Road side detection and reconstruction using LIDAR sensor

Road edge localization is key knowledge for automatic road modeling and hence, in the field of autonomous vehicles. In this paper, we investigate the case of road border detection using LIDAR data. The aim is to propose a system recognizing curbs and curb ramps and to reconstruct the missing information in case of occlusion. A prediction/estimation process (inspired by Kalman filter models) has been analyzed. The map of angle deviation to ground normal is considered as a feature set, helping to characterize efficiently curbs while curb ramps and occluded curbs have been handled with the proposed model. Such a method may be used for both road map modeling and driver-assistance systems. A user interface scheme has also been described, providing an effective tool for semi-automatic processing of a large amount of data.