Aiming at the problem of low lane dete ction accuracy and robustness,which is interrupted by strong light,shadows,non lan e road markings and so on,this paper presents a new algorithm combined with info r mation obtained from roadside structures model and extended Kalman filter (EKF). It detects edge points using adaptive edge detection operator based on scan lines.In view of the roadside model,custom para meter space which is adapted to the algorithm in this paper is established.It can extract all candidate lanes b y voting the edge points.The custom parameter space solves problem of slow processing speed in the traditional Hough transform.According to the roadway geometry and vehicle dynamics,a new driveway model is set up.The paramet ers of driveway information to be evaluated are increased.At the same time,we get the lane inner boundary by using the various constraints of the lane to eliminate interference lines.Tracking a nd estimating coordinate parameters of lane edge points are following that,combined with the extended kalman filter, which can ensure the stability and robustness of the algorithm.The results indicate that the introduced algorithm is robust in vario us complex road scenes and gets good results in time complexity robustness and performance of lane detection.