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为确定高速公路互通式立交单车道出口小客车运行速度特征和运行速度值,确保车辆在衔接段运行速度协调可控,使车辆安全运行,在分析高速公路互通式立交单车道出口小客车运行速度实测数据的基础上,得出车辆在出口处的运行规律。采用链式开普勒雷达测速仪对出口小客车速度进行实时采集,选取8条匝道特征点(渐变段起点、分流点与小鼻点)处自由流状态下的小客车速度作为分析样本,采用K-S检验对所取样本进行正态分布检验,在满足检验要求并分析渐变段和减速段速度及加速度特性后,确定自变量参数,最后利用SPSS软件进行回归,分别建立了小客车在分流点及小鼻点处运行速度预测模型,并采用4条匝道数据对模型进行了验证。结果表明:分流点处车辆运行速度随渐变段起点速度增大而增大,随渐变段长度增大而减小;小鼻点处车辆运行速度随渐变段起点速度增大而增大,随渐变段长度、渐变段长与减速段长之比r的增大而减小;预测模型通过了回归等式及回归参数的显著性检验和相对平均误差检验,模型预测值与实测值的相对误差平均值均小于10%,建立的回归模型满足精度要求。
In order to determine the running speed characteristics and operating speed value of the exit passenger car of express interchange lane, ensure that the running speed of the bus is coordinated and controllable in the connecting section so as to make the vehicle run safely. When analyzing the running speed of the exit passenger car of expressway interchange Based on the measured data, we can get the running law of the vehicle at the exit. The velocity of exit passenger cars was collected in real time by using Chain Kepler radar velocimeter, and the speed of minibuses in free flow state at eight ramp characteristics (gradient start, diversion and little nose) was selected as the analysis sample. KS After the test, the samples were tested for normal distribution. After satisfying the inspection requirements and analyzing the characteristics of velocity and acceleration of the gradient and deceleration sections, the parameters of the variables were determined. Finally, SPSS software was used to carry out the regression. Point running speed prediction model, and using four ramp data to verify the model. The results show that the running speed of the vehicle at the shunt point increases with the starting speed of the gradient section and decreases with the length of the gradient section. The running speed of the vehicle with small nose increases with the starting speed of the gradient section. Length, the length of the gradient section and the length of the deceleration section r decreases; the prediction model passed the regression equation and regression analysis of significant parameters and the relative average error test, the model predicted value and the measured value of the relative error average Less than 10%, the regression model established to meet the accuracy requirements.