Localization of Autonomous Vehicles in Tunnels Based on Roadside Multi-Sensor Fusion

Tunnels present significant challenges for the navigation and localization of autonomous vehicles due to the lack of GNSS signals and the presence of uniform scene textures. Current cooperative positioning strategies, which rely on RSS and ToF, are less effective in tunnel environments due to the unique electromagnetic conditions. To address this issue, a novel Vehicle-to-Infrastructure (V2I) cooperative localization methodology is introduced. The system comprises a roadside subsystem and a vehicle-side subsystem. In the roadside subsystem, data from multiple sensors is collected to calculate the vehicle's position. This information is then transmitted to the vehicle-side subsystem via V2I communication, where it is fused with onboard module data. A highly effective co-location process for the vehicle-side subsystem is proposed, along with an exemplary algorithm. This process resolves issues related to data dimension inconsistency, delay, and pose fusion commonly encountered during co-location. Furthermore, a comprehensive investigation and analysis explores factors that may impact positioning performance. This meticulous examination enhances the understanding of the framework and reveals its limitations.