Abstract: Road detection and identification are one of the essential problems for vision understanding in autonomous vehide systems. However, it becomes relatively harder with the surrounding conditions such as shadows, asymmetric illumination, and blurry edge information. To enhance the robustness and interference immunity, a Vision Dynamic Mode ling based road detection algorithm was proposed. This method structures camera observation systems on computer vision, and introduces deformablc line model for road geometry description. Based on continuity a dynamic model for the vehicle motion was constructed, which incorporates Particle Filtering into road tracking by parameters estimation and prediction. Besides,likelihood probability combined with road model was utilized to evaluate the fitness with sampled images. Experiments with road images from CMU lab and our system proved the effectiveness and applicability of this algorithm.

Key words: Autonomous vehicle systems,Deformable line model,Dynamic modeling,Particle filtering,Likelihood probability