• Journal of Korean Society of Transportation
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• v.27 no.1
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• pp.179-190
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• 2009

Travel time is one of the most important traffic parameters to evaluate operational performance of freeways. A variety of methods have been proposed to estimate travel times. One feasible solution to estimating travel times is to utilize existing loop detector-based infrastructure since the loops are the most widely deployed detection system in the world. This study proposed a new approach to estimate travel times for freeways. Inductive vehicle signatures extracted from the loop detectors were used to match vehicles from upstream and downstream stations. Ground-truthing was also conducted to systematically evaluate the performance of the proposed algorithm by recognizing individual vehicles captured by video cameras placed at upstream and downstream detection stations. A lexicographic optimization method vehicle reidentification algorithm was developed. Vehicle features representing the characteristics of individual vehicles such as vehicle length and interpolations extracted from the signature were used as inputs of the algorithm. Parameters associated with the signature matching algorithm were calibrated in terms of maximizing correct matching rates. It is expected that the algorithm would be a useful method to estimate freeway link travel times.