ASSESSMENT OF CAR COLLABORATIVE POSITIONING WITH UWB AND VISION
Keywords: Collaborative positioning, UWB, Vision, Extended Kalman filter, Deep Learning
Abstract. During the last decades the role of positioning and navigation systems is drastically changed in the everyday life of common people, influencing people behavior even multiple times each day. One of the most common applications of this kind of systems is that of terrestrial vehicle navigation: the use of GPS in the automotive navigation sector started thirty years ago, and, nowadays, it commonly assists drivers in reaching most of their non-standard destinations. Despite the popularity of global navigation satellite systems (GNSS), their usability is quite limited in certain working conditions, such as in urban canyons, in tunnels and indoors. While the latter case is typically not particularly interesting for the automotive sector, the first two scenarios represent important cases of interest for automotive navigation. In addition to the market request for increasing the usability of navigation systems on consumer devices, the recent increasing eagerness for autonomous driving is also attracting a lot of researchers’ attention on the development of alternative positioning systems, able to compensate for the unavailability or unreliability of GNSS. In accordance with the motivations mentioned above, this paper focuses on the development of a positioning system based on collaborative positioning between vehicles with UltraWide-Band devices and vision. To be more specific, this work focuses on assessing the performance of the developed system in successfully accomplishing three tasks, associated to different levels of gathered information: 1) assessing distance between vehicles, 2) determining the vehicle relative positions, 3) estimating the absolute car positions. The obtained results show that a) UWB can be reliably used (error of few decimeters error) to assess distances when vehicles are relatively close to each other (e.g. less than 40 m), b) the combination of UWB and vision allows to obtain good results in the computation of relative positions between vehicles, c) UWB-based collaborative positioning can be used for determining the absolute vehicle positions if a sufficient number of UWB range measurements can be ensured (sub-meter error for vehicles connected with a static UWB infrastructure, whereas error at meter level for those exploiting only vehicle-to-vehicle UWB communications).