How to Cite
Abstract
The current algorithms to ensure vehicle safety are not fool-proof. For example, in a recent example, systems did not correctly identify between a cloud and temperature reading and caused an accident. That and many more examples show the limit that can be reached without proper human intervention to guide systems that are meant to drive and function independently. This lack of human intervention exists in most systems of learning systems today, research has shown. This paper features one of the first to demonstrate the limitations of current algorithms, demonstrate how human-in-the-loop (HIL) validation could address these issues, and evaluate the transferability, legal applicability, and societal implications of autonomous vehicle algorithms [1].References
Y. Shao, S. Weerdenburg, J. Seifert, H. Paul Urbach et al., "Wavelength-multiplexed Multi-mode EUV Reflection Ptychography based on Automatic-Differentiation," 2023. [PDF]
S. Lee, Y. Cho, and B. C. Min, "Attack-Aware Multi-Sensor Integration Algorithm for Autonomous Vehicle Navigation Systems," 2017. [PDF]
Tatineni, Sumanth. "Exploring the Challenges and Prospects in Data Science and Information Professions." International Journal of Management (IJM) 12.2 (2021): 1009-1014.
J. N. Brewer and G. Dimitoglou, "Evaluation of Attack Vectors and Risks in Automobiles and Road Infrastructure," 2020. [PDF]
Vemori, Vamsi. "Evolutionary Landscape of Battery Technology and its Impact on Smart Traffic Management Systems for Electric Vehicles in Urban Environments: A Critical Analysis." Advances in Deep Learning Techniques 1.1 (2021): 23-57.
L. A. Shepherd, S. De Paoli, and J. Conacher, "Human-Computer Interaction Considerations When Developing Cyber Ranges," 2020. [PDF]
P. Xiong, S. Buffett, S. Iqbal, P. Lamontagne et al., "Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective," 2021. [PDF]
S. M Mostaq Hossain, S. Banik, T. Banik, and A. Md Shibli, "Survey on Security Attacks in Connected and Autonomous Vehicular Systems," 2023. [PDF]
F. Berman, E. Cabrera, A. Jebari, and W. Marrakchi, "The impact universe—a framework for prioritizing the public interest in the Internet of Things," 2022. ncbi.nlm.nih.gov
A. Dinesh Kumar, K. Naga Renu Chebrolu, V. R, and S. KP, "A Brief Survey on Autonomous Vehicle Possible Attacks, Exploits and Vulnerabilities," 2018. [PDF]
D. Haileselassie Hagos and D. B. Rawat, "Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives," 2022. ncbi.nlm.nih.gov
A. Shah, "Adversary ML Resilience in Autonomous Driving Through Human Centered Perception Mechanisms," 2023. [PDF]
P. McDaniel and F. Koushanfar, "Secure and Trustworthy Computing 2.0 Vision Statement," 2023. [PDF]
D. Papatsaroucha, Y. Nikoloudakis, I. Kefaloukos, E. Pallis et al., "A Survey on Human and Personality Vulnerability Assessment in Cyber-security: Challenges, Approaches, and Open Issues," 2021. [PDF]
S. Adam Matei and E. Bertino, "Educating for AI Cybersecurity Work and Research: Ethics, Systems Thinking, and Communication Requirements," 2023. [PDF]
F. Sharevski, A. Trowbridge, and J. Westbrook, "Novel Approach for Cybersecurity Workforce Development: A Course in Secure Design," 2018. [PDF]
V. Linkov, P. Zámečník, D. Havlíčková, and C. W. Pai, "Human Factors in the Cybersecurity of Autonomous Vehicles: Trends in Current Research," 2019. ncbi.nlm.nih.gov
D. H. Lee, C. M. Kim, H. S. Song, Y. H. Lee et al., "Simulation-Based Cybersecurity Testing and Evaluation Method for Connected Car V2X Application Using Virtual Machine," 2023. ncbi.nlm.nih.gov
M. Hamad and S. Steinhorst, "Security Challenges in Autonomous Systems Design," 2023. [PDF]
T. Holstein, G. Dodig-Crnkovic, and P. Pelliccione, "Ethical and Social Aspects of Self-Driving Cars," 2018. [PDF]
L. Luxmi Dhirani, N. Mukhtiar, B. Shankar Chowdhry, and T. Newe, "Ethical Dilemmas and Privacy Issues in Emerging Technologies: A Review," 2023. ncbi.nlm.nih.gov