Научно-практический журнал кибер безопасности | ISSN 2587-4667

INVESTIGATION OF HUMAN-MACHINE INTERACTION VULNERABILITIES IN AUTONOMOUS VEHICLES

Автор: Vimbainashe M Mhangwa and Brian Maodza
Организация: The Independent Institution of Education, IIEMSA

Категория:

машинное обучение
Ключевые слова: Autonomous Vehicles, Human–Machine Interaction, Interface Vulnerabilities, Trust in Automation, User Safety, System Transparency
Аннотация. There is a growing trend of the use of autonomous vehicles (AVs) to enhance road safety and transportation efficiency. However, these systems introduce significant human–machine interaction (HMI) vulnerabilities that can affect user trust, decision making, safety, security and overall system reliability of autonomous vehicles. This study examined HMI vulnerabilities in autonomous vehicles through a Systematic Literature Review (SLR) of peer-reviewed articles published between 2015 and 2025. The research focused on user concerns regarding interface design, system transparency, automation overreliance, and response to unexpected situations. The findings revealed notable risks associated with poor interface usability, limited user understanding, and weak feedback mechanisms, which can reduce user trust and compromise safety and security of road users. These results contribute to the ongoing discussion on balancing technological advancement with human oversight and provide recommendations for designing more secure, transparent, and user-centred autonomous vehicle systems.
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