Centre of Product Design and Manufacturing, Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
School of Mining and Geomatics, Hebei University of Engineering (Hebei), No. 19 Taiji Road, Handan Economic and Technological Development District, Handan 056038, China.
Comput Intell Neurosci. 2022 Oct 7;2022:3100509. doi: 10.1155/2022/3100509. eCollection 2022.
The popularity of private cars has brought great convenience to citizens' travel. However, the number of private cars in society is increasing yearly, and the traffic pressure on the road is also increasing. The number of traffic accidents is increasing yearly, and the vast majority are caused by small private cars. Therefore, it is necessary to improve the traffic safety awareness of drivers and help car manufacturers to design traffic risk prediction systems. The Backpropagation neural network (BPNN) algorithm is used as the technical basis, combined with the MATLAB operation program, to simulate the driving process of the car. Dynamic predictive models are built to predict and analyze vehicle safety risks. Multiple experiments found that: (1) in various simulations, the simulation driving process of MATLAB is more in line with the actual car driving process; (2) the error between BPNN and the actual driving prediction is within 0.4, which can meet the actual needs. Predictive models are optimized to deploy and predict in various traffic situations. The model can effectively prompt risk accidents, reduce the probability of traffic accidents, provide a certain degree of protection for the lives of drivers and passengers, and significantly improve the safety of traffic roads.
私家车的普及给市民出行带来了极大的便利。然而，社会上私家车的数量逐年增加，道路的交通压力也在增加。交通事故的数量也在逐年增加，而且绝大多数都是由小型私家车引起的。因此，有必要提高驾驶员的交通安全意识，并帮助汽车制造商设计交通风险预测系统。采用反向传播神经网络（BPNN）算法作为技术基础，结合 MATLAB 运算程序，模拟汽车的驾驶过程。建立动态预测模型，对车辆安全风险进行预测和分析。多项实验发现：（1）在各种模拟中，MATLAB 的模拟驾驶过程更符合实际汽车驾驶过程；（2）BPNN 与实际驾驶预测之间的误差在 0.4 以内，可以满足实际需要。对预测模型进行优化，以在各种交通情况下进行部署和预测。该模型可以有效地提示风险事故，降低交通事故的概率，为驾驶员和乘客的生命提供一定程度的保护，并显著提高道路交通的安全性。
