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基于模糊识别的城市交通拥堵预测方法研究

时间:2019-02-20 15:24来源:毕业论文
基于模糊识别的城市交通拥堵预测方法,旨在对于某一路段的交通流参数进行分析识别,根据相应等级道路的通行能力建立模糊识别模型进行模糊识别,判断道路此时处于怎样的交通状

摘要近些年来,我国社会和经济飞速发展,带动了城市规模的急剧扩张,机动车保有量逐年增长,然而城市规模的扩张与道路建设的速度远远落后于机动车的增长速度,现有的交通设施满足不了人们的交通需求,大中城市普遍存在或轻或重的交通拥堵问题。交通拥堵会增加出行者的出行时间出行成本,导致出行者心理焦虑增加交通事故的概率, 影响城市工作效率增加额外的社会成本并且会带来严重的城市环境污染等问题,这些都会制约一个城市的发展。如何解决交通拥堵,提高工作效率,降低社会成本是一个城市想要发展首先需要解决的问题。33407
    本文提出基于模糊识别的城市交通拥堵预测方法,旨在对于某一路段的交通流参数进行分析识别,根据相应等级道路的通行能力建立模糊识别模型进行模糊识别,判断道路此时处于怎样的交通状态,然后建立灰色预测模型,利用之前所测得的交通流参数预测出此道路下一时间段的交通流,得出对应数据再通过模糊识别模型进行判别,根据模型判别的结果预测出道路下一时间段的交通状态是畅通,正常,拥挤还是堵塞。从而就可以作出相应的处理措施来疏导交通或者将信息发布给交通出行者自行选择合适路线,以达到缓解交通避免堵塞的目的。
关键词  交通拥堵  模糊识别  灰色预测
 毕业论文设计说明书外文摘要
Title  Urban traffic congestion prediction method based on fuzzy recognition
Abstract
In recent years, China's rapid social and economic development, led to the rapid expansion of city size, the vehicle population growth year after year, however, the speed of expansion and road construction is far behind urban scale growth of motor vehicles, the existing traffic transportation facilities can not meet the needs of the people, the prevalence of cities or light or heavy traffic congestion. Traffic congestion will increase travel time travelers travel costs, resulting in psychological anxiety increased travel accident probability, affect the efficiency of the city's social costs extra and will bring serious urban environmental pollution and other issues.

源`自*六)维[论*文'网www.lwfree.cn


In this paper, urban traffic congestion prediction method based on fuzzy recognition, aims for a certain section of the traffic flow parameters were analyzed to identify, establish fuzzy fuzzy recognition model to identify the appropriate level according to the capacity of the road, the road at this time to determine what kind of transportation in the state and then establish the gray prediction model of traffic flow parameters measured prior to use to predict the traffic flow of this road to the next period of time, then the corresponding data obtained by the fuzzy recognition model discrimination, discrimination based on the results of the model to predict the path of the next traffic state period is smooth, normal, congestion or blockage. So you can make the appropriate measures to deal with the flow of traffic or the information released to the transportation of travelers choose the right route to achieve the purpose of easing traffic to avoid clogging.
Keywords  traffic congestion gray prediction fuzzy recognition
 目  次
第1章 绪论    1
1.1 选题背景    1
1.2 研究目的和意义    1
1.3 国内外研究背景    3
第2章 交通拥堵相关理论    6
2.1 拥堵的定义及分类    6
2.2 拥堵的成因及特征    6
2.3 经典的拥堵识别算法    6
第3章 城市交通拥堵模糊识别模型    9
3.1 道路交通状态模糊分类    9
3.2 模糊理论的识别算法    9 基于模糊识别的城市交通拥堵预测方法研究:http://www.lwfree.cn/zidonghua/20190220/30502.html
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