为研究快速路入口匝道汇入行为，首先对交织区全范围的汇入位置进行采集，然后通过聚类分析将汇入行为分为前段汇入、中段汇入、末段汇入三种。采用5种分布模型对各类行为的汇入位置进行拟合，通过最大似然估计法确定模型参数并进行Kolmogorov-Smirnov拟合优度检验，得到前段汇入符合Johnson SB模型，中段汇入符合Log-logistic模型，末段汇入符合Gen.extreme.value模型。最后，建立汇入位置分布与主路外侧车道密度、匝道车辆合并速度间的关系模型。敏感性分析的结果表明同一类别的汇入位置分布受密度、速度的影响显著。

A field survey was first conducted to collect merging information of on-ramp vehicles at urban expressway. Then clustering analysis was used to divide merging maneuvers into three clusters: the forepart, the midpiece and the endpiece. Five distribution models were selected to fit the distribution of merging positions in each cluster. Model parameters were determined by maximum likelihood estimation, and the goodness of fit to these models was also given by Kolmogorov-Smirnov test. It was found that the Johnson SB model obtains the best result in the forepart cluster, the Log-logistic model is the most suitable for the midpiece merging maneuvers, and the Gen. extreme. value model provides the best fit for the endpiece cluster. At last, a regression model was proposed to describe the relationship among the distribution of merging positions, the density of the shoulder lane, the merging velocity of an on-ramp vehicle. The result of sensitivity analysis shows that the density and the velocity have significant effect on the distribution of merging position in the same cluster.