Modern autonomous vehicle perception systems often struggle with occlusions and limited perception range. Previous studies have demonstrated the effectiveness of cooperative perception in extending the perception range and overcoming occlusions, thereby enhancing the safety of autonomous driving. In recent years, a series of cooperative perception datasets have emerged; however, these datasets primarily focus on cameras and LiDAR, neglecting 4D Radar, a sensor used in single-vehicle autonomous driving to provide robust perception in adverse weather conditions. In this paper, to bridge the gap created by the absence of 4D Radar datasets in cooperative perception, we present V2X-Radar, the first large-scale, real-world multi-modal dataset featuring 4D Radar. V2X-Radar dataset is collected using a connected vehicle platform and an intelligent roadside unit equipped with 4D Radar, LiDAR, and multi-view cameras. The collected data encompasses sunny and rainy weather conditions, spanning daytime, dusk, and nighttime, as well as various typical challenging scenarios. The dataset consists of 20K LiDAR frames, 40K camera images, and 20K 4D Radar data, including 350K annotated boxes across five categories. To support various research domains, we have established V2X-Radar-C for cooperative perception, V2X-Radar-I for roadside perception, and V2X-Radar-V for single-vehicle perception. Furthermore, we provide comprehensive benchmarks across these three sub-datasets. We will release all datasets and benchmark codebase at https://huggingface.co/datasets/yanglei18/V2X-Radar and https://github.com/yanglei18/V2X-Radar.

翻译：现代自动驾驶车辆感知系统常面临遮挡与感知范围受限的挑战。先前研究已证明协同感知在扩展感知范围、克服遮挡方面的有效性，从而提升自动驾驶安全性。近年来，一系列协同感知数据集相继涌现；然而，这些数据集主要聚焦于相机与激光雷达，忽视了4D雷达——一种在单车自动驾驶中用于恶劣天气条件下提供鲁棒感知的传感器。本文为填补协同感知领域4D雷达数据集的空白，提出了V2X-Radar，首个包含4D雷达的大规模真实世界多模态数据集。V2X-Radar数据集通过网联车辆平台及配备4D雷达、激光雷达与多视角相机的智能路侧单元采集。采集数据涵盖晴雨天气条件，横跨白昼、黄昏与夜间时段，并包含多种典型挑战性场景。数据集包含20K帧激光雷达点云、40K张相机图像及20K组4D雷达数据，涵盖五类目标共计350K个标注边界框。为支持多领域研究，我们建立了面向协同感知的V2X-Radar-C、面向路侧感知的V2X-Radar-I以及面向单车感知的V2X-Radar-V子数据集。此外，我们为这三个子数据集提供了全面的基准测试方案。所有数据集与基准代码库将发布于 https://huggingface.co/datasets/yanglei18/V2X-Radar 与 https://github.com/yanglei18/V2X-Radar。