An OpenAI gym wrapper for CARLA simulator
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Updated
Feb 14, 2022 - Python
An OpenAI gym wrapper for CARLA simulator
Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.
(CVPR 2022) A minimalist, mapless, end-to-end self-driving stack for joint perception, prediction, planning and control.
Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch
Official github page of UCF SST CitySim Dataset
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:
Deep Reinforcement Learning (PPO) in Autonomous Driving (Carla) [from scratch]
[ICCV'23] Hidden Biases of End-to-End Driving Models
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
[CoRL'22] PlanT: Explainable Planning Transformers via Object-Level Representations
[CVPR 2023] Pytorch implementation of ThinkTwice, a SOTA Decoder for End-to-end Autonomous Driving under BEV.
A research framework for autonomous driving
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
Generating training data from the Carla driving simulator in the KITTI dataset format
SHIFT Dataset DevKit - CVPR2022
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