Virtual Trust on Driverless Cars Using Fuzzy Logic Design

Alroshan, A, Asgher, T, Hussain, M, Shahzad, M, Rasool, M and Abu-Khadrah, A (2022) Virtual Trust on Driverless Cars Using Fuzzy Logic Design. In: 2022 International Conference on Business Analytics for Technology and Security (ICBATS), 16-17 Feb. 2022, Dubai, United Arab Emirates.

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Abstract

People’s interest in self-driving cars is increasing day by day. How they affect our daily lives and how they benefit us in different ways. These cars are also called robotic cars. These vehicles work with the latest technology to meet the needs of human transportation without any interference. This is a major development in the car manufacturing industry using the latest technology features. These cars communicate with each other over a wireless network. These cars take note of their surroundings with cameras and sensors. Their positions are tracked by navigation paths, GPS radar, etc. If the current path changes, the cars change their position through the modern control system. These cars reduce traffic accidents, increase confidence, and increase road capacity. The main advantage is to reduce the traffic police and no car insurance policy is required, self-drive cars use less fuel than other cars. But on the other hand, issues related to software such as cybersecurity, reliability need to be overcome. The most important thing is related to driver jobs which are most dangerous for human beings. This paper deals with the calculation of virtual trust on driverless cars using fuzzy logic design. Verified results and analysis obtained through the Mamdani Fuzzy Inference System to test virtual trust in driverless cars. Results have been verified using MATLAB simulation.

Affiliation: Skyline University College
SUC Author(s): Alroshan, A
All Author(s): Alroshan, A, Asgher, T, Hussain, M, Shahzad, M, Rasool, M and Abu-Khadrah, A
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Self-Driving Cars, Robotic Cars, Sensing, Advance Technology ,Manufacture, Mamdani Fuzzy Inference System
Subjects: B Information Technology > BC Digital Logic
Divisions: Skyline University College > School of IT
Depositing User: Mr Veeramani Rasu
Date Deposited: 27 May 2022 15:10
Last Modified: 27 May 2022 15:10
URI: https://research.skylineuniversity.ac.ae/id/eprint/266
Publisher URL: https://doi.org/10.1109/ICBATS54253.2022.9759077
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