【作者】 翟晓峰；

【导师】 李星毅；

【作者基本信息】 江苏大学 ， 计算机应用技术， 2007， 硕士

【摘要】 随着经济的发展,城市化水平的提高,交通问题也日趋严重。尤其在一些大城市,交通拥挤、环境污染等已经成为制约经济发展、亟待解决的重要问题。智能交通系统是解决城市交通问题公认的最好的方法。车辆诱导系统是智能交通系统中的一个重要方面,旨在通过向驾驶员提供基于实时交通信息的最佳行驶路线来达到诱导出行行为,减少车辆在道路上的逗留时间,避免交通拥挤、阻塞现象,从而改善城市交通状况的目的。文章主要对车辆诱导系统的结构框架、实施框架以及若干关键技术进行了研究。本文的主要工作如下:1.介绍了国内外几种具有代表性的车辆诱导系统,总结了当前的研究现状,并对车辆诱导系统的研究内容、构成和分类进行了讨论。在对各个功能模块进行分析的基础上给出了符合中国国情的车辆诱导系统结构框架及实施框架。2.行程时间预测是车辆诱导系统中最重要的问题之一。对现有的几种行程时间预测方法及近年来所做出的一些研究进行了分析,指出这些方法普遍过于追求预测的准确性,而忽视了算法的实用性。为此,给出一种基于车牌自动识别系统的行程时间预测模型。该模型使用四分位异常数据剔除的方法对观测到的行程时间进行预处理;在对指数平滑方法进行分析的基础上,给出了等参数模型和等参数比例模型两种行程时间预测方法。最后,用某城市的交通实测数据对该模型进行验证,实验结果表明该模型有较好的预测效果,算法简单实用、易于推广。3.路径优化是车辆诱导系统中的一个关键功能,路径选择的好坏直接影响着诱导的效果。城市交通网络中路径行程时间是随着时间的变化而变化的,因此最小时间路径求解比较困难,传统的一些最短路径求解方法都无法直接应用。为此,提出把交通网络抽象为时间依赖的网络模型的解决方法。在对时间依赖网络模型和理论基础进行分析的基础上给出最小时间路径算法,并通过实验验证了算法的正确性和有效性。更多还原

【Abstract】 Along with the economical development, the urbanized level enhancement, the transportation question day by day is also serious. Especially in some big cities, traffic congestion, the environmental pollution and so on, the questions which caused already becomes urgently awaited to be solved which restricts economy development. The study on the vehicles guidance system is an important research in the field of Intelligent Transportation System, which guide the behaviors of travelers by providing them with optimal route based on real-time traffic information. As the result the travel time can be saved and the traffic congestion can be avoid. The article studied on the framework and the key technology of the vehicles guidance system.The main working content as follows:1. Several kind representative vehicles guidance system in the domestic and foreign was introduced and the current study present situation was summarized. The working content, constitution and classification of the vehicles guidance system were discussed. Based on the analysis to each function module, conformed to the Chinese national condition vehicles guidance system framework was presented.2. The prediction of link travel time is one of the most important questions of the vehicles guidance system. The accuracy vehicles guide need the real-time prediction to link travel time, and the accuracy vehicles guide depend on the prediction accurately. Several kinds of prediction method was introduction and some study based on which was analyzed. Based on the data collected by the license auto-recognition system, an algorithm for predicting travel time is proposed. The algorithm makes the moving exponential average model as the foundation, depend on the history travel time data to predict the link travel time in future times. The method is proved to be sample and efficient by experiments and practical application.3. The route optimization is an essential function of the vehicles guidance system. As the time is changing, the travel time is also changing in traffic network. So shortest path search becomes considerably more difficult. Some traditional method for searching the shortest path was disabled in time-dependent networks. For solve the problems, many transportation systems can be represented by networks with travel times that are time-dependent. Based on the analyses to time-dependent networks and its theoretical foundations, a new shortest path algorithm is presented. The algorithm is proved to be correct and efficient by experiments and practical application. The shortest path algorithm in time-dependent networks has a broad application fields.更多还原