Study and Analysis of Various Smart Vehicle Vulnerable Prevention Using Digital Twin Technology: A Challenging Review
Study and Analysis of Various Smart Vehicle Vulnerable Prevention Using Digital Twin Technology: A Challenging Review |
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| © 2024 by IJETT Journal | ||
| Volume-72 Issue-8 |
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| Year of Publication : 2024 | ||
| Author : Ravula Vishnukumar, Mangayarkarasi Ramaiah |
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| DOI : 10.14445/22315381/IJETT-V72I8P109 | ||
How to Cite?
Ravula Vishnukumar, Mangayarkarasi Ramaiah, "Study and Analysis of Various Smart Vehicle Vulnerable Prevention Using Digital Twin Technology: A Challenging Review," International Journal of Engineering Trends and Technology, vol. 72, no. 8, pp. 73-87, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I8P109
Abstract
In light of the exponential growth of the digital age, several intelligent and autonomous systems are implemented in the intelligent transport system. Safety and security measures of Autonomous Vehicles (AV) significantly minimize accidents and manage a cautious environment for drivers and pedestrians. Therefore, the digital twin approach plays a vital role in data renovation for data-driven vehicles, especially within autonomous vehicle design. This raises the need to obtain novel safety models to boost the security of sovereign vehicle systems. Hence, this survey analyses various Smart vehicle vulnerability prevention techniques using Digital twin technology. This study analyzes the different research papers focused on numerous methods, such as machine learning, reinforcement learning, optimization, graph and deep learning, etc. Finally, the assessment is made based on the year of publication, research technique, evaluation metrics, and accomplishment of Smart vehicle vulnerable prevention research methods using Digital twin technology. In the end, the research comes up with the gaps and challenges of systems so that inspiration for emerging a productive technique for Smart vehicle vulnerability prevention using Digital twin technology is revealed.
Keywords
Vulnerable prevention, Smart vehicle, Digital twin, Deep reinforcement learning, Machine learning.
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