Ford Autonomous Vehicle

We present a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles at different days and times during 2017-18. The vehicles were manually driven on a route in Michigan that included a mix of driving scenarios including the Detroit Airport, freeways, city-centers, university campus and suburban neighborhood. We present the seasonal variation in weather, lighting, construction and traffic conditions experienced in dynamic urban environments. This dataset can help design robust algorithms for autonomous vehicles and multi-agent systems. Each log in the dataset is time-stamped and contains raw data from all the sensors, calibration values, pose trajectory, ground truth pose, and 3D maps. All data is available in Rosbag format that can be visualized, modified and applied using the open source Robot Operating System (ROS). The dataset contains full resolution time stamped data from the following sensors: The dataset also includes: The vehicles traversed an average route of 66 km in Michigan that included a mix of driving scenarios such as the Detroit Airport, freeways, city-centers, university campus and suburban neighbourhoods, etc. Each vehicle used in this data collection is a Ford Fusion outfitted with an Applanix POS-LV GNSS system, four HDL-32E Velodyne 3D-lidar scanners, 6 Point Grey 1.3 MP Cameras arranged on the rooftop for 360-degree coverage and 1 Pointgrey 5 MP camera mounted behind the windshield for the forward field of view. We present the seasonal variation in weather, lighting, construction and traffic conditions experienced in dynamic urban environments.

本研究提出了一款具有挑战性的多智能体季节性数据集，该数据集由福特（Ford）自动驾驶车辆车队于2017至2018年间的不同日期与时段采集得到。参与采集的车辆均为人工驾驶，行驶路线位于密歇根州境内，涵盖多种驾驶场景：底特律机场、高速公路、城市中心、大学校园以及郊区居民区等。本数据集展现了动态城市环境中所经历的天气、光照、道路施工以及交通状况的季节性变化特征。该数据集可用于辅助研发面向自动驾驶车辆与多智能体系统的鲁棒算法。数据集中的每条日志均带有时间戳，包含所有传感器的原始数据、标定参数、位姿轨迹、真值位姿以及三维地图。所有数据均采用Rosbag格式存储，可通过开源机器人操作系统（Robot Operating System，ROS）进行可视化、修改与应用。本数据集包含来自以下传感器的全分辨率带时间戳数据：本数据集还包含以下内容：采集车辆的平均行驶路线长度为66公里，行驶区域同样位于密歇根州境内，涵盖底特律机场、高速公路、城市中心、大学校园以及郊区居民区等多种驾驶场景。本次数据采集所用车辆均为福特Fusion，搭载的设备包括：Applanix POS-LV GNSS系统、4台HDL-32E型Velodyne三维激光扫描仪、6台布置于车顶以实现360°覆盖的Point Grey 1.3 MP相机，以及1台安装于挡风玻璃后方以获取前向视野的Pointgrey 5 MP相机。本数据集展现了动态城市环境中所经历的天气、光照、道路施工以及交通状况的季节性变化特征。