Research on Verification and Evaluation Method of Automatic Emergency Braking Function in Rain and Fog Weather Based on TOPSIS

This paper addresses the impact of adverse weather conditions on the performance of sensors in autonomous vehicles, focusing on radar and cameras. An evaluation system, incorporating the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method, is proposed to objectively assess sensor effectiveness in various weather scenarios. The study delves into the specific effects of rain, fog, and snow on sensors, considering factors such as detection range, sensitivity, and signal distortion. The proposed TOPSIS-based evaluation system involves normalization, construction of a projection indicator function, determination of ideal and negative ideal solutions, and calculation of distances to these solutions. The relative closeness metric aids in ranking sensor performance under diverse weather conditions. Experimental verification through simulation experiments validates the proposed method, revealing notable delays in Automatic Emergency Braking (AEB) activation during rainy weather. The study offers comprehensive insights into sensor behavior in adverse weather, shedding light on critical factors influencing sensor accuracy and triggering AEB systems. This research contributes a systematic approach to evaluating sensor performance in adverse weather, crucial for advancing the reliability and safety of autonomous vehicles.