TY - GEN
T1 - Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems
AU - Stappen, Lukas
AU - Dillmann, Jeremy
AU - Striegel, Serena
AU - Vögel, Hans Jörg
AU - Flores-Herr, Nicolas
AU - Schuller, Björn W.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - 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 with, 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, multi-modal integration and others, as well as, address the challenges and risks associated with ethics. By fostering collaboration and addressing these research areas, generative artificial intelligence can unlock its full potential, transforming the driving experience and shaping the future of intelligent vehicles.
AB - 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 with, 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, multi-modal integration and others, as well as, address the challenges and risks associated with ethics. By fostering collaboration and addressing these research areas, generative artificial intelligence can unlock its full potential, transforming the driving experience and shaping the future of intelligent vehicles.
UR - http://www.scopus.com/inward/record.url?scp=85168737030&partnerID=8YFLogxK
U2 - 10.1109/ITSC57777.2023.10422003
DO - 10.1109/ITSC57777.2023.10422003
M3 - Conference contribution
AN - SCOPUS:85168737030
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 5790
EP - 5797
BT - 2023 IEEE 26th International Conference on Intelligent Transportation Systems, ITSC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th IEEE International Conference on Intelligent Transportation Systems, ITSC 2023
Y2 - 24 September 2023 through 28 September 2023
ER -