Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
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. However, automatic traffic data collection has been one of the
challenges in Intelligent Transportation Systems (ITS). This project presents the development of a single camerabased
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.
Department of Electrical and Computer Engineering, University of Minnesota Duluth;
Northland Advanced Transportation Systems Research Laboratories, University of Minnesota Duluth
Tang, Hua; Dinh, Hai.
A Tracking-Based Traffic Performance Measurement System for Roundabouts and Intersections.
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota.
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