交通流状态辨识系统集成研究

The Integration of Traffic Flow State Recognition System

交通流状态辨识是智能运输系统,尤其是其先进的交通管理系统和先进的出行者信息系统研究的一项重要内容。对道路交通流状态进行分析研究,深入挖掘交通流动态信息,及时、准确地辨识未来和实时交通流状况,是制定正确诱导和控制措施的一个重要前提。根据我国制定的"国家智能运输系统体系框架",以动态交通管理为基本思想,构建了交通流状态辨识系统框架。介绍了在交通流状态辨识中所采用的一些新技术,利用实测数据以及交通仿真系统VISSIM的模拟数据分别对所建立的算法进行验证,结果表明本文所建立的算法和模型具有较好的性能,为交通流状态辨识提供了新的研究方法。

Traffic flow state recognition is one of the important issues of Intelligent Transportation Systems （ITS）, especially Advanced Traffic Management Systems （ATMS） and Advanced Traveler Information Systems （ATIS）. As an important prerequisite for taking correct measures, it is necessary to analyze road conditions, evaluate dynamical traffic information, and identify the future and real-time traffic states under different conditions timely and accurately. According to the structure of Intelligent Transportation System in our country, based on the basic concepts of dynamical traffic management, a framework of traffic state recognition system is proposed. In presenting the traffic state recognition system, the paper puts the emphasis on the key nonparametric theory and methods used in the system. Related algorithms were tested with the field data and simulation data from the traffic simulation system software VISSIM, and the results indicate that these algorithms and models enjoy good performance and can be used for the development of the traffic state recognition system.