ITSC 2025 Paper Abstract

Paper WE-LA-T13.3

QIN, Qijun (Hong Kong Polytechnic University), Zhang, Ziqi (Hong Kong Polytechnic University), Zhong, Yihan (The Hong Kong Polytechnic University.), Huang, Feng (The Hong Kong Polytechnic University), Liu, Xikun (The Hong Kong Polytechnic University), Hu, Runzhi (The Hong Kong Polytechnic University), CHEN, Hang (Hong Kong applied science and technology research institute), HU, Wei (Hong Kong Applied Science and Technology Research Institut), Su, Dongzhe (Hong Kong Applied Science and Technology Research Institute (AST), Zhang, Jun (Nanyang Technological University), Ng, Hoi-Fung (The Hong Kong Polytechnic University), Wen, Weisong (Hong Kong Polytechnic University)

UrbanV2X: A Multisensory Vehicle-Infrastructure Dataset for Cooperative Navigation in Urban Areas

Scheduled for presentation during the Regular Session "S13c-Localization, Mapping, and Sensing for Robust Navigation in ITS" (WE-LA-T13), Wednesday, November 19, 2025, 16:40−17:00, Stradbroke

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 19, 2025

Keywords Infrastructure Requirements for Connected and Automated Vehicles, Sensor Integration and Calibration for Accurate Localization in Dynamic Road Conditions, Integration of Autonomous Vehicles with Public and Private Transport Networks

Abstract

Due to the limitations of a single autonomous vehicle, Cellular Vehicle-to-Everything (C-V2X) technology opens a new window for achieving fully autonomous driving through sensor information sharing. However, real-world datasets supporting vehicle–infrastructure cooperative navigation in complex urban environments remain rare. To address this gap, we present UrbanV2X, a comprehensive multisensory dataset collected from vehicles and roadside infrastructure in the Hong Kong C-V2X testbed, designed to support research on smart mobility applications in dense urban areas. Our onboard platform provides synchronized data from multiple industrial cameras, LiDARs, 4D radar, Ultra-wideband (UWB), IMU, and high-precision GNSS-RTK/INS navigation systems. Meanwhile, our roadside infrastructure provides LiDAR, GNSS, and UWB measurements. The entire vehicle–infrastructure platform is synchronized using the Precision Time Protocol (PTP), with sensor calibration data provided. We also benchmark various navigation algorithms to evaluate the collected cooperative data. The dataset is publicly available at: https://polyu-taslab.github.io/UrbanV2X/.