Abstract: Road detection is one of the most important technologies in the vision-based intelligent navigation system. In this study, a fast and robust unstructured road detection method is proposed. In order to ensure the robustness of the algorithm, BP (Back Propagation) Neural Network is employed to learn the color features from a set of sample of both road region and off-road region and then to classify a new pixel. And a heuristic fitting approach based on Conditional Destiny Propagation is employed to fit the boundaries of the lanes with the Least Square Method. Taking the advantages of these properties, the proposed implementation works out with high performance of detection in various environments. Meanwhile it is robust against noise, shadows and illumination variations.