Video systems can locate, identify and track vehicles. A video-based vehicle detection and location method is presented, which exploits the symmetry of vehicles seen from behind. The method can account for a range of symmetry types. These include (1) simple pixel presence in a binary edge image, (2) gray level of the edge pixel, (3) color value of the edge pixel, and (4) connectedness structure of the (binary) pixels around an edge pixel. A fast algorithm for the generation of a symmetry histogram is presented, whose (sufficiently strong) peaks indicate the likely presence and approximate location of a vehicle. The speed of the algorithm results from its data driven nature. Typical results for this algorithm in dense urban traffic are presented, using symmetry type (1). The generalization of the algorithm to skew symmetric images is shown. A potential application of the algorithm to automated roadways and fatigue detection is sketched out. Robustifying extensions in the spirit of (2), (3) and (4) are proposed.