The purpose of this research is to demonstrate the feasibility of an automated system for medium-duration, deployable, in-the-field vehicle classification. Most temporary surveys of vehicle traffic today are done manually, typically with human observers recording traffic. Instead, we plan to employ a network of traffic sensors (NOTS), a number of small, low-cost computer nodes, each with a portable inductive loop sensor. This system can provide accurate measurements for longer duration and lower cost than is possible today. Our system will allow medium-term surveys, targeting 7-14 days. For temporary surveys like these it is essential that the system be easily deployable, not requiring investment in permanent, in-roadway sensors, but instead capable of being deployed by one or a few people in a few hours. We look at accurate vehicle classification and compare our results to ground truth taken from off-line analysis of videos, and to on-line human observations.


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    Titel :

    Sensor for Unexpected Roadway Events: Field Trials (SURE-FT)


    Beteiligte:
    J. Heidemann (Autor:in) / G. Guiliano (Autor:in) / U. Park (Autor:in) / F. Silva (Autor:in) / M. Hu (Autor:in)

    Erscheinungsdatum :

    2008


    Format / Umfang :

    29 pages


    Medientyp :

    Report


    Format :

    Keine Angabe


    Sprache :

    Englisch




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