How to Cite
Abstract
Autonomous vehicles use various technologies to compute trajectories, detect potential threats, and avoid accidents without much driver intervention [1]. AVs use several sensors to monitor the vehicle’s environment by scanning several details like the road and driving surfaces, and to detect pedestrians, vehicles, and road obstacles using radar and camera technologies. The AVs can use sensor fusion data to predict potential collision events and help the driver avoid accidents by using potential hazards. Taking road safety from different AV levels as a practical study, this project focuses on developing a complex real-time risk assessment for intervening at level-2 AVs. Hybrid state (between human control and sensor automation) between “human-in the loop” and “automation-in-the-loop”, can recognize future or current risks. Although AVs have huge potentials of saving numerous lives and their social adoption is non-stoppable, they may be also affected by various kinds of hazards—stochastic or accidental road users and potential attacks. Breaking into AV control systems, hackers may cause synthetic accidents causing the robots to interfere with safety even if these ”black box” state transitions are not directly possible. These types of hacking engagement require applying more standard cybersecurity models to recognize potential hazards. The primary standard that many countries are trying to adhere to is ISO€211. However, security cannot be ensured by following the required rules, physically incapable of communicating with the control hardware, validation engineers, or AI designers only. An architectural module, based on the cybersecurity risk-management model used by Bosch in operation, can fill the gap by measuring how much an ISO 21,194-by-compliant system provides security in practice. This model involves all kinds of perpetrators, professional and non-professional adversaries, autonomous and supervised attacks, such as jamming, spoofing, and penetrating through the communication networks between the car and infrastructure [2].
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