主数据集为一个304 MB的轨迹数据文件（I90_94_stationary_final.csv），包含城市环境中高速公路上小型与大型L2级自动驾驶车辆及非自动驾驶车辆的位置、速度与加速度数据。配套文件包括六次独立数据采集‘运行’（Runs）的航拍参考图像（文件名格式为I90_94_Stationary_Run_X_ref_image.png，其中X取值为1至6）；以及每次‘运行’对应的中心线文件（I-90-stationary-Run_X-geometry-with-ramps.csv）。各中心线文件中提供了以米为单位的x、y坐标，用于标记各车道中心线；参考图像原点位于左上角。此外，各中心线文件中均包含一个指示变量，用于标识各车道所属路段类型：0=无匝道段，1=入口匝道段，2=出口匝道段，3=交织段。各列标题所附数字为对应车道分配的数值ID（详见《TGSIM – 中心线数据字典 – I90_94Stationary.csv》）。该数据集利用上述中心线文件定义了六条北行车道；根据具体‘运行’，共使用十二个不同数值ID（1、2、3、4、5、6、10、11、12、13、14、15）表示这六条北行车道。将感兴趣车道映射至轨迹数据集中所引用数值车道ID的图像存于‘Annotation on Regions.zip’文件夹中。各数据采集‘运行’的参考图像中，以红色文字标注了对应车道ID（文件名格式为I90_94_Stationary_Run_X_ref_image_annotated.jpg，其中X取值为1至6）。本数据集系‘第三代仿真数据（TGSIM）：自动驾驶系统对人类行为影响的深入研究’项目的一部分。

The main dataset is a 304 MB file of trajectory data (I90_94_stationary_final.csv) that contains position, speed, and acceleration data for small and large automated (L2) vehicles and non-automated vehicles on a highway in an urban environment. Supporting files include aerial reference images for six distinct data collection “Runs” (I90_94_Stationary_Run_X_ref_image.png, where X equals 1, 2, 3, 4, 5, and 6). Associated centerline files are also provided for each “Run” (I-90-stationary-Run_X-geometry-with-ramps.csv). In each centerline file, x and y coordinates (in meters) marking each lane centerline are provided. The origin point of the reference image is located at the top left corner. Additionally, in each centerline file, an indicator variable is used for each lane to define the following types of road sections: 0=no ramp, 1=on-ramps, 2=off-ramps, and 3=weaving segments. The number attached to each column header is the numerical ID assigned for the specific lane (see “TGSIM – Centerline Data Dictionary – I90_94Stationary.csv” for more details). The dataset defines six northbound lanes using these centerline files. Twelve different numerical IDs are used to define the six northbound lanes (1, 2, 3, 4, 5, 6, 10, 11, 12, 13, 14, and 15) depending on the run. Images that map the lanes of interest to the numerical lane IDs referenced in the trajectory dataset are stored in the folder titled “Annotation on Regions.zip”. Lane IDs are provided in the reference images in red text for each data collection run (I90_94_Stationary_Run_X_ref_image_annotated.jpg, where X equals 1, 2, 3, 4, 5, and 6). This dataset was collected as part of the Third Generation Simulation Data (TGSIM): A Closer Look at the Impacts of Automated Driving Systems on Human Behavior project. During the project, six trajectory datasets capable of characterizing human-automated vehicle interactions under a diverse set of scenarios in highway and city environments were collected and processed. For more information, see the project report found here: https://rosap.ntl.bts.gov/view/dot/74647. This dataset, which is one of the six collected as part of the TGSIM project, contains data collected using the fixed location aerial videography approach with one high-resolution 8K camera mounted on a helicopter hovering over a short segment of I-94 focusing on the merge and diverge points in Chicago, IL. The altitude of the helicopter (approximately 213 meters) enabled the camera to capture 1.3 km of highway driving and a major weaving section in each direction (where I-90 and I-94 diverge in the northbound direction and merge in the southbound direction). The segment has two off-ramps and two on-ramps in the northbound direction. All roads have 88 kph (55 mph) speed limits. The camera captured footage during the evening rush hour (4:00 PM-6:00 PM CT) on a cloudy day. During this period, two SAE Level 2 ADAS-equipped vehicles drove through the segment, entering the northbound direction upstream of the target section, exiting the target section on the right through I-94, and attempting to perform a total of three lane-changing maneuvers (if safe to do so). These vehicles are indicated in the dataset. As part of this dataset, the following files were provided: <ul><li>I90_94_stationary_final.csv contains the numerical data to be used for analysis that includes vehicle level trajectory data at every 0.1 second. Vehicle type, width, and length are provided with instantaneous location, speed, and acceleration data. All distance measurements (width, length, location) were converted from pixels to meters using the following conversion factor: 1 pixel = 0.3-meter conversion.</li> <li>I90_94_Stationary_Run_X_ref_image.png are the aerial reference images that define the geographic region for each run X.</li> <li>I-90-stationary-Run_X-geometry-with-ramps.csv contain the coordinates that define the lane centerlines for each Run X. The "x" and "y" columns represent the horizontal and ve