, Assistant Professor, UMD-Electrical Engineering
Automatic traffic data collection can significantly save labor work and cost compared to manual data collection. The collected traffic data is necessary for traffic simulation and modeling, performance evaluation of the traffic scene, and eventually, (re)design of the traffic scene. Automatic traffic data collection, however, has been one of the challenges in intelligent transportation systems. This project developed a single camera-based video system for automatic traffic data collection for roundabouts and intersections. The system targets roundabouts and intersections because no mature data collection systems exist for these traffic scenes yet, in contrast to highway scenes. The developed system has mainly processing modules. First, the camera is calibrated for the traffic scene of interest and a novel circle-based calibration algorithm is proposed for roundabouts. Second, the system tracks vehicles from the video by incorporating powerful imaging processing techniques and tracking algorithms. Finally, the resulting vehicle trajectories from vehicle tracking are analyzed to extract the interested traffic data, which includes vehicle volume, vehicle speed (including acceleration/de-acceleration behavior), travel time, rejected gaps, accepted gaps, follow-up time, and lane use. Practical tests of the developed system show that it can reliably track vehicles and provide reasonably accurate traffic data in most cases.
- Project number: 2011013
- Start date: 07/2010
- Project status: Completed
- Research area: Transportation Safety and Traffic Flow
Data and modeling, Vision Systems