Semi Autonomous

Semi-autonomous systems, particularly in the context of autonomous driving, aim to combine automated functionalities with human oversight to enhance safety and performance. Current research focuses on improving human-machine interaction, particularly during critical takeovers, through multimodal interfaces and advanced situation awareness assessment using techniques like Answer Set Programming and deep learning for object detection and scene understanding in diverse traffic conditions. This work is crucial for advancing the reliability and safety of semi-autonomous vehicles, addressing challenges like accurate localization and robust perception in complex and unstructured environments.