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电子不停车收费系统是智能交通应用系统中取得较大发展的子系统. 系统能实时记录车辆的进、出口收费站的时间、地点等数据. 本文以电子不停车收费的交易数据为基础，通过对原始交易数据的分析，确定了数据的处理流程，在此基础上，提出了路段行程速度计算模型，交通流量分布规律分析方法和高速公路站点OD分布、车型比例分布等指标获取方法. 研究以北京市高速公路电子收费数据为例，进行了案例分析. 结果表明，本研究中提出的数据处理和提取技术能较为准确地获取高速公路运营管理中所需的信息，这些信息为高速公路出行者信息服务、高速公路交通运营和规划等提供有效的信息支撑.

ETC Data Based Traffic Information Mining Techniques

The electronic toll collection (ETC) system is an importation subsystem in the intelligent transportation system (ITS).It can continuously record the time of vehicles entering or departuring from the certain toll station.Based on the charge transaction data of ETC system,this paper analyzed the original data and determined the data processing flow of ETC Data.Then,it proposed the travel speed calculation model of freeway,the traffic flow distribution analysis method,the information mining techniques of OD distribution,vehicle type proportion in different toll gate,and so on.The research finally took the ETC data of Beijing city in 2008 as an example,and carried a case analysis.The result indicated that the data processing and the index extraction techniques can accurately gain the information which is necessary in the freeway operation and management.These provide effective decision-making support for the freeway travelers' information service and the highway tragic operation and the plan.