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Traffic surveillance is an important issue in Intelligent TransportationSystems(ITS). In this paper, we propose a novel surveillance system to detectand track vehicles using ubiquitously deployed magnetic sensors. That is,multiple magnetic sensors, mounted roadside and along lane boundary lines, areused to track various vehicles. Real-time vehicle detection data are reportedfrom magnetic sensors, collected into data center via base stations, andprocessed to depict vehicle trajectories including vehicle position, timestamp,speed and type. We first define a vehicle trajectory tracking problem. We thenpropose a graph-based data association algorithm to track each detectedvehicle, and design a related online algorithm framework respectively. Wefinally validate the performance via both experimental simulation andreal-world road test. The experimental results demonstrate that the proposedsolution provides a cost-effective solution to capture the driving status ofvehicles and on that basis form various traffic safety and efficiencyapplications.

Vehicle Trajectory Tracking Through Magnetic Sensors: A Case Study of Two-lane Road