An OpenAI gym wrapper for CARLA simulator

Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.

Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]

[ICCV'23] Hidden Biases of End-to-End Driving Models & A starter kit for the CARLA leaderboard 2.0.

(CVPR 2022) A minimalist, mapless, end-to-end self-driving stack for joint perception, prediction, planning and control.

Official github page of UCF SST CitySim Dataset

Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch

Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:

[CoRL'22] PlanT: Explainable Planning Transformers via Object-Level Representations

Interpretable End-to-end Urban Autonomous Driving with Latent Deep Reinforcement Learning

Blender add-on for creating OpenDRIVE and OpenSCENARIO based automotive driving scenarios including 3D models

[CVPR 2023] Pytorch implementation of ThinkTwice, a SOTA Decoder for End-to-end Autonomous Driving under BEV.

A research framework for autonomous driving

A simple and easy-to-use autonomous driving environment for reinforcement learning, based on the CARLA simulator.

converter for OpenStreetMaps to OpenDrive roads - for use with Carla or other things

(ICCV 2021, Oral) RL and distillation in CARLA using a factorized world model

The Combined Anomalous Object Segmentation (CAOS) Benchmark

Predict Vehicle collision moments before it happens in Carla!. CNN and LSTM hybrid architecture is used to understand a series of images.

Reinforcement Learning Agents Trained in the CARLA Simulator

🚗 This repository offers a ready-to-use training and evaluation environment for conducting various experiments using Deep Reinforcement Learning (DRL) in the CARLA simulator with the help of Stable Baselines 3 library.