This presentation explores the transformative role of artificial intelligence (AI) in advanced driver assistance systems (ADAS) and automated driving (AD) applications. It delves into the integration of AI models, highlighting the shift from traditional, stack-oriented architectures to end-to-end (E2E) networks. The presentation discusses the benefits of using E2E networks with generative AI, including enhanced system integration, simplified maintenance and scalability. It also examines the potential of AI in sensor fusion, route planning and driver assistance, emphasizing the importance of modern architectures in improving vehicle safety and driver satisfaction.

• The transformative impact of artificial intelligence (AI) on advanced driver assistance systems (ADAS) and automated driving (AD) applications
• The transition from traditional, stack-oriented architectures to end-to-end (E2E) networks in AI integration
• The role of AI in sensor fusion, route planning and driver assistance
• The importance of modern architectures in improving vehicle safety and driver satisfaction
• The benefits of using E2E networks with generative AI, such as enhanced system integration, simplified maintenance and scalability