Vehicle re-identification using wireless magnetic sensors: Algorithm revision, modifications and performance analysis

A vehicle re-identification method based on matching vehicle signatures obtained from wireless magnetic sensors was studied on a single lane loop on-ramp. Different modifications were implemented in the algorithm in order to address limitations of the system when vehicles stop/move slowly over the detectors. The original and modified vehicle re-identification algorithm results were compared against ground truth data obtained from video. Based on the ground truth data it was possible to determine the percentage of vehicles that are re-identified and the number of those vehicles that are misidentified as a function of different algorithm parameters. For this analysis, vehicles were divided into two subsets: i) uncongested and ii) congested. The original method mismatched percentage was around or below 15% for the uncongested vehicle subset and between 20% to 60% for the congested one. With the modified method it was possible to improve the matching rate as well as the accuracy of the matching algorithm. For the uncongested subset, the modified method showed a higher vehicle re-identification rate while maintaining the mismatched percentage around or below 8%. The main improvement over the original method was achieved on the congested vehicle subset, since the number of re-identified vehicles was increased over the original method while keeping the mismatched percentage around or below 14%.