Vehicle Top Tag Assisted Vehicle-Road Cooperative Localization For Autonomous Public Buses

Li, Hao, Sun, Yifei, Liu, Bo, Wang, Linbin

arXiv.org Artificial Intelligence 

V ehicle Top Tag Assisted V ehicle-Road Cooperative Localization For Autonomous Public Buses Hao Li, Yifei Sun, Bo Liu, Linbin Wang Abstract -- Accurate vehicle localization is indispensable to autonomous vehicles, but is difficult to realize in complicated application scenarios. Intersection scenarios that suffer from environmental shielding and crowded dynamic objects are especially crucial and challenging. T o handle difficult intersection scenarios, the methodology of vehicle top tag assisted vehicle-road cooperative localization or for short vehicle top tag assisted localization is proposed. The proposed methodology has merits of satisfying all the feasibility, reliability, explainability, society and economy concerns. Concrete solutions of vehicle top tag detection and vehicle top tag localization that instantiate the core part of the proposed methodology are presented. Simulation results are provided to demonstrate effectiveness of the presented solutions. The proposed methodology of vehicle top tag assisted localization also has the potential to be extended to a much wider range of practical applications than our intended ones involving autonomous public buses. State-of-the-art (SOT A) vehicle localization systems normally rely on certain exteroceptive sensors such as GNSS, LiDAR, and vision system (or camera), augmented by proprioceptive sensors such as IMU. Relevant methods can be mainly categorized into GNSS based ones, LiDAR based ones, and vision based ones. These categories of vehicle localization methods are not mutually exclusive.