A Comprehensive Survey and Tutorial on Smart Vehicles: Emerging Technologies, Security Issues, and Solutions Using Machine Learning

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Usman Ahmad, Mu Han, Alireza Jolfaei, Sohail Jabbar, Muhammad Ibrar, Aiman Erbad, Houbing Herbert Song, Yazeed Alkhrijah

Published: 01 Jan 2024, Last Modified: 04 Nov 2025IEEE Transactions on Intelligent Transportation SystemsEveryoneRevisionsCC BY-SA 4.0
Abstract: According to research, the vast majority of road accidents (90%) are the result of human error, with only a small percentage (2%) being caused by malfunctions in the vehicle. Smart vehicles have gained significant attention as potential solutions to address such issues. In the future of transportation, travel comfort and road safety will be ensured while also offering several value-added services. The automotive industry has undergone a significant transformation through the use of emerging technologies and wireless communication channels, resulting in vehicles becoming more interconnected, intelligent, and safe. However, these technologies and communication systems are susceptible to numerous security attacks. The objective of this paper is to present a comprehensive overview of the smart vehicle’s architecture, encompassing emerging technologies and security challenges and solutions associated with smart vehicles. There has been a significant surge in the utilization of machine learning techniques in smart vehicles. We categorically discuss common security measures, including machine learning and deep learning based solutions that have been mentioned in the literature and implemented against security threats on smart vehicles. This paper has also been titled a tutorial due to its layout, which begins with covering preliminary knowledge, terminologies, and encompassing technologies required to comprehend smart vehicles. Following this, the paper addresses the overall challenges associated with smart vehicles and then focuses on security issues. In terms of solutions, the paper discusses overall solutions to security issues in smart vehicles before delving into a specific solution based on machine learning and deep learning.