Multi-Lane Visual Perception for Lane Departure Warning Systems

This paper presents a Road Detection and Tracking algorithm for Lane Departure Warning Systems. An inverse perspective transformation gives a bird-eye view of the road, where longitudinal road markings are detected by exploration of horizontal gradient, looking for a road marking model. Next, a parabolic lane model is fitted to road markings and tracked through a particle filter. The right and left lane boundaries are classified in three types (solid, broken or merge lane boundaries), through a Fourier analysis, and adjacent lanes are searched when broken or merge lines are detected. This gives the system the ability to automatically detect the number and type of road lanes. This ability allows to tell the difference between allowed and forbidden manoeuvres, such as crossing a solid line, and it is used by the lane departure warning system. Despite of its importance, lane boundary classification has been seldom considered in previous works. A Lane Departure Warning System launches an acoustic signal when a lane departure is detected. Warnings are suppressed when the blinkers are enabled, or when the vehicle is crossing a solid line regardless of the state of the blinkers.