time for ITS applications in Indian traffic conditions.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Travel time prediction under heterogeneous traffic conditions using global positioning system data from buses


    Beteiligte:
    Vanajakshi, L. (Autor:in) / Subramanian, S.C. (Autor:in) / Sivanandan, R. (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2009-03-01


    Format / Umfang :

    9 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Dynamic Travel Time Prediction Models for Buses Using Only GPS Data

    Wei Fan / Zegeye Gurmu | DOAJ | 2015

    Freier Zugriff

    Urban traffic travel time prediction method for multi-source heterogeneous data

    LIU FENGKAI / LI MU / FENG YIJUN | Europäisches Patentamt | 2022

    Freier Zugriff



    Freeway path travel time prediction based on heterogeneous traffic data through nonparametric model

    Qiao, Wenxin / Haghani, Ali / Shao, Chun-Fu et al. | Taylor & Francis Verlag | 2016