【摘要】：交叉口作為城市道路網(wǎng)絡(luò)的節(jié)點(diǎn),在整個(gè)城市網(wǎng)絡(luò)體系中起著至關(guān)重要的作用,城市主干道上交叉口往往會(huì)成為城市交通活動(dòng)的瓶頸,一點(diǎn)不暢可能引發(fā)整條線,甚至整個(gè)路網(wǎng)的連鎖反應(yīng)。對(duì)主干道交叉口節(jié)點(diǎn)的合理控制可以減少擁堵,降低停車延誤,提高通行效率,減少環(huán)境污染。而智能交通技術(shù)的發(fā)展恰是能夠?yàn)榻徊婵谛盘?hào)控制提供一個(gè)良好的優(yōu)化方案。車輛動(dòng)態(tài)誘導(dǎo)系統(tǒng)作為智能交通系統(tǒng)的重要組成部分,已成為交通管理部門疏導(dǎo)城市道路交通的有效途徑,實(shí)時(shí)準(zhǔn)確的流量預(yù)測是實(shí)現(xiàn)動(dòng)態(tài)路徑誘導(dǎo)的基礎(chǔ)和關(guān)鍵。因此,對(duì)城市道路交通流量短時(shí)預(yù)測的研究具有重要意義。傳統(tǒng)預(yù)測方法一般只根據(jù)單交叉口歷史數(shù)據(jù)進(jìn)行預(yù)測,只考慮了時(shí)間因素而忽略了空間聯(lián)系,本文以城市關(guān)聯(lián)交叉口的交通流量預(yù)測為研究內(nèi)容。首先分析和研究了國內(nèi)外針對(duì)交叉口短時(shí)流量預(yù)測的現(xiàn)狀、發(fā)展趨勢和存在的問題。對(duì)交通流預(yù)測中涉及到的數(shù)據(jù)采集、交通流特性、交通預(yù)測原理進(jìn)行簡要闡述。然后對(duì)灰色預(yù)測模型進(jìn)行研究,針對(duì)灰色預(yù)測模型的不足進(jìn)行分析,并進(jìn)行改進(jìn)。論文針對(duì)傳統(tǒng)方法的不足提出將時(shí)間和空間因素綜合考慮,重點(diǎn)研究上下游交叉口流量路徑配比和車輛在路段的行程時(shí)間,根據(jù)關(guān)聯(lián)交叉口之間的空間地理關(guān)系提出在線滾動(dòng)預(yù)測短時(shí)流量的方法,該方法不需要將所有交通量數(shù)據(jù)都予以保存,又保證了預(yù)測的連續(xù)性,提高預(yù)測精度,降低誤差離散程度。結(jié)合現(xiàn)代交通數(shù)據(jù)采集技術(shù),本文提出利用次關(guān)聯(lián)交叉口流量統(tǒng)計(jì)來預(yù)測研究目標(biāo)的交通流量的構(gòu)想。并以成都府城大道-益州大道交叉口與府城大道-成漢南路交叉口為例,驗(yàn)證了模型的精度和可行性。
[Abstract]:Intersection, as the node of urban road network, plays a vital role in the whole urban network system. Intersection on the urban main road often becomes the bottleneck of urban traffic activities, which may lead to the whole line. Even the chain reaction of the whole road network. The reasonable control of the main road intersection can reduce the congestion, reduce the delay of stopping, improve the traffic efficiency and reduce the environmental pollution. The development of intelligent transportation technology can provide a good optimization scheme for intersection signal control. As an important part of intelligent transportation system, vehicle dynamic guidance system has become an effective way for traffic management departments to channel urban road traffic. Accurate and real-time flow prediction is the foundation and key to realize dynamic path guidance. Therefore, it is of great significance to study the short-term prediction of urban road traffic flow. The traditional forecasting method is usually based on the historical data of a single intersection, only considering the time factor and neglecting the spatial relationship. This paper takes the traffic flow prediction of the urban intersections as the research content. Firstly, the present situation, development trend and existing problems of short-time flow prediction at intersections are analyzed and studied. The data acquisition, traffic flow characteristics and traffic forecasting principle are briefly described. Then the grey prediction model is studied, and the shortcomings of the grey prediction model are analyzed and improved. Aiming at the shortcomings of the traditional methods, the paper puts forward that considering the time and space factors, the paper focuses on the proportion of the flow paths of the upstream and downstream intersections and the travel time of the vehicles on the road sections. According to the spatial and geographical relationship between intersections, a method of on-line rolling prediction of short time flow is proposed. The method does not need to save all traffic volume data, and ensures the continuity of prediction and improves the accuracy of prediction. Reduce the degree of error dispersion. Combined with modern traffic data acquisition technology, this paper puts forward the idea of forecasting the traffic flow of the research target by using the traffic statistics of sub-related intersections. The accuracy and feasibility of the model are verified by taking the intersection of Chengdu Fucheng Avenue-Yizhou Avenue and Fucheng Avenue-Cheng Hannan Road as an example.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U491.23

【參考文獻(xiàn)】

中國期刊全文數(shù)據(jù)庫 前10條

1 王珂;田瑞;王菲菲;;基于灰色遺傳支持向量機(jī)的短時(shí)交通流預(yù)測[J];武漢理工大學(xué)學(xué)報(bào)(交通科學(xué)與工程版);2014年05期

2 胡鵬;;數(shù)據(jù)挖掘在交通管理中的應(yīng)用研究[J];計(jì)算機(jī)安全;2013年10期

3 郭海鋒;方良君;俞立;;基于模糊卡爾曼濾波的短時(shí)交通流量預(yù)測方法[J];浙江工業(yè)大學(xué)學(xué)報(bào);2013年02期

4 黨小超;閻林;;基于多元線性自回歸模型的流量預(yù)測[J];計(jì)算機(jī)工程;2012年01期

5 余冰;任莎;歐志梅;何玉花;羅玄;;城市交通擁堵問題研究綜述[J];物流技術(shù);2011年11期

6 隋亞剛;郭敏;;北京市道路交通流仿真與預(yù)測預(yù)報(bào)系統(tǒng)的研究及應(yīng)用[J];道路交通與安全;2010年06期

7 李鴻飛;;城市交通規(guī)劃中路網(wǎng)布局的合理性分析——以蘭州城市交通規(guī)劃理論與實(shí)踐為例[J];城市發(fā)展研究;2008年S1期

8 姚亞夫;曹鋒;;基于ARIMA的交通流量短時(shí)預(yù)測[J];交通科技與經(jīng)濟(jì);2006年03期

9 徐今強(qiáng),劉智勇;交通流的時(shí)間序列建模及預(yù)測[J];五邑大學(xué)學(xué)報(bào)(自然科學(xué)版);2004年03期

10 姜桂艷,Q，

本文編號(hào)：2320768