Toward C-V2X Enabled Connected Transportation System: RSU-Based Cooperative Localization Framework for Autonomous Vehicles
Zilin Huang, Sikai Chen, Yuzhuang Pian, Zihao Sheng, Soyoung Ahn, David A. Noyce
Abstract
An accurate and robust localization system is crucial for autonomous vehicles (AVs) to enable safe driving in urban scenes. While existing global navigation satellite system (GNSS)-based methods are effective at locating vehicles in open-sky regions, achieving high-accuracy positioning in urban canyons such as lower layers of multi-layer bridges, streets beside tall buildings, tunnels, etc., remains a challenge. In this paper, we investigate the potential of cellular-vehicle-to-everything (C-V2X) wireless communications in improving the localization performance of AVs under GNSS-denied environments. Specifically, we propose the first roadside unit (RSU)-based cooperative localization framework, namely CV2X-LOCA, that only uses C-V2X channel state information to achieve lane-level positioning accuracy. CV2X-LOCA consists of four key parts: data processing module, coarse positioning module, environment parameter correcting module, and vehicle trajectory filtering module. These modules jointly handle challenges present in dynamic C-V2X networks. Extensive simulation and field experiments show that CV2X-LOCA achieves state-of-the-art performance for vehicle localization even under noisy conditions with high-speed movement and sparse RSU coverage environments. While focusing on AV localization, CV2X-LOCA also can extend to other C-V2X-equipped road users. The study results also provide insights into future investment decisions for transportation agencies regarding deploying RSUs cost-effectively.