Occupancy grid map estimation method using roadside sensor for cooperative automated driving

Abstract

In recent years, cooperative automated driving, which shares information from in-vehicle and roadside sensors via communication technology, has gained attention. To share sensor information, methods using occupancy grid maps (OGMs) have been explored. However, when using roadside sensors to estimate OGMs, which are installed at higher elevations than in-vehicle sensors, the challenge arises of being unable to accurately recognize the road environment due to increased undetected areas. This study proposed a method to estimate OGMs using roadside LiDAR sensors, considering undetected areas. And the proposed method was demonstrated to accurately reflect the road environment in OGMs.