Robust and accurate tracking and localization of road users like pedestrians and cyclists is crucial to ensure safe and effective navigation of Autonomous Vehicles (AVs), particularly so in urban driving scenarios with complex vehicle-pedestrian interactions. Existing datasets that are useful to investigate vehicle-pedestrian interactions are mostly image-centric and thus vulnerable to vision failures. In this paper, we investigate Ultra-wideband (UWB) as an additional modality for road users' localization to enable a better understanding of vehicle-pedestrian interactions. We present WiDEVIEW, the first multimodal dataset that integrates LiDAR, three RGB cameras, GPS/IMU, and UWB sensors for capturing vehicle-pedestrian interactions in an urban autonomous driving scenario. Ground truth image annotations are provided in the form of 2D bounding boxes and the dataset is evaluated on standard 2D object detection and tracking algorithms. The feasibility of UWB is evaluated for typical traffic scenarios in both line-of-sight and non-line-of-sight conditions using LiDAR as ground truth. We establish that UWB range data has comparable accuracy with LiDAR with an error of 0.19 meters and reliable anchor-tag range data for up to 40 meters in line-of-sight conditions. UWB performance for non-line-of-sight conditions is subjective to the nature of the obstruction (trees vs. buildings). Further, we provide a qualitative analysis of UWB performance for scenarios susceptible to intermittent vision failures. The dataset can be downloaded via https://github.com/unmannedlab/UWB_Dataset.

翻译：鲁棒且精确地追踪和定位行人、骑行等道路使用者，对于确保自动驾驶汽车（AV）安全高效的导航至关重要，尤其是在城市驾驶场景中复杂的车辆-行人交互情境下。现有用于研究车辆-行人交互的数据集大多以图像为中心，因而易受视觉故障影响。本文探索将超宽带技术（UWB）作为道路使用者定位的补充模态，以增强对车辆-行人交互的理解。我们提出WiDEVIEW，这是首个融合激光雷达（LiDAR）、三个RGB摄像头、GPS/IMU及UWB传感器的多模态数据集，用于捕捉城市自动驾驶场景中的车辆-行人交互。数据集以二维边界框形式提供真值图像标注，并采用标准二维目标检测与跟踪算法进行评估。利用LiDAR作为真值，在视距与非视距条件下评估了UWB在典型交通场景中的可行性。结果表明：在视距条件下，UWB测距数据与LiDAR精度相当（误差0.19米），且锚点-标签测距数据在40米范围内稳定可靠；非视距条件下UWB性能受遮挡物性质（树木或建筑物）影响。此外，我们对易发生间歇性视觉故障场景下的UWB性能进行了定性分析。数据集可通过https://github.com/unmannedlab/UWB_Dataset下载。