%0 Journal Article
%T 高速公路隧道路段小客车运行速度预测模型<br>Prediction model of passenger train running speed on？？expressway tunnel section
%A 马聪
%A 张生瑞
%A 王亚群
%J 长安大学学报(自然科学版)
%D 2018
%X 为了提高隧道进出口位置处的安全性，对隧道路段运行速度的预测模型进行研究。在分析隧道路段短、中、特长隧道路段的运行速度连续变化特性基础上，对影响运行速度的因素进行分析，并做单因素分析；选取影响运行速度的显著因素，如曲率变化率、曲度、弯坡组合、圆曲线半径进行多元回归，建立隧道路段出入口及隧道内运行速度预测模型，并通过实车数据对所建立模型进行检验。研究结果表明：建立的高速公路隧道路段运行速度模型能够精确预测隧道各路段运行速度，预测结果与实际结果的平均残差值为4.06 km/h，且检验残差均服从正态分布，说明该模型有效；提出的运行速度预测模型的精度较高，可以在高速公路隧道路段实际应用，为高速公路隧道路段安全审查与评价山区高速公路特殊位置速度预测提供参考。<br>To improve the safety of tunnel entrances and exits, a prediction model of the speed of a car in a tunnel section was studied. Based on analysis of the continuous change characteristics of the speed of the car in short, medium, and long tunnel sections, the factors that affected the speed were determined. A single？？factor analysis was performed to select the influence speed. The significant factors, such as curvature change rate, curvature, bending slope combination, and circular curve radius were obtained using multiple regressions. The prediction model of the tunnel entrance and tunnel running speed were established, and the model was tested on real vehicle data. The results show that the speed model for the car in the highway tunnel section can accurately predict the optimum limit of speed for each section of the tunnel. The average residual value of the prediction results compared to the actual results is 4.06 km/h. The test residuals conform to a positive distribution, which indicates that the model is effective, and the speed prediction model is thus formulated. This model can be used in highway tunnel sections to provide references for safety reviews and evaluation of speed limits or predictions for special cases for expressways in mountain areas. 7 tabs, 7 figs, ？？16 refs？？
%K 交通工程
%K 隧道路段
%K 速度变化特征
%K 运行速度预测模型
%K 模型标定&lt
%K br&gt
%K traffic engineering
%K tunnel section
%K change characteristics of speed
%K prediction model of speed
%K model calibration
%U http://zzszrb.chd.edu.cn/oa/DArticle.aspx?type=view&id=201804012