As hardware devices that help intelligent vehicles perceive the traffic environment, sensors play a crucial role in vehicle safety control. However, in the face of a complex traffic scene, detection failure is a safety of the intended functionality (SOTIF) problems that may occur due to sensors’ limited functions. For example, under slope road at night, the radar sensor may lose the target because of the narrow detection perspective, vision sensors is prone to severe distortion because of poor light. Therefore, this paper proposes a following strategy to address the SOTIF problems like this. By analyzing the historical data, the motion behavior of the preceding vehicle when SOTIF events happen is predicted based on the improved Markov model. Then, the observation and expectation models of the vehicular distance are designed based on vehicle movement and slope conditions to obtain the distance information. The sliding mode controller is designed to control velocity and prevent collisions and other accidents reasonably. Finally, simulation and hardware-in-the-loop (HiL) tests verify that the proposed method can improve vehicle safety when the sensors’ function fails on slope road at night.
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