Model-Based Lane Detection and Lane Following for Intelligent Vehicles

A robust model-based lane detection and tracking algorithm has been studied. Initially, Dynamic programming (DP) and Hough transform are employed to detect lane boundaries. The Dynamic programming is known to be a powerful algorithm for optimal path finding on a cost field. Utilizing the intensities of edge image as costs of the DP, most likely road boundaries are obtained in this paper. An improved Hough Transform is applied to detect practically useful road boundaries with straight line segments. In the following stage, based on the prior information of lane boundaries in the detection procedure, the road boundary region has been obtained. A linear lane model has been employed with an energy function in tracking algorithm. Experiment results in inter-frame processing describe the proposed method can fit for real condition on expressway.