摘要
驾驶员驾驶平稳性分析对研究交通安全影响因素起着至关重要的作用。为此提出基于车载自动诊断系统(OBD)采集数据,利用多项式回归进行短时间内车辆速度预测研究。首先分析影响车辆驾驶速度的客观因素,如地势、天气、行驶路径等。其次通过控制客观因素不变,整合有效驾驶速度数据进行多项式回归预测,得到模型的参数。通过真实值与预测值的比对,得到均方差MSE与拟合优度,进而得到最优参数。最后通过大量的实验数据,验证了该模型在此次研究中取得了很好的预测结果。
The analysis of driver driving stability plays a crucial role in studying the factors affecting traffic safety.To this end,it is proposed to use polynomial regression to predict vehicle speed in a short period of time based on data collected by an onboard automatic diagnostic system(OBD).Firstly,it analyzes the objective factors that affect the driving speed of vehicles,such as terrain,weather,driving path,etc.Secondly,by controlling objective factors to remain unchanged and integrating effective driving speed data for polynomial regression prediction,the parameters of the model are obtained.By comparing the true value with the predicted value,the mean squared error(MSE)and goodness of fit are obtained,thereby obtaining the optimal parameters.Finally,through a large amount of experimental data,it is verified that the model has achieved good prediction results in this study.
作者
李文婷
LI Wenting(Qiming Information Technology Co.,Ltd.,Changchun 130122,China)
出处
《现代信息科技》
2024年第7期91-94,共4页
Modern Information Technology
