Skip to content

Latest commit

 

History

History
121 lines (95 loc) · 5.25 KB

dataset_format_description.md

File metadata and controls

121 lines (95 loc) · 5.25 KB
Raw

Dataset Format

This library colects a driving datasets using a hardcoded expert driver navigating towards a goal.

The module used to write the dataset can be seen here

General Structure

A dataset directory should look like the structure below. In the next sections will explain each of one the components described.

<dataset_name>
│   dataset_metadata.json
│
└───episode_00000
│   │   episode_metadata.json
│   │   <Camera1_name>_00000.png
│   │   ...
│   │   <Camera2_name>_00000.png
│   │   ...
│   │   <Lidar_name>_00000.png
│   │   ...
│   │   measurements_00000.json
│   │   ...
└───episode_00001
    │   ...
    │
    ...
Dataset metadata

Each dataset contains a metadata file with the following information:

  • Cameras used.
  • The FOV, and image size for the cameras.
  • The range of the number of cars to be used in each episode.
  • The range of the number of pedestrians to be used in each episode.
  • The percentage of lateral noise.
  • The percentage of longitudinal noise.
  • The set of weathers to be sampled from.
Episode Metadata

Each episode is stored on a different folder. For each collected episode we generate a json file containing its general aspects that are:

  • Number of Pedestrians: the total number of spawned pedestrians.
  • Number of Vehicles: the total number of spawned vehicles.
  • Spawned seed for pedestrians and vehicles: the random seed used for the CARLA object spawning process.
  • Weather: the weather of the episode.

Each episode lasts from 1-5 minutes partitioned in simulation steps of 100 ms. For each step, we store data divided into two different categories, sensor dat stored as PNG images, and measurement data stored as json files.

Sensor Data

All images collected are stored as png. All lidar sensors collected are store as PLY files. The collected sensors are the ones described in the configuration file.

Measurements

Measurements represent all the float data collected for each simulation step. Each measurement is associated with the respective sensor data. The units of the measurements are on SI format, otherwise we specify the format. All measurements are stored in json files and contain the following information:

  • Step Number: the number of the current simulation step, starts at zero and is incremented by one for every simulation step.

  • Game Timestamp: the time that has passed since the simulation has started. Expressed on miliseconds.

  • Position: the world position of the ego-vehicle. It is expressed as a three dimensional vector (x,y,z) in meters.

  • Orientation: the orientation of the vehicle with respect to the world. Expressed as Euler angles (row, pitch and yaw).

  • Acceleration: the acceleration vector of the ego-vehicle with respect to the world.

  • Forward Speed: an scalar expressing the linear forward speed of the vehicle.

  • Intentions: a signal that is proportional to the effect that the dynamic objects on the scene are having on the ego car actions. We use three different intention signals: stopping for pedestrians, stopping for cars and stopping for traffic lights. For example, an intention of 1 for stopping for pedestrian means that the ego car is totally stopped for a pedestrians that is less than 5 meters away. An intention of the same class of 0.5 means that the expert noticed a pedestrians and has reduced its speed to a certain extent. An intention of 0 means there are no pedestrians nearby in the field of view of the expert.

  • High Level Commands: the high level command saying what the ego-vehicle should do in the next intersection: go straight, turn left, turn right, or do not care (the ego vehicle could pick any option). These commands are encoded as an integer number. 2 is do not care, 3 for turn left, 4 for turn right, 5 for go straight.

  • Waypoints: a set containing the 10 future positions of the vehicle.

  • Steering Angle: the current angle of the vehicle's steering wheel. Normalized from -1 to 1

  • Throttle: the current pressure on the throttle pedal. Normalized from 0 to 1.

  • Brake: the current pressure on the brake pedal.Normalized from 0 to 1.

  • Hand Brake: if the hand brake is activated.

  • Steer Noise: the current steering angle in the vehicle considering the noise function.

  • Throttle Noise: the current pressure on the throttle pedal considering the noise function.

  • Brake Noise: the current pressure on the brake pedal considering the noise function. The noise function is described here.

For each one of the non-player agents (pedestrians, vehicles, traffic light), the following information is provided:

  • Unique ID: an unique identifier of this agent.
  • Type: if it is a pedestrian, a vehicle or a traffic light.
  • Position: the world position of the agent. It is expressed as a three dimensional vector (x,y,z) in meters.
  • Orientation: the orientation of the agent with respect to the world. Expressed as Euler angles (row, pitch and yaw).
  • Forward Speed: an scalar expressing the linear forward speed of the agent.
  • State: only for traffic lights, contains the state of the traffic light, if it is either red, yellow or green.