In an effort to improve positioning accuracy in Vehicular Ad hoc NETworks (VANETs), Cooperative Localization (CLoc) has been proposed to fuse relative observations from Vehicle-to-Vehicle (V2V) communication devices with absolute observations from on-board resources such as Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU), and Wheel Speed Sensors (WSSs). In challenging but common tunnel environments, prolonged GNSS outages and unsustainable error accumulation of inertial sensors over time (e.g., gyroscopes) lead to the fast divergence of position estimates. In this paper, we aim at resolving this problem by relying on additional Vehicle-to-Infrastructure (V2I) measurements, making use of RoadSide Units (RSUs) internally to the tunnel. In particular, we explore practical trade-offs between V2I technology (i.e., Impulse Radio — Ultra WideBand (IR-UWB) or ITS-G5) and RSUs deployment costs (i.e., in terms of density and geometric configuration), while improving CLoc absolute accuracy. We also consider combining this solution with lane detection capabilities (e.g., camera-based) and associated road information, while comparing it with a more conventional approach based on GNSS repeaters.
Robust data fusion for cooperative vehicular localization in tunnels
2017 IEEE Intelligent Vehicles Symposium (IV) ; 1372-1377
01.06.2017
695340 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Robust Data Fusion for Cooperative Vehicular Localization in Tunnels
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