Video Vehicle Detector Verification System (V2DVS) operators manual and project final report.
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Video Vehicle Detector Verification System (V2DVS) operators manual and project final report.

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  • Alternative Title:
    Upgrade the Video Vehicle Detector Verification System (V2DVS;Video Vehicle Detector Verification System (V2DVS) operator's manual and project final report;
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  • Abstract:
    The accurate detection of the presence, speed and/or length of vehicles on roadways is recognized as critical for

    effective roadway congestion management and safety. Vehicle presence sensors are commonly used for traffic

    volume measurement and control of signalized intersections and ramp meters. In addition, vehicle speed, either

    measured directly from a “speed trap” or estimated based on vehicle length, and classification from length are

    important for automated incident detection and the characterization and prediction of traffic demand.

    The market has recently seen an increasing number of out-of-pavement and wireless in-pavement detection

    systems. These systems are easier to install and maintain than conventional inductive loop detectors, but there

    is evidence from pilot installations, however anecdotal, that they have different detection characteristics and can

    yield different results. Due to situations including lane-changing, high ground clearance, trailers and occlusion,

    detectors will occasionally fail to detect, falsely detect or multiply detect individual vehicles. These errors tend to

    cancel each other when detection data is aggregated into bins, as in common practice. Non-aggregated (i.e.

    individual vehicle) data is needed on how these detectors perform in different situations in order to optimally

    specify equipment for certain detection requirements and environments. There was previously no way to compile

    individual detection data or quantify detection errors without manually comparing each individual detection event

    record to video ground-truth, which is a labor-intensive process that is practically impossible for large datasets.

    Selected out-of-pavement and wireless in-pavement detection systems, along with duplex inductive loop

    detectors, are installed on Route 405 in the city of Irvine to detect the passage of each northbound vehicle.

    Installed at the same site is the Video Vehicle Detector Verification System (V2DVS) that automates the

    collection and accuracy assessment of output data from all detectors under test.

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