Navigating Security and Safety Challenges in Autonomous Vehicle Systems: A Risk-Based Assessment Framework

In the past few years, the advancement and adoption of autonomous vehicles AVs have rapidly increased. As a result of which safety and security of Avs has become a big challenge. These vehicles are dependent on systems including various sensors, AI systems and connectivity systems These systems are vulnerable to security threats and safety risks. The autonomous driving system faces various security challenges including cyberattacks on the AV software, communication systems or on the cloud-based platforms. These security threats could affect control systems of the vehicle which could lead to catastrophic failures. In addition to this, system and sensor errors could also result in failure of the AI decision system, which pose risks not only to passengers but also to other road users. To the ensure the safety and reliability of AVs a comprehensive risk assessment framework is needed that will not only evaluate the impact of such incidents but also incorporate advance technologies for timely detection and prevention of such incidents. This paper will focus on developing a risk-based framework to assess and mitigate the challenges associated with AV technologies, emphasizing the safety and security dimensions. We will examine key safety standards and explore techniques such as real-time risk monitoring, machine learning-based threat detection, and resilient system design. Through a focus on risk management practices, we aim to establish guidelines for the secure and safe integration of autonomous vehicles, making the way for widespread adoption and public trust in this transformative technology.

Keywords: Risk-assessment, Security challenges, Autonomous vehicle systems.