Harnessing Artificial Intelligence for Enhanced Vehicle Control and Diagnostics

DOI: https://doie.org/10.0618/Jbse.2024953164

Ravi Aravind, Srinivas Naveen Reddy Dolu Surabhii

Keywords:

Harnessing Artificial Intelligence, Industry 4.0, Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), Smart Manufacturing (SM),Computer Science, Data Science,Vehicle, Vehicle Reliability

Abstract:

Automotive systems are becoming increasingly complex, with new technology being included to meet safety, performance, standardization, and cost targets. Control systems are an essential part of the increment just of such technologies. Artificial Intelligence (AI) has been proposed to play an important role in vehicle control, helping to create self-driving solutions and enhancing the overall vehicle stability and efficiency, particularly in extreme operating conditions. By adopting suitable supervisory control actions, AI can help recover vehicle operations when these are outside the range of standard control solutions and have the onset scenario of different failures. In addition to these benefits, designed AI tools, in particular Neural Networks, appeared to be adopted and developed for diagnostics purposes, where learning from collected 'experience observations data, often not possible to be generated with simulations or under controlled conditions, is required. This paper presents a review of designed AI tools applied to automotive vehicle control optimization, diagnostics, and fault detection purposes.

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