Situation-based multi-target detection and tracking with laserscanner in outdoor semi-structured environment

This paper addresses the development of an anti-collision system (ACS) based on a laserscanner, for low speed vehicles running in cybercars scenarios. The ACS core is a multi-target detection and tracking system (MTDATS), which is able to classify several kind of objects and can be easily expanded to detect new ones. The MTDATS is composed by five modules: 1) scan segmentation; 2) situation based information integration; 3) object classification using a suitable voting scheme of several object properties; 4) object tracking using a Kalman filter that takes the object type to increase the tracking performance into account; 5) and a database with the objects being tracked at each interval of data processing. For each database object, the time to collision with the vehicle is computed. The worst case time-to-collision and the correspondent predicted impact point on the vehicle are sent to the path-following controller, which using this information provides collision avoidance behaviour.