Abstract
In order to accelerate the social implementation of autonomous driving, it is important to repeat the process of technological development, environmental improvement, and evaluation of social acceptance in a short demonstration cycle. In this study, we present an installation assistance system that automatically calibrates the installation posture of infrastructure sensors to speed up integration of geofenced autonomous driving. The calibration pipeline is composed of multi-point search and iterative closest point. Additionally, we propose grid-based hidden point removal, which improves robustness of the multi-point search while reducing execution time. The proposed algorithm is evaluated with actual infrastructure sensor data.
