A multiple-sensor multiple-target tracking approach for the autotaxi system

The Autotaxi system is a safety critical sensor system that is being specially developed to perform the sensing required for an autonomous vehicle to drive safely along a dedicated paved guideway and to avoid collision. Therefore, the host vehicle is equipped with a set of sensors used to detect and track any object of interest in the field of view. In this work a multiple-sensor multiple-target tracking (MS-MTT) approach for the Autotaxi system is proposed. A decentralized MS-MTT system is considered for this application. It consists of two basic components: sensor-level tracking and multiple-sensor track fuser or fusion centre. Each sensor in the sensor-level is considered as an intelligent sensor which generates it own track file. Thus, the task of the fusion centre is to combine or fuse the local track files to produce a more accurate and reliable single system track file. This is performed in three stages: data alignment, track-to-track association, and track fusion.