Autonomous Train

Autonomous train technology aims to develop self-driving trains through advanced sensor systems and AI-based control strategies, prioritizing safety and efficiency. Current research heavily focuses on robust perception systems, employing deep learning models like convolutional neural networks for tasks such as precise track detection (including the train's immediate path), real-time obstacle segmentation, and reliable traffic sign recognition. These advancements are crucial for improving railway safety, optimizing operational efficiency, and enabling the transition towards fully automated railway systems.