D2 TPred : Discontinuous Dependency for Trajectory Prediction under Traffic Lights

How was the data collected?

The data in VTP-TL comes from at urban intersections with traffic lights is used to predict vehicles trajectory in different times of day and provides a broad range of real-world driving scenarios. We use drones to hover at 70 to 120 meters above the traffic intersections, as statically as possible, to record vehicle trajectories passing through the area with a bird’s-eye view in the daytime of the non-rush hours, rush hours, and the evening.

Where was the data collected?

We choose 3 different traffic intersections, including crossroad, T-junction, and roundabout scenarios. In these scenario, they own the different number of roads and traffic lights, and cause to different movement behaviors for vehicles.

Summary of the Dataset

In the VTP-TL dataset, we have collected data from 3 different categories of traffic scenarios using drones. The summary of the data is listed in the following table.

Included Materials

For the 3 recording scenarios, we include 2 files for each scenarios:

1. The sample of video clips (xxx.mp4)
2. Recorded vehicle trajectory file (xxx.txt) where, we provide trajectories information in pixel.

Recorded Vehicle Trajectory files (xxx.txt)

F_id: column 1. For each agent (per Agent_id), frame_id represents the frames the agent appears in the video.
A_id: column 2. For each xxx.txt file, the Agent_id starts from 0, and represent the ID of the agent.
x: column 3, the x position of the agent at each frame. The unit is pixel.
y: column 4, the y position of the agent at each frame. The unit is pixel.
Lane_id: column 5, For each xxx.txt file, the Lane_id starts from 0, and represent the ID of the traffic lane.
pa: column 6, For each xxx.txt file, the inperception is set as 0 or 1, and represent whether vehicle locates in the influencing area of traffic light.
f: column 7, For each xxx.txt file, the isfirstobj is set as 0 or 1, and represent whether vehicle is the first agent in the influencing area of traffic light.
Lig_id: column 8, For each xxx.txt file, the Lig_id starts from 0, and represent the ID of the traffic light.
ls: column 9, For each xxx.txt file, the Ls is set as 0, 1 and 2, and represents the state of traffic light.
mb: column 10, For each xxx.txt file, the Mb is set as 0, 1 and 2, and represents the movement behaviors of vehicle.
lt: column 11, For each xxx.txt file, the Ldurtime represents the durtime of traffic light.

Example: