Lane detection and tracking based on annealed particle filter

Abstract

This paper describes a highway lane detection and tracking algorithm based on an annealed particle filter; the algorithm combines multiple cues of road images with the annealed particle filter. We build a geometric lane model that can be applied to not only linear roads but also to curved roads. As a first step, preprocessing with a bar filter and color cues is used. In the annealed particle filter step, a K-means algorithm is utilized to measure the weights of the particles. We realize lane detection and tracking using the annealed particle filter which is the main contribution of the current paper. Experimental results show that our method is effective in various road situations. What’s more, the particle number and time cost of the annealed particle filter for each frame is largely reduced compared with those values when using the conventional particle filter.