构建城市场景下车路协同多传感器数据集，支持智能交通研究
UrbanV2X: A Multisensory Vehicle-Infrastructure Dataset for Cooperative Navigation in Urban Areas
- 车与路边设施同步采集多源传感器数据
- 包含400+小时高清影像、激光雷达与厘米级定位信息
- 适合自动驾驶、车路协同算法研发者使用
由于单个自动驾驶车辆存在感知局限，蜂窝车联网（C-V2X）技术通过共享传感器信息，为实现完全自动驾驶提供了新路径。然而，支撑复杂城市环境中车路协同导航的真实世界数据集仍十分稀缺。为此，我们提出UrbanV2X，一个在港珠澳大桥周边C-V2X测试床中，从车辆与路边基础设施采集的综合性多感官数据集，旨在支持密集城市区域智慧出行应用的研究。车载平台同步获取多个工业级摄像头、激光雷达、4D雷达、超宽带（UWB）、惯性测量单元（IMU）以及高精度GNSS-RTK/INS导航系统数据；路边设施则提供激光雷达、GNSS和UWB测量。整个车-路系统采用精确时间协议（PTP）实现同步，并提供传感器标定数据。我们还对多种导航算法进行了基准测试，以评估协同数据性能。该数据集已公开发布于https://polyu-taslab.github.io/UrbanV2X/。
原文摘要 · Abstract (English)
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/.
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