Vehicle tracking system based on videotaping data

The relevance of microscopic traffic simulation models for the analysis of traffic operations and safety is based on their ability to reproduce real time traffic operations at a given location. Accordingly, one of the major steps in the development and application of these models is a good calibration of the model input parameters based on a thorough comparison of simulated and observed vehicle trajectories. Videotaping provides a low cost nonintrusive procedure for capturing individual vehicle operations over time, and as such, provides a useful tool for obtaining observational data for calibration and validation of traffic simulation models. Before videotaped data can be used, however, vehicle tracks or trajectories will need to be extracted from a frame by frame analysis of vehicle progression measurements concerning longitudinal and lateral position, speed, and acceleration over time. A system for tracking moving vehicles is presented that overcomes many of the practical limitations of current videotaping applications usually resulting from traffic and site conditions for the road segment being videotaped. The data extraction algorithm proposed in this paper provides a more flexible (less restrictive) method for videotaping of vehicle in the traffic stream, which attempts to overcome many of the limitations imposed by other more restricting taping methods currently in use. However, the accuracy of the vehicle tracking system needs to be assessed. This necessitates a comparison of individual vehicle trajectories as extracted from the video with the corresponding profiles obtained from baseline ground control points (GCP) referenced values for the same trajectories. This study has two objectives: 1) to introduce and describe the video extraction algorithm that allows vehicle segmentation and tracking, and the computation of traffic parameters from the tracking data, 2) to assess the accuracy of this algorithm with respect to changes in the horizontal viewing angle, and the number and placement of GCP along a given road segment. Preliminary results obtained from a case study shown that the number of GCP and the deflection angle from the perpendicular camera sightline to the roadway have a significant effect on the accuracy of the detected vehicle trajectories. Furthermore, the placement of GCP along the road segment has a significant effect on error, especially as it affects the scale of pixels at the edge of the video angle.