Reliability and Security Analysis of Artificial Intelligence-Based Self-Driving Technologies in Saudi Arabia: A Case Study of Openpilot

Author:

Alsubaei Faisal S.1ORCID

Affiliation:

1. Department of Cybersecurity, College of Computer Science and Engineering, University of Jeddah, Jeddah, Saudi Arabia

Abstract

Saudi Arabia has an ambitious vision that embraces artificial intelligence (AI) technologies at a mass scale in new cities such as Neom. Self-driving has recently become one of the most important AI applications due to the advancement of sensors and AI algorithms. Given that safety is vital to the success of self-driving cars, existing infrastructures (e.g., roads and traffic signs) should be compatible with self-driving technologies. However, self-driving technologies have not been thoroughly examined in Saudi Arabia with regard to the country’s infrastructure and traffic. Therefore, this paper highlights the main areas of improvement in available self-driving technologies in Saudi Arabia. This analysis can help governments understand the current limitations of such technologies so that they can regulate them and enhance infrastructures to prepare for the mass adoption of self-driving cars. It can also help car manufacturers and developers improve self-driving algorithms to overcome their existing limitations, which will ultimately improve the safety and experience of driving.

Funder

University of Jeddah

Publisher

Hindawi Limited

Subject

Strategy and Management,Computer Science Applications,Mechanical Engineering,Economics and Econometrics,Automotive Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Public Perception of the Introduction of Autonomous Vehicles;World Electric Vehicle Journal;2023-12-12

2. Application of Artificial Intelligence in Automobiles: Applications, Challenges and Future Scope;2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS);2023-12-11

3. Emerging Cybersecurity and Privacy Threats to Electric Vehicles and Their Impact on Human and Environmental Sustainability;Energies;2023-01-19

4. Detecting Defects in Deep Learning Systems: a Survey;13th Asia-Pacific Symposium on Internetware;2022-06-11

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