In urban road systems, it is a challenging task to investigate traffic status of all intersections due to the scarce distribution of road surveillance cameras. Previous research mostly focuses on how to use historical data of camera-equipped intersections to infer their future traffic statuses. However, as far as we know, there does not exist an effective algorithm to infer the real-time traffic statuses of those camera- free intersections by using the traffic information from some other road video cameras in urban road system. In this paper, we first study the spatial- temporal variation characteristics of urban traffic flows from a macroscopic view, including turning ratio models and traveling time models of individual road segments. And then we build a novel traffic impact tree model to calculate the real-time traffic volume for specific camera-free intersections. We evaluate our solutions on real-world taxicab and road surveillance system data-set. The experimental results show that our proposed method outperforms alternative solutions in terms of the accuracy of the reckoned future traffic flow.


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    Titel :

    SmartMonitoring: Reckoning Traffic Statuses of Road System in Real-Time Based on Scarce Road Surveillance Cameras


    Beteiligte:
    Ding, Wenjian (Autor:in) / Wang, Yang (Autor:in) / Guo, Yan (Autor:in) / Chen, Wuji (Autor:in) / Huang, Liusheng (Autor:in) / Liu, Hengchang (Autor:in)


    Erscheinungsdatum :

    01.09.2017


    Format / Umfang :

    1739320 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch