In today’s quickly changing automotive market, Advanced Driver Assistance Systems (ADAS) have evolved as a key component of vehicle safety and driving experience. However, assuring dependability and identifying dangers in the application of ADAS features is a major challenge today. This thesis program aims to introduce a unique approach, as stated in the ISO 21448 standard (SOTIF), for testing the robustness, criticality, and dangers associated with ADAS systems and their related advanced/autonomous driving functions. Following the guidelines and recommendations provided by the ISO 21448 standard, the thesis work will contribute to developing comprehensive testing methodologies to identify and effectively mitigate risks associated with ADAS functionalities through the creation, simulation, and virtualization of various test scenarios, enabling testing the robustness of the ADAS system in various environmental conditions.
Main topic: Automotive – Functional Safety – ADAS
Course of study and candidate requirements:
A team of highly motivated students with background in AI/Machine Learning topics applied to ADAS functionality.
Location: Naples