Development of preceding vehicle recognition algorithm for lead vehicle of autonomous platooning system based on multi sensor fusion and digital map

We have been developing an autonomous platooning system of heavy trucks aimed at enhancing its energy efficiency by shortening headway distance between trucks. In this paper, we focused on developing a forward environment perception method for fully automated lead vehicle of the autonomous platooning system. To percept the forward environment of autonomous platooning system, it is important to robustly detect obstacles from distance. Additionally, it is also important to recognize which lane the detected obstacles exist. In this research, the obstacles are detected robustly and precisely based on multi-sensor fusion scheme between LIDAR and RADAR. Moreover, the lanes, where the obstacles exist, are recognized by using digital map based on lane marker detection.