Improvement of an autonomous emergency-braking decision-making system for commercial vehicles based on unsafe control strategy analysis

Most current automatic emergency-braking (AEB) systems perceive the surrounding environment through on-board sensors, which generally encounter the following issues: the cost of lidar is high, their performance in the presence of smoke medium and rain and snow weather is imprecise and is restricted by long-distance energy loss, and the millimeter-wave radar can only sense obstacles in a short distance. The monocular/binocular camera is greatly affected by objective factors, such as reduced visibility due to weather and nighttime, resulting in a small observation distance. At the intersection, the road traffic environment is complex, specifically when a commercial vehicle has a remarkable blind spot, and the function of the vehicle sensor is greatly limited.

To improve the safety and reliability of AEB systems, this work designs and studies an AEB system for commercial vehicles based on unsafe control behavior. First, a compensation method is proposed on the basis of the characteristics of vehicle-to-vehicle communication delay under different conditions. Real vehicle tests are conducted to collect data regarding the communication delay of vehicle-mounted communication equipment transmitting self-vehicle information under different working conditions. The average value is taken as the delay compensation in the safety distance and then added as compensation data to the established safety distance model in the AEB system based on vehicle-road coordination. The delay law is used to correct parameters such as the speed, displacement, and coordinates of the environmental vehicle to compensate for the impact of communication delay on system decision-making. An AEB strategy for commercial vehicles at the intersection section is described. The contours of the two vehicles are projected onto a coordinate system to determine whether the two vehicles overlap. When a collision risk is detected, the collision avoidance strategy of the two vehicles at the road intersection is implemented. When the two vehicles are about to collide, the braking system of the vehicle is controlled to brake automatically and urgently with maximum braking deceleration to avoid collision. Furthermore, the unsafe control behavior causing the accident is determined through analysis, and the corresponding safety constraints are used to optimize the algorithm strategy. Finally, the proposed algorithm is simulated and tested.

Results show that the proposed AEB algorithm based on unsafe control behavior can effectively prevent the collision of two vehicles at the intersection and has high safety and reliability.

This study has a few limitations and shortcomings. This work only considers the influence of communication delay and braking onset stage on the safe braking distance, and the collision avoidance strategy only considers the scene of a straight intersection. In future research, consideration will be given to the factors affecting the ability to obtain an accurate and safe braking distance, and 5G technology will be gradually applied to an AEB system based on vehicle-road coordination.