基于拟人智能决策-规划算法的主动制动系统研究

Investigation of Active Braking System Based on Personification Intelligent Decision Planning Algorithm

摘要:

为了提高智能汽车在突发性交通危险工况下的安全性，设计了主动制动系统拟人智能决策-规划算法。建立了不同路面峰值附着系数条件下的制动电机目标电流Ii-hope函数，依据制动过程中实际滑移率λ和路面峰值附着系数μ，对制动电动机最优目标电流进行实时决策-规划。研究结果表明，在突发性交通危险工况下，所设计的拟人智能决策-规划算法能够把滑移率控制在当前路况最佳滑移率附近，在兼顾了舒适性的同时，整车制动能力提高了4.12%~4.38%，有效降低了智能汽车在突发性交通危险工况下的事故率。

Abstract:

In order to improve the safety of intelligent vehicle in sudden traffic dangerous condition, a humanoid intelligent decision-planning algorithm was designed for active braking system. The characteristics of braking deceleration of experienced drivers under sudden traffic hazard were simulated and the target current function Ii-hope of the braking motor under the condition of different maximum tire-road friction coefficient was established. According to the actual slip ratio λ and the maximum tire-road friction coefficient μ in the braking process, a real-time decision-planning was made for the optimal target current of the braking motor. Using CarSim’s vehicle model, a humanoid intelligent decision-planning algorithm of active braking system was built in Simulink. Through the joint simulation of CarSim and Simulink and compared with the hydraulic brake system that existed in CarSim, the braking performance of stationary target and moving target under different tire-road friction coefficients was analyzed. The results showed that in the sudden danger of traffic conditions, the designed humanoid intelligent decision-planning algorithm was able to control the slip ratio in the current road near optimal slip ratio, and when taking both comfort and safety into consideration, the braking ability of the active braking system was increased by 4.12%~4.38%, which effectively reduced the accident rate of intelligent vehicle under the dangerous traffic condition.