Research on key scenario generation and simulation of automatic emergency braking function test under rain and fog weather conditions

This paper presents a method for generating and simulating critical scenarios for Automatic Emergency Braking (AEB) testing in rainy and foggy weather conditions. The method utilizes a subgradient descent optimization algorithm and a six-neighborhood flood-fill algorithm to search and generate critical hazard scenarios, based on a scenario importance model and threshold setting. Simulation results demonstrate that under clear weather conditions, the AEB system successfully triggers and prevents collisions. However, in snowy weather conditions, although the AEB system triggers, it fails to prevent collisions due to late triggering and insufficient braking deceleration. The experimental results validate the effectiveness of the proposed method in effectively testing the performance of AEB systems under different weather conditions. This research is of significant importance for enhancing the safety performance of AEB systems.