Development of Autonomous Driving in Electric Vehicles: Analysis of Quality Engineering and Future Applicability

This thesis begins by tracing the history and evolution of autonomous driving technologies, highlighting key advancements and current trends. It delves into the integration of autonomous systems with electric vehicles (EVs), examining the challenges and benefits of this convergence. A detailed analysis of global regulatory frameworks governing autonomous vehicle deployment is provided, emphasizing how these regulations must adapt to rapidly advancing technologies. In Chapter 5, a Failure Modes Effects and Criticality Analysis (FMECA) addresses the reliability of core autonomous system components, such as sensors, actuators, and software. This analysis identifies potential failure modes and mitigates risks to ensure the safe development of autonomous driving technologies. The thesis also presents case studies of real-world implementations, including Tesla’s Autopilot, Waymo's autonomous driving technologies, and NIO’s. These examples offer practical insights into how autonomous technologies are being applied and the challenges they encounter. The final chapter discusses future trends, technological innovations, and the socio-economic impacts of widespread autonomous vehicle adoption. The thesis concludes by emphasizing the critical role of ongoing research, regulatory adaptation, and innovations like artificial intelligence and machine learning in shaping the future of autonomous driving.