Machine Learning Algorithms for Predictive Maintenance in Autonomous Vehicles

Chirag Vinalbhai Shah

doi:10.18535/ijecs/v13i01.4786

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Chirag Vinalbhai Shah,

Article Date Published : 30 January 2024 | Page No.: 26015-26032 |

DOI https://doi.org/10.18535/ijecs/v13i01.4786

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Abstract

The complexity and hazards of autonomous vehicle systems have posed a significant challenge in predictive maintenance. Since the incompetence of autonomous vehicle system software and hardware could lead to life-threatening crashes, maintenance should be performed regularly to protect human safety. For automotive systems, predicting future failures and taking actions in advance to maintain system reliability and safety is very crucial in large-scale product design. This paper will explore several machine learning algorithms including regression techniques, classification techniques, ensemble techniques, clustering techniques, and deep learning techniques used for system maintenance need assessment in autonomous vehicles. Experimental results indicate that predictive maintenance can be greatly helpful for autonomous vehicles either in improving system design or mitigating the risk of threats.

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

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Chirag Vinalbhai Shah

Sr Vehicle Integration Engineer GM
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International Journal of Engineering and Computer Science, 2024.

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Issue: Vol. 13 No. 01 (2024)

Page No.: 26015-26032

Section: Articles

DOI: https://doi.org/10.18535/ijecs/v13i01.4786

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Shah, C. V. (2024). Machine Learning Algorithms for Predictive Maintenance in Autonomous Vehicles. International Journal of Engineering and Computer Science, 13(01), 26015–26032. https://doi.org/10.18535/ijecs/v13i01.4786

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Machine Learning Algorithms for Predictive Maintenance in Autonomous Vehicles

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