【摘要】 车辆换道过程对交通安全和交通拥堵有重要影响,为了获得不同驾驶人的换道行为特性,考虑了车辆换道过程中驾驶人的因素,利用SPSS对问卷调查的结果进行主成分分析,采用K-均值聚类方法对驾驶风格进行量化,将驾驶人分为激进型和保守型两种类型,再利用时间对数模型提出了驾驶风格值变量。对两组类型驾驶人进行换道试验,获得了不同风格驾驶人换道时间和换道纵向距离等换道特性的试验数据,并建立了考虑驾驶风格的车辆换道时间预测模型;基于预测的换道时间以及换道车辆转向角与驾驶风格值变量、速度之间的关系,结合车辆运动学模型,建立了车辆换道纵向距离预测模型,并将预测结果与实际换道数据进行了对比分析,结果表明,本研究提出的预测模型准确率较高。研究结果表明,激进型驾驶人在换道过程中其行为较为激进,换道时间较短,换道距离较短;所建立的预测模型可以较准确地预测和解释驾驶人的换道行为。更多还原

【Abstract】 The lane-changing process exerts a significant impact on traffic safety and urban congestion issues.Drivers’ different driving styles were considered in lane-changing characteristics analysis.Results of the questionnaires were first examined by SPSS,quantifying different driving styles via principal component analysis(PCA).Drivers were then categorized into two types:aggressive type and conservative type,using K-means clustering method.Vehicle trajectory data were collected separately for each driver type(aggressive and conservative),and fitted by polynomial models with high goodness of fit.Further,prediction models for lane-changing process were also furnished in both temporal and spatial fashion.A time-logarithmic model considering driving style factor was developed to predict lane-changing time,as well as a longitudinal distance prediction model.Results manifest high accuracy of the prediction models developed in this paper compared with the experimental data.更多还原