The proposed research aims at developing an integrated and a most efficient travel management model to generate a smart transportation system by detecting traffic data at signalized intersections. This study will utilize an emerging data acquiring technique called “floating car data (FCD)”. Even if there were several past studies on using FCD, but those have been limited into obtaining traffic related information parameters (such as speed, etc.). But this study will focus on using FCD technology to obtain information on vehicular left turn movement at different levels of congestion at protected only left turn signal. Since left turning movements are considered as the points of having most of the conflicts involving both vehicles and pedestrians this research emphasizes on collecting traffic data for protected only left turning vehicular movements. Therefore, using the vehicular performance information during traffic jam, a most effective protected left turn signal timing can be regulated providing faster and safer left turning movement. This research will develop an integrated mathematical model based on the probabilistic approach at a signal focusing on left turning traffic movement. Driver behavior can also be specifically studied during real-time information relay on congestion. This approach can be applied for congestion relief during peak hour travels as well as in the events of accidents in local roads.


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    Titel :

    Efficient Left Turn Movements at Signalized Intersections by Applying Floating Car Data (FCD) Technology


    Beteiligte:

    Kongress:

    International Conference on Transportation and Development 2019 ; 2019 ; Alexandria, Virginia



    Erscheinungsdatum :

    2019-08-28




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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