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- Performance Analysis of End-To-End Autonomous Driving Systems in Varying Simulated ScenariosPublication . Morgado, Ângelo Miguel Rodrigues; Pombo, Nuno Gonçalo Coelho CostaIn recent years, the importance of autonomous driving has increased significantly due to technological advances and the changing needs of society. Autonomous driving promises safer, more efficient transportation, with the potential to reduce traffic congestion and accidents. However, achieving fully autonomous driving remains a challenge. One of the main limitations is that current autonomous vehicles cannot drive safely in all scenarios, especially in adverse weather conditions. Testing these scenarios in the real world is impractical and often unsafe, which makes simulation an essential tool for developing autonomous driving agents. Simulation environments allow for extensive testing of autonomous vehicles, providing valuable information and helping to improve the reliability and safety of autonomous driving systems. Most commercially available autonomous vehicles follow a modular architecture, where each phase, from information collection, to vehicle control is separated into different modules arranged individually from each other. However, there are studies that discuss a different architecture, end-to-end, where all these modules are combined into one and trained simultaneously. This project has two main objectives, the first is to develop a tool called CARLA-GymDrive, whose functionality is to allow the user to train a reinforcement learning agent in an environment compatible with the gymnasium library in the CARLA simulator; the second is to train agents with the two autonomous vehicle architectures end-to-end and modular, along with two learning algorithms, DQN and PPO. Trained agents are subject to a series of tests to comprehensively assess their performance and robustness. This study not only highlights the fundamental role of simulation in the development of reliable autonomous systems, but also acesses the potential of the end-to-end architecture.