In this paper, we present a congestion-aware route planning system. First we learn the congestion model based on real data from a fleet of taxis and loop detectors. Using the learned street-level congestion model, we develop a congestion-aware traffic planning system that operates in one of two modes: (1) to achieve the social optimum with respect to travel time over all the drivers in the system or (2) to optimize individual travel times. We evaluate the performance of this system using 10,000+ taxis trips and show that on average our approach improves the total travel time by 15%.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Congestion-aware Traffic Routing System using sensor data


    Beteiligte:
    Aslam, Javed (Autor:in) / Lim, Sejoon (Autor:in) / Rus, Daniela (Autor:in)


    Erscheinungsdatum :

    2012-09-01


    Format / Umfang :

    1663759 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Congestion-aware Routing and Rebalancing of Autonomous Mobility-on-Demand Systems in Mixed Traffic

    Wollenstein-Betech, Salomon / Houshmand, Arian / Salazar, Mauro et al. | IEEE | 2020



    Traffic aware electric vehicle routing

    Basso, Rafael / Lindroth, Peter / Kulcsar, Balazs et al. | IEEE | 2016


    Traffic and congestion free routing for mobile robots

    Rana, Manoj / Gupta, Avdhesh / Singh, R. K. | IEEE | 2015


    A Semi-Cooperative Social Routing System to Reduce Traffic Congestion

    Mohanty, Amit / Zeng, Xiangrui | SAE Technical Papers | 2019