高速公路平纵组合路段运行速度预测研究

发布时间：2018-07-02 10:30

本文选题：高速公路 + 平纵组合路段　；参考：《哈尔滨工业大学》2014年硕士论文

【摘要】：诱导道路交通事故发生的因素有许多种，其中不良的公路线形条件往往是造成交通事故发生的主要原因之一。在对公路线形的连续性、一致性和舒适性等指标进行评价中，，运行速度是重要的参考标准。运行速度作为各线形指标综合作用的结果，对其开展相关研究，建立运行速度预测模型，对于指导公路几何线形设计以及后续的安全性评价等工作均具有重要的理论意义与应用价值。论文结合实际工程项目，以设计速度为100km/h的高速公路为研究对象，对高速公路上平纵组合路段的运行速度开展了预测研究工作。首先，论文选取广东省粤赣高速公路广东省境内段作为数据采集地点，制定了数据采集和提取方案。根据运行速度的定义，自由流交通状态是运行速度的前提条件。通过对车头时距与实测车速的关系分析，结合国内外学者在自由流状态判定方面的研究成果，提出了基于车头时距的自由行驶状态的判定准则，研究分析得出在车头时距不小于6s的情况下，车辆处于自由行驶状态。基于该准则提取了自由流状态下的实测车速数据，计算出各调查路段上的运行速度。在得到各调查路段运行速度数据的基础上，分析了公路线形指标对运行速度的影响，研究结果表明平曲线半径与公路纵坡这两个线形指标对运行速度的影响较大，其中小客车运行速度主要受到平曲线半径的影响，而公路纵坡则对大货车的运行速度影响较显著。为了建立基于道路线形指标的高速公路平纵组合路段运行速度预测模型，论文选取平曲线半径、公路纵坡以及平曲线偏角这三个线形要素作为影响变量，采用多元线性回归分析的统计方法分别对小客车和大货车的运行速度预测模型进行了标定，并对模型的合理性进行了理论分析。然后，运用模糊逻辑理论对高速公路上平曲线与纵坡组合路段的运行速度进行了研究分析。将平曲线半径、公路纵坡以及平曲线偏角作为输入变量，小客车和大货车的运行速度作为输出变量，基于模糊统计原理获得了预测模型所有变量的模糊集合和聚类中心，以及各输入变量和输出变量对应的隶属函数，从而建立了基于模糊逻辑的运行速度预测模型，通过对模型的检验与分析最终得出采用模糊逻辑对运行速度进行预测研究其预测结果同样可靠。最后，以未参与模型构建的运行速度实测数据为基础，对基于两种方法的运行速度预测模型的预测结果进行了对比分析，研究结果表明，两种预测模型均可用于预测高速公路平曲线与纵坡组合路段的平均运行速度。
[Abstract]:There are many kinds of factors inducing road traffic accidents, among which poor road alignment is one of the main causes of traffic accidents. In evaluating the continuity, consistency and comfort of highway alignment, the running speed is an important reference standard. As the result of the comprehensive action of various linear indexes, the running speed is studied, and the prediction model of running speed is established. It has important theoretical significance and application value for guiding highway geometric alignment design and subsequent safety evaluation. Based on the actual project and taking the design speed of the expressway as the research object, this paper makes a prediction study on the running speed of the horizontal and longitudinal combination section on the expressway. Firstly, the paper selects Guangdong Guangdong province expressway as the data acquisition site, and formulates the data acquisition and extraction scheme. According to the definition of running speed, free flow traffic condition is the precondition of running speed. Based on the analysis of the relationship between the head-time distance and the measured speed, combined with the research results of the scholars at home and abroad in the determination of the free flow state, the criterion of judging the free driving state based on the head-time distance is put forward. The research and analysis show that the vehicle is in the state of free running when the headspace is not less than 6 s. Based on this criterion, the measured speed data under free flow state are extracted, and the running speed of each section of investigation is calculated. On the basis of obtaining the running speed data of each investigation section, the influence of highway alignment index on running speed is analyzed. The results show that the radius of plane curve and the longitudinal slope of highway have great influence on the running speed. The running speed of passenger cars is mainly affected by the radius of the plane curve, while the longitudinal slope of the highway has a significant effect on the running speed of large freight cars. In order to establish the speed prediction model of highway horizontal and vertical combination section based on road alignment index, this paper selects three linear elements, namely, the radius of the plane curve, the longitudinal slope of the highway and the deflection angle of the horizontal curve, as the influence variables. Using the statistical method of multiple linear regression analysis, the prediction models of the running speed of passenger cars and freight cars are calibrated, and the rationality of the model is analyzed theoretically. Then, using fuzzy logic theory, the running speed of the combination of horizontal curve and longitudinal slope on expressway is studied and analyzed. Taking the radius of plane curve, longitudinal slope of highway and deflection angle of plane curve as input variables, and the running speed of minibus and truck as output variables, the fuzzy set and cluster center of all variables of prediction model are obtained based on fuzzy statistical principle. And the corresponding membership function of each input variable and output variable, thus the speed prediction model based on fuzzy logic is established. Finally, it is concluded that the fuzzy logic is used to predict the running speed and the prediction results are equally reliable through the examination and analysis of the model. Finally, based on the measured data of running speed which is not involved in the construction of the model, the prediction results of the two methods are compared and analyzed. The results show that, The two prediction models can be used to predict the average running speed of the combination of highway plane curve and longitudinal slope.
【学位授予单位】：哈尔滨工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491

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