Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems
Lukas Stappen, Jeremy Dillmann, Serena Striegel, Hans-J\"org V\"ogel,, Nicolas Flores-Herr, Bj\"orn W. Schuller

TL;DR
This paper provides a comprehensive overview of how generative AI and foundation models are transforming intelligent vehicle systems, highlighting current applications, future research directions, and ethical considerations.
Contribution
It offers a detailed synthesis of current generative AI applications in automotive, identifies key future research challenges, and discusses ethical issues in intelligent vehicle integration.
Findings
Generative AI enhances in-car user interactions through speech, audio, and vision.
Identification of critical future research areas like multimodal integration.
Discussion of ethical challenges and risks in AI-driven automotive systems.
Abstract
This paper aims to serve as a comprehensive guide for researchers and practitioners, offering insights into the current state, potential applications, and future research directions for generative artificial intelligence and foundation models within the context of intelligent vehicles. As the automotive industry progressively integrates AI, generative artificial intelligence technologies hold the potential to revolutionize user interactions, delivering more immersive, intuitive, and personalised in-car experiences. We provide an overview of current applications of generative artificial intelligence in the automotive domain, emphasizing speech, audio, vision, and multimodal interactions. We subsequently outline critical future research areas, including domain adaptability, alignment, multimodal integration and others, as well as, address the challenges and risks associated with ethics.…
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Taxonomy
TopicsReinforcement Learning in Robotics · Topic Modeling · Explainable Artificial Intelligence (XAI)
