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

[NeurIPS 2022] Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline.

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]

Self Driving Cars Longitudinal and Lateral Control Design

Code for the paper "Reinforced Curriculum Learning for Autonomous Driving in CARLA" (ICIP 2021)

A simple gym environment wrapping Carla, a simulator for autonomous driving research. The environment is designed for developing and comparing reinforcement learning algorithms. Trackable costs also enable the application of safe reinforcement learning algorithms.

Learning Model Predictive Control (LMPC) for autonomous racing in CARLA 3D environment.

Implementation of a Longitudinal and Lateral controller (2D) of an autonomous vehicle on Carla Simulator

An implementation of a full motion and behavior planning pipeline for a self-driving car in the CARLA simulator.

A simple yet effective repo for object detection based on the FCOS architecture.

The goal of this project is to develop models capable of completing a variety of autonomous tasks within the Carla simulator.

This is the ultimate step-by-step guide for the final Project work of Coursera's Introduction to Self-Driving Car's Course on Carla Driving Simulator for Trajectory Tracking and PID controlling.

Semantic Segmentation project for Autonomous Driving based on a TensorFlow implementation of UNet

Codebase of paper "DeFIX: Detecting and Fixing Failure Scenarios with Reinforcement Learning in Imitation Learning Based Autonomous Driving" published at ITSC 2022 📝

Module for deep learning powered, stateful imitation learning in the CARLA autonomous vehicle simulator.

The aim of this project is to provide and implement a comprehensive suite of AI tools for Car vision to detect potential hazards, provide collision warnings, and analyze road conditions.

This generator creates valid variations of carla scenarios in XML

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