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山区高速公路弯坡路段车辆运行速度预测模型
引用本文:于海鹏.山区高速公路弯坡路段车辆运行速度预测模型[J].交通科技,2021(1).
作者姓名:于海鹏
作者单位:同济大学道路与交通工程教育部重点实验室
摘    要:为确定山区高速公路弯坡路段的车辆运行速度特征,提高山区高速公路运营安全管理水平,结合山区高速公路复杂的道路线形条件,研究适用于弯坡路段的运行速度预测模型。文中列举国内外具有代表性的运行速度模型,并分析其局限性;通过调研3条典型山区高速公路,采用气压管式车速检测器对车速数据进行采集,选择路段特征点的运行速度作为分析样本;通过比较偏相关系数,确定模型的自变量参数,利用多元线性回归的方法,分别建立不同车型在山区高速公路弯坡路段的运行速度预测模型,并对模型的拟合度进行验证。结果表明,模型预测值与实测值的平均相对误差在5%以内,模型精度满足要求。

关 键 词:运行速度  山区高速公路  弯坡路段  预测模型  模型验证

Vehicle Operating Speed Prediction Model on Curve and Steep Section of Mountain Expressway
YU Haipeng.Vehicle Operating Speed Prediction Model on Curve and Steep Section of Mountain Expressway[J].Transportation Science & Technology,2021(1).
Authors:YU Haipeng
Institution:(The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Shanghai 201804, China)
Abstract:In order to determine the characteristics of vehicle operating speed on curve and steep sections of expressways in mountainous areas,and improve the safety management,considering the complex road alignment conditions,an operating speed prediction model suitable for curved sections of expressway is studied.First,some representative operating speed models at home and abroad are listed and their limitations are analyzed.Secondly,three typical mountainous expressways are investigated.The vehicle speed data are collected using a pneumatic tube speed detector,and the operating speed of the characteristic sections is selected as an analysis sample.Finally,by comparing the partial correlation coefficients,the independent variable parameters of the model are determined.The operating speed prediction models of different vehicles on the curve and steep sections of the mountain expressway are established by the multiple linear regression method.The degree of fitting of the model is verified,and the results show that the average relative error between the predicted value of the model and the measured value is within 5%,and the accuracy of the model meets the requirements.
Keywords:operating speed  mountain expressway  curve and steep section  prediction model  model verification
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