2023 年 62 巻 3 号 p. 114-118
Automated vehicle technology is rapidly growing with the aim of practical applications as the next generation of transportation systems. In order to achieve fully-automated driving on public roads, a common approach is to implement digital map based robust perception and decision-making systems. It is a challenging task of self-localization to stably estimate ego-vehicle position with decimeter-level accuracy even under adverse conditions such as rain and snow. This paper describes overviews of the digital map generation based on SLAM technology and self-localization technology based on map matching for robust urban automated driving.