Abstract: The existing vehicle detection algorithms are subject to many environmental influences, such as different lighting conditions, shadows. To solve these problems, a novel vehicle detection algorithm was proposed. Different from traditional methods, which use motion features to detect vehicles, the proposed method used edge and symmetry features to locate possible vehicles. First, the color-image was preprocessed with grayscaling, smoothing. The vertical gradient components of the image were found using the vertical mask of Sobel operator. Then the candidate areas with sufficient amount of edges were determined by calculating the gradient of edges. After finding possible vehicle candidates, the proposed method measured the prominent vertical symmetry of candidate areas and verified all possible candidates, as symmetry is an important feature of vehicle. The proposed method also figured out the vertical axis of symmetry and the width of the candidate vehicle. Three important restrictions obtained from above steps, including edges, symmetry and width, were used to validate the candidate vehicles. The experimental results show that the proposed algorithm is effective, reliable and robust.