Vol. 1 No. 1 (2021): Journal of AI-Assisted Scientific Discovery
Articles

AI-Driven Approaches for Autonomous Vehicle Adaptive Cruise Control

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  • Dr. Heejin Choi
Dr. Heejin Choi
Professor of Computer Science, Gwangju Institute of Science and Technology (GIST)
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Published 30-06-2021

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How to Cite

[1]
Dr. Heejin Choi, “AI-Driven Approaches for Autonomous Vehicle Adaptive Cruise Control”, Journal of AI-Assisted Scientific Discovery, vol. 1, no. 1, pp. 72–91, Jun. 2021, Accessed: Nov. 22, 2024. [Online]. Available: https://scienceacadpress.com/index.php/jaasd/article/view/60

Abstract

AI technology and edge computing are going to play key roles in the future of autonomous vehicles, facilitating comprehensive software and hardware co-development. As a result, the automotive industry has been witnessing considerable AI-driven initiatives to reach smart lateral-conducive and longitudinal-regulating systems that are amended to suite the sky-reaching requirements of autonomous vehicles. The communication between vehicles and the cloud server will be a bottleneck for advanced intelligent control of autonomous vehicles that can be solved through deploying AI and edge computing support. Consequently, the following research questions should be carefully addressed: how can edge-AI engine be designed and deployed to approximate critical interactive features among AV-only networks and also among mixed AV- CV networks. Furthermore, being an integral part of the future automotive industry, the technology is expected to be applicable to a series of performance tests under real traffic scenarios. Consequently, the communication between vehicles and the cloud server will set to be a bottleneck for advanced intelligent control of autonomous vehicles that can be greatly solved by deploying AI and edge computing support. [1]

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