In order to overcome the problem that the boundaries cannot be accurately detected in unstructured roads

an unstructured road detection method based on adaptive road model is proposed. The algorithm extracts the region of interest（ Ro I） according to the gray feature of the unstructured road

and uses the HSV space map to segment the region of interest with the two-dimensional Otsu algorithm

and then the road boundary points can be extracted. Subsequently least square method or random sample consensus（ RANSAC） algorithm is used to perform boundary points fitting operation

which is depended on different road models. The experimental results show that the method can be applied not only to straight roads

but also to curved roads

and it has good robustness to roads affected by shadows and road with unclear boundaries.