LIDAR-based parking spot search algorithm

Abstract

Autonomous driving considers issues related to a car driving in different real world situations. This work addresses a parking task and describes a new LIDAR-based parking spot search algorithm. The proposed approach was successfully validated in virtual experiments within the Gazebo simulator in a parking area with a perpendicular parking setup. HDBScan, OPTICS, and Gaussian Mixture clustering methods were compared for LIDAR data clustering in the parking spot search task, and the HDBScan clustering demonstrated best prediction and performance results.