The Analysis of Route Choice Behavior by Fuzzy Reasoning Approach

模糊推理方法的路径选择行为分析

基本信息

批准号：
07650619
负责人：
AKIYAMA Takamasa
金额：
$ 1.41万
依托单位：
Gifu University
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07650619/
关键词：
Fuzzy Reasonig Route Choice Behavior Neural Networks Trafic Information Service Urban Road Networks Fuzzy Neural Networks Genetic Algorithm Path Flow 三角型ファジィ数交通情報多段推論簡略ファジィ推論交通行動分析

项目摘要

The route choice model with fuzzy reasoning is considered to be developed and applied to the traffic information service. The main research results are summarized as follows in the order of the research procedure :1) The primitive survey to describe the route choice phenomena on the urban road network is done. The route choice model with fuzzy reasoning is provided using the data. The factors of route choice associated with traffic information are gathered and the knowledge based rules for the route choice are created with the linguistic expressions. The primitive model is established with referring to the related research results about T-norms and defuzzification.2) The fuzzy reasoning model is practically modified. The simplified model is introduced to promote the efficiency of calculation in forecasting the path flows. And also the multi-stage fuzzy reasoning is introduced to describe sequential decision steps. The proper type of fuzzy reasoning model (FL model) is proposed with the … More se improvements and the impacts of traffic information to the flows are considered.3) The estimation of the membership functions is discussed as a disadvantage of the FL model. The genetic algorithm may be used to estimate the parameters because the FL model involves non-linear calculating process. The parameters are obtained with considering the errors between real values and estimated values.4) The model with fuzzy reasoning for route choice description is established with linguistic expressions. However, the crisp value estimation is recommended for the practical estimation of the path flows. The neural network model with error back propagation is introduced to modify at this point. The fuzzy reasoning model with neural network in conclusions of the rules are proposed as a hybrid model.5) The several similar techniques are summarized as "soft computing" and their advantages to construct the travel behavior models are discussed. Furthermore, the effective use of the models to traffic information management is mentioned. The transforming the traffic information and information service are analyzed precisely. The result shows the proper way of information provision on urban transport networks.6) The research results are summarized and reported in the several conferences and the further discussions are recommended. The some remarks are also planned to be reported the international and domestic conferences related with civil engineering. Less

具有模糊推理的路线选择模型被认为是开发并应用于交通信息服务的。主要的研究结果总结如下研究程序的顺序：1）原始调查描述了城市道路网络上的路线选择现象。使用数据提供带有模糊推理的路由选择模型。收集了与流量信息相关的路线选择因素，并通过参考有关T-norms和Defuzzification的相关研究结果建立了原始模型的知识规则。2）实际上修改了模糊的推理模型。引入了简化的模型，以促进预测路径流的计算效率。还引入了多阶段模糊推理来描述顺序决策步骤。提出了适当的模糊推理模型（FL模型），并考虑了……更多的SE改进和流量信息对流量的影响。3）讨论了成员资格功能的估计，以作为FL模型的灾难进行讨论。遗传算法可用于估计参数，因为FL模型涉及非线性计算过程。通过考虑真实值和估计值之间的误差，可以获得参数。4）用语言表达式建立了具有模糊推理的模型。但是，建议对路径流的实际估计进行清晰的价值估计。此时引入了具有错误反向传播的神经网络模型以修改。在规则的结论中，提出了具有神经元网络的模糊推理模型作为混合模型。5）几种类似的技术总结为“软计算”，并讨论了它们构建旅行行为模型的优势。此外，提到了模型在流量信息管理中的有效使用。精确分析了转换流量信息和信息服务。结果表明，在城市运输网络上提供了适当的信息提供方式。6）总结了研究结果，并在几个会议中进行了报告，建议进一步讨论。一些提醒还计划报告与土木工程有关的国际和国内会议。较少的