Fast road boundary detection and tracking in occupancy grids from laser scans

This paper presents a novel method to extract and track road boundaries in a temporal sequence of occupancy grids collected from a moving vehicle that is equipped with a laser scanner. The road boundaries are represented as circular arcs, where it is assumed that the boundaries are parallel to the driving direction. In order to find the optimal parameters of the circular arcs, first a one-dimensional optimization problem over the curvature is solved. Second, based on the optimal curvature, the optimal offset, i.e., radius, is determined. In order to obtain robust and smooth road boundary estimates, we suggest to employ a tracking algorithm, i.e., the Integrated Probabilistic Data Association (IPDA). The overall method is evaluated with real-world data from a highway scenario and compared with two state-of-the-art methods.