福特多自动驾驶车辆季节性数据集

福特多自动驾驶车辆季节性数据集是由福特汽车公司收集的，旨在为自动驾驶和多代理系统设计提供挑战性数据。该数据集包含2017-18年间在密歇根州不同时间和天气条件下，平均66公里路线的多种驾驶场景数据。数据集内容丰富，包括来自多种传感器（如3D激光雷达、高清摄像头和GPS/INS系统）的原始数据，以及校准值、姿态轨迹和3D地图。数据集支持使用开源机器人操作系统（ROS）进行可视化、修改和应用，适用于开发适应季节和城市变化的稳健算法。

The Ford Multi-Autonomous Vehicle Seasonal Dataset was collected by Ford Motor Company to provide challenging data for the design of autonomous driving and multi-agent systems. This dataset contains data from various driving scenarios collected along an average 66-kilometer route across Michigan during 2017–2018, under different temporal and weather conditions. The dataset is rich in content, including raw data from multiple sensors such as 3D LiDAR, high-definition cameras, and GPS/INS systems, as well as calibration parameters, pose trajectories, and 3D maps. It supports visualization, modification and application via the open-source Robot Operating System (ROS), and is applicable for developing robust algorithms that adapt to seasonal and urban changes.