Vehicle position estimation based on road area detection and image registration

This paper describes the development of a new localization method using a simple 2D map. The general method for localization using a 2D map is to match between the boundary line on the 2D map and the detected boundaries in the real world, i.e. lane markers, walls of building, or curbs. It is necessary to create a differential process in order to detect boundary lines of the road. If these methods try to detect small changes, the false-detection rate increases due to enhanced noises; if they try to reduce the effect of noise, boundary lines are misdetected. The estimation result of this method deteriorates drastically if the false-detection or misdetection of the boundary line occurs. We propose the new localization method based on the road area detection. First, the road map is extracted from the boundary lines on a 2D map. Next, the road plane image is made by the road area detected using LiDAR in the real world. Finally, the road map and the road plane image are matched by image registration. We confirmed that the proposed method have accurate estimation performance with several noise and low-cost calculation from the simulation. And we conducted the performance validation of proposed method in the real world. As a result, we confirmed the same tendency as simulation results.