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Open Access Publications from the University of California

Vehicle Reidentification and Travel Measurements on Congested Freeways


This paper presents a vehicle reidentification algorithm for consecutive detector stations on a freeway, whereby a vehicle measurement made at a downstream detector station is matched with the vehicle's corresponding measurement at an upstream station. The method is illustrated using measured vehicle lengths from paired loop detector speed traps. Where speed traps are quite common, often placed at half mile spacings or less on urban freeways. In conventional operation, these detectors only monitor traffic conditions over the loops, leaving most of the freeway unmonitored. By taking the difference in known arrival times for a matched vehicle, it is possible to measure true link travel time and thus, quantify conditions between detector stations. This approach is significant because no one has attempted to use the existing detector infrastructure to match vehicle measurements between detector stations. The results of this work suggest that it is possible to extract a sufficient number of vehicle matches for traffic surveillance applications, while accepting few, if any, false positives. Thus, with the new algorithm, it will be possible to evaluate applications of travel time data without deploying new detector hardware. Keywords: traffic surveillance, loop detectors, travel time measurement, vehicle reidentification

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