Background: The automotive industry is experiencing a transformative shift with the integration of Autonomous Driving (AD) and Advanced Driver Assistance Systems (ADAS). These technologies promise to enhance vehicle safety and performance, but their complexity requires rigorous testing and validation processes. However, these testing processes often face challenges such as inefficiencies and gaps that can hinder their effectiveness. Identifying and understanding these challenges is crucial for ensuring the reliability and safety of AD and ADAS technologies.

Objectives: This thesis aims to identify and analyze gaps and inefficiencies in the current AD and ADAS testing processes within a leading automotive company. The study seeks to prioritize these issues to offer insights for improving testing practices and enhancing overall efficiency.

Methods: The research adopts a qualitative case study approach, employing document analysis, observations, semi-structured interviews, and surveys to gather comprehensive data. The study focuses on a specific AD/ADAS testing team within the company, providing in-depth insights into their testing processes and practices.

Results: The findings highlight several key challenges, including inconsistent availability of Hardware-in-the-Loop (HiL) test rigs, heavy reliance on specific individuals for technical knowledge, outdated documentation practices, and a lack of formal guidelines for creating test strategies. These issues are prioritized based on their severity to guide future considerations.

Conclusions: The study underscores the importance of addressing the identified challenges to improve the efficiency and reliability of AD and ADAS testing practices. While the findings are specific to one company's processes, they provide insights that can be seen as general guidance for AD and ADAS technology developers facing similar challenges. Future research should explore the integration of advanced technologies to optimize testing processes further. The findings provide a strategic roadmap for the company's AD and ADAS testing practices.