immanuelpeter/carla-autopilot-images

CARLA Autopilot Images Dataset

Note: A newer, extended version of this dataset is available.
🤗 CARLA Autopilot Multimodal Dataset 🤗
It includes semantic segmentation, LiDAR, 2D bounding boxes, and additional environment metadata.
Use it if your research requires multimodal signals beyond the RGB images and vehicle state/control data provided here.

This dataset contains autonomous driving data collected from CARLA simulator using autopilot.

Dataset Structure

• Train/val/test split is by run, not by frame, to ensure generalization
• Total train samples: 56.2K
• Total val samples: 4.8K
• Total test samples: 7.2K
• Runs processed: 24

Features

Images

Multiple camera views are available depending on the run configuration:

• image_front: Front-facing camera view
• image_rear: Rear-facing camera view
• image_front_left: Front-left camera view
• image_front_right: Front-right camera view

Vehicle State

• Position: location_x, location_y, location_z
• Orientation: rotation_pitch, rotation_yaw, rotation_roll
• Velocity: velocity_x, velocity_y, velocity_z, speed_kmh

Vehicle Controls (Targets)

• throttle: Throttle input [0.0, 1.0]
• steer: Steering input [-1.0, 1.0]
• brake: Brake input [0.0, 1.0]

Environment

• Traffic density information
• Weather conditions
• Map information

Usage

from datasets import load_dataset

dataset = load_dataset("immanuelpeter/carla-autopilot-images")
train_dataset = dataset["train"]
val_dataset = dataset["validation"]
test_dataset = dataset["test"]

Citation

If you use this dataset, please cite the CARLA simulator:

@inproceedings{Dosovitskiy17,
  title = {CARLA: An Open Urban Driving Simulator},
  author = {Alexey Dosovitskiy and German Ros and Felipe Codevilla and Antonio Lopez and Vladlen Koltun},
  booktitle = {Proceedings of the 1st Annual Conference on Robot Learning},
  pages = {1--16},
  year = {2017}
}