A CONCEPT FOR AN AUTOMATED APPROACH OF PUBLIC TRANSPORT VEHICLES TO A BUS STOP
Keywords: Self-Localization, SLAM, Automated Driving, Graph Optimization, High Definition Map, Low-level Data Fusion
Abstract. This paper discusses the current methods for vehicle self-localization and compares previous findings to the use for urban public traffic vehicles. In specific, requirements for autonomous buses approaching a bus stop are defined. An autonomous system capable of reliable vehicle self-localization running in real-time in a city scenario shall be developed in a future work based on this paper. The comparison of filter-based estimation and graph-based optimization techniques shows that the latter suits the the automated approach to a bus stop in an urban environment the best. Based on these findings, a concept for self-localization of public transport vehicles equipped with a variety of imaging sensors with the help of a digital high definition map is presented. A current method is shown and a concept of improving the localization by inferring semantic information into landmark detection by low-level data fusion is provided. Validation and verification of the proposed fusion approach have to be carried out in the future, but a validation scenario is presented in this work.