In-vehicle Sensing Datasets (e.g., GPS, IMU, and OBD data) In Florida

This data collection and distribution is supported by NSF OAC-1948066. These datasets include a total of 497 trajectory datasets over 2404 km. Each dataset includes 6DOF IMU data (e.g., triaxial acceleration and gyroscope data), GPS data (e.g., latitude, longitude, altitude, speed over ground, the number of connected satellites, Course Over Ground), and OBD data (e.g., rpm, throttle positions, accelerator positions, RPM, air temperature, etc.). The data collection mechanism adopts the asynchronous sampling technologies that make capturing sensor data independent of the recorded signal. Therefore, datasets collected from each sensor are logged in separate files (e.g., time_obd.jsonl, time_gps.jsonl, time_obd.jsonl). By matching the time when each sensor module initiated to log data, one can aggregate/fuse multi-type in-vehicle sensing data.本数据集的采集与分发得到了NSF OAC-1948066项目的支持。本数据集共包含497条轨迹数据集，总覆盖里程达2404千米。每条数据集均包含六自由度惯性测量单元（6DOF IMU）数据（如三轴加速度与陀螺仪数据）、全球定位系统（GPS）数据（如纬度、经度、海拔高度、地面行驶速度、连接卫星数量、对地航向（Course Over Ground））以及车载诊断系统（OBD）数据（如转速、节气门开度、油门踏板位置、进气温度等）。本数据集采用异步采样技术进行采集，该技术可脱离记录信号独立捕获传感器数据，因此各传感器采集的数据将分别存储于独立文件中（例如time_obd.jsonl、time_gps.jsonl、time_obd.jsonl）。通过对齐各传感器模块启动数据记录的时间戳，即可实现多类型车载感知数据的聚合与融合。