Video sequences of road and traffic scenes are currently used for various purposes, such as studies of the traffic character of freeways. The task here is to automatically estimate vehicle speed from video sequences, acquired with a downward tilted camera from a bridge. Assuming that the studied road segment is planar and straight, the vanishing point in the road direction is extracted automati-cally by exploiting lane demarcations. Thus, the projective distortion of the road surface can be re-moved allowing affine rectification. Consequently, given one known ground distance along the road axis, 1D measurement of vehicle position in the correctly scaled road direction is possible. Vehicles are automatically detected and tracked along frames. First, the background image (the empty road) is created from several frames by an iterative per channel exclusion of outlying colour values based on thresholding. Next, the subtraction of the background image from the current frame is binarized, and morphological filters are employed for vehicle clustering. At the lowest part of vehicle clusters a window is defined for normalised cross-correlation among frames to allow vehicle tracking. The reference data for vehicle speed came from rigorous 2D projective transformation based on control points (which had been previously evaluated against GPS measurements). Compared to these, our automatic approach gave a very satisfactory estimated accuracy in vehicle speed of about ±3 km/h.