目前高速公路交通数据资源未得到充分利用，使得管理和建设成本较高的高速公路联网收费系统只能实现车辆记录、联网收费等初级功能，导致交通数据资源的严重浪费． 为此设计了基于高速公路联网收费数据的路段行程时间估计方法，提出以大、小车速度变化情况为基础，采用模糊 C-均值聚类方法对高速公路交通状态进行判别，并应用VISSIM 软件分别对上述两种方法验证分析． 结果表明，路段行程时间估计方法能够获得高质量的路段行程时间数据，同时交通状态判别方法也能够准确判别出道路上所呈现的交通状态，可为历史数据更新提供技术支持，为高速公路交通管理部门提供精确的决策依据．

Current freeway traffic data resources have not been fully utilized,and therefore the freeway toll systemwith high management and construction costs only has such primary functions as collecting traffic information vehiclerecord and network toll,which leads to a great waste of traffic data resources.In order to solve this problem,atravel time estimation method is designed based on freeway network toll data,and the FCM(Fuzzy C-Means)cluste-ring method is adopted to identify the freeway traffic state according to the velocity changes of big and small vehi-cles.Then,the two methods are verified on the VISSIM platform.The results show that the first method can obtainhigh-quality link travel time data and the second method can accurately identify the freeway traffic state,whichhelps to update history data and can provide an accurate basis for freeway management departments to make deci-sions.