CarlaDRLAutonomy is a repository that focuses on the development and testing of Deep Reinforcement Learning (DRL) algorithms for autonomous vehicle driving within the CARLA simulation environment. CARLA is an open-source simulator for autonomous driving research, which provides the necessary tools for assessing the performance of DRL-based autonomous driving systems.
- DRL Integration: Utilizes advanced DRL algorithms to train autonomous vehicles to navigate complex driving scenarios within the CARLA simulator.
- Simulation Environment: Leverages the CARLA simulation platform to provide a realistic and safe environment for testing and improving autonomous driving models.
- Autonomous Vehicle Control: Aims to develop DRL models that can effectively control an autonomous vehicle, handling tasks such as lane keeping, obstacle avoidance, and navigation.