Algorithms for calibrating roadside traffic cameras and estimating mean vehicle speed

In this paper we present a simplified model for traffic management cameras and a calibration method based on a known distance along the road. We then describe how to estimate this interval from the images using an autocorrelation method applied to lane marker features. Assuming the camera has been calibrated and the vehicle lanes have been identified, we also present a method to track a group of vehicles in a lane and estimate the space mean speed using a cross-correlation technique. The algorithm is appropriate for building a speed sensor with fine time resolution (i.e., 200 ms); 20-second averages are shown to be equivalent to data from two different inductance loops. The results for several test cases show that the speed estimation method performs well under a variety of challenging weather, lighting, and traffic conditions.