Connected vehicle (CV) technology is considered a promising way to collect real-time individual vehicle data such as traffic count, speed, and location. Unlike loop detectors, CV technology can gather data at various points along the road. Such data are essential for traffic management systems. Cost-wise, CV technology is effective because it can be deployed on a large scale with less construction and maintenance costs. However, there are difficulties with the low penetration ratio. Vehicles equipped with sensor devices are generally fewer than vehicles without it. As a result, traffic data retrieved from CVs might not have satisfactory accuracy. Therefore, some estimation algorithms are needed to attain accurate traffic data from the CV data. New innovative techniques need to be developed for CVs. On the other hand, adaptive signal control, considered to be very effective in decreasing delay time from pre-timed plans, is also an important contribution to traffic management systems. With the new source of data, new adaptive signal logic must be developed. Therefore, methodologies that can accurately estimate traffic data from CVs and adaptive signal control logic for traffic data are important to not only traffic management systems but traveler information. These methodologies can play important roles in state-of-the-art research and practical applications.


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    Titel :

    Enhanced Adaptive Signal Control Using Dedicated Short-Range Communications


    Beteiligte:
    Y. Zhang (Autor:in) / K. Tiaprasert (Autor:in)

    Erscheinungsdatum :

    2014


    Format / Umfang :

    84 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch