【摘要】 在当前商用车自主紧急制动系统(autonomous emergency braking,AEB)的控制策略中,测试环境基本为平地路面,且制动距离预测模型较为简单,不能精确预测制动距离,因此提出面向AEB的商用车下坡工况制动距离预测与控制方法,通过仿真得到下坡工况的制动距离数据,使用BP(back propagation)神经网络算法训练,得到制动距离预测模型,最后在TruckMaker中验证制动距离预测与控制方法的有效性。研究结果可为我国商用车AEB系统的设计和改进提供理论依据。更多还原

【Abstract】 In the current control strategy of the commercial vehicle autonomous emergency braking system(AEB), the braking distance cannot be accurately predicted because the test environment is basically a flat road surface, and the braking distance prediction model is relatively simple. A control method to predict the braking distance for AEB of commercial vehicle under downhill conditions is proposed in this work. The data of the braking distance under the downhill condition is obtained by simulation. The BP(back propagation) neural network algorithm is used to train the braking distance prediction model.The feasibility of the control method in predicting the braking distance is finally verified by TruckMaker. The results can provide a theoretical basis for the design and improvement of China’s commercial vehicle AEB system.更多还原