Optimization of AEB Decision System Based on Unsafe Control Behavior Analysis and Improved ABAS Algorithm

The current Automatic Emergency Braking (AEB) system based on vehicle sensors has a field of view blind spot, greatly limiting its function. This paper proposes an optimization strategy for commercial vehicle AEB system based on unsafe control behavior to improve the safety and reliability of the AEB system. Firstly, the communication delay law of vehicle-to-vehicle communication under different working conditions is obtained through real vehicle tests. The delay is then used to compensate and correct parameters such as speed, displacement, and coordinates of the environmental vehicle, in order to account for the impact of communication delay on system decision-making. Next, an AEB strategy for commercial vehicles at the intersection section is formulated. When two vehicles are about to collide, the braking system of the test vehicle is controlled to automatically emergency brake with the maximum braking deceleration to avoid collision. The AEB system strategy is optimized based on the analysis of unsafe control behavior. Then, an improved Antenna historical optimum-based Beetle Antenna Search (ABAS) algorithm is proposed based on the Beetle Antenna Search (BAS) and Beetle Swarm Antenna Search (BSAS) algorithm, which improves the optimization performance of the algorithm under the known constraint space, such as vehicle motion modeling and collision avoidance. Finally, the simulation result show that our proposed method can effectively prevent the collision of two vehicles at the intersection, and has high safety and reliability.