To deal with different road conditions and environment situations

a hierarchical vanishing point detection method based on holistic image features is proposed. Four road types are classified based on an abstracted holistic road feature

which also coarsely locates the road. After classification

the lane or edges in a specific scale is chosen for the line-segment-detection or region segmentation

and for the voting of the intersection point. Additionally

an inverse projective image or region entropy verifies the result. Interference of vehicles and shadows are eliminated during image pre-processing to further improved the accuracy. Our results show that the hierarchical method can choose the right road type and robustly detect the vanishing point under complex road scenes in real time

achieving an improvement for accuracy and efficiency at 37.5% and 20% compared to the state-of-the-art method based on intrinsic line orientation and color texture properties.