發(fā)布時間：2018-10-09 17:53

【摘要】：近年來,世界經(jīng)濟(jì)的飛速發(fā)展促進(jìn)了城市化的步伐,隨之而來的是城市交通擁堵的問題,這個問題制約了城市經(jīng)濟(jì)的發(fā)展,因此,緩解交通擁堵和提高交通運輸能力已經(jīng)是迫在眉睫的事情。而傳統(tǒng)的控制方法在處理復(fù)雜的交通問題方面己經(jīng)顯的無能為力。為此,需要一些新的技術(shù)和手段從根本上來解決交通問題,智能交通系統(tǒng)是目前解決這一問題的有效方法。 以城市區(qū)域的交通信號控制為研究對象,利用模糊邏輯、神經(jīng)網(wǎng)絡(luò)等智能控制方法,對城市交通信號控制展開研究,以緩解城市交通擁堵,提高交通運輸效益。 對城市單交叉口多相位的模糊控制進(jìn)行了分析研究,在此基礎(chǔ)上,結(jié)合交通流的特點設(shè)計了一種單交叉口兩級模糊控制方法。在單交叉口信號控制的基礎(chǔ)上,綜合考慮多個交叉口之間的關(guān)聯(lián),設(shè)計了一種針對區(qū)域內(nèi)多交叉口的協(xié)調(diào)模糊控制方法,該方法以交叉口車輛的平均延誤作為信號控制的性能評價指標(biāo),綜合考慮相鄰交叉口之間道路上車輛的排隊長度、各交叉口車輛的平均達(dá)到率等因素,以此來決定相位的切換順序和綠燈分配時間,仿真結(jié)果驗證了協(xié)調(diào)模糊控制的有效性。 以交通流數(shù)據(jù)為基礎(chǔ),利用模糊神經(jīng)網(wǎng)絡(luò)對城市區(qū)域多交叉口的信號控制進(jìn)行建模。模糊神經(jīng)網(wǎng)絡(luò)由模糊邏輯和神經(jīng)網(wǎng)絡(luò)有機(jī)結(jié)合而成,吸取了二者的優(yōu)勢,彌補了各自的缺點,有效地提高了整個系統(tǒng)對知識的學(xué)習(xí)和表達(dá)能力。仿真結(jié)果表明將其應(yīng)用于區(qū)域多交叉口的信號控制取得了比較好的效果。
[Abstract]:In recent years, the rapid development of the world economy has promoted the pace of urbanization, followed by the problem of urban traffic congestion, which restricts the development of urban economy. It is urgent to alleviate traffic congestion and improve transportation capacity. However, the traditional control method has been powerless in dealing with complex traffic problems. Therefore, some new technologies and methods are needed to solve the traffic problem fundamentally. Intelligent Transportation system is an effective method to solve this problem. Taking the traffic signal control in the urban area as the research object, using the intelligent control methods such as fuzzy logic and neural network, the paper studies the urban traffic signal control in order to alleviate the urban traffic congestion and improve the transportation efficiency. Based on the analysis and study of multi-phase fuzzy control of urban single intersection, a two-stage fuzzy control method is designed based on the characteristics of traffic flow. On the basis of single intersection signal control and considering the correlation between multiple intersections, a coordinated fuzzy control method for multi-intersection in the region is designed. In this method, the average delay of vehicle at intersection is taken as the performance evaluation index of signal control, and the factors such as the queue length of vehicles on the road between adjacent intersections and the average rate of achievement of vehicles at each intersection are considered synthetically. The phase switching order and the green light allocation time are determined. The simulation results show the effectiveness of the coordinated fuzzy control. Based on the traffic flow data, the fuzzy neural network is used to model the signal control of multiple intersections in urban areas. Fuzzy neural network is an organic combination of fuzzy logic and neural network, which absorbs the advantages of both, makes up for their shortcomings, and effectively improves the ability of the whole system to learn and express knowledge. The simulation results show that the application of this method to regional multi-intersection signal control has achieved good results.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U491.54

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 梁久禎,許少華,張建,付麗萍;模糊神經(jīng)元網(wǎng)絡(luò)的統(tǒng)一模型[J];大慶石油學(xué)院學(xué)報;2000年04期

2 邱偉康;王偉智;;基于模糊神經(jīng)網(wǎng)絡(luò)的交通信號控制[J];江蘇電器;2008年04期

3 劉智勇;宋正東;;城市區(qū)域交通信號的混沌模糊Q學(xué)習(xí)控制[J];計算機(jī)工程與應(yīng)用;2012年04期

4 徐啟華,胡建華,富巍;基于模糊神經(jīng)網(wǎng)絡(luò)的道路交叉口交通控制方法[J];計算機(jī)工程;2004年14期

5 張浩炯,余岳峰,王強(qiáng);應(yīng)用自適應(yīng)神經(jīng)模糊推理系統(tǒng)(ANFIS)進(jìn)行建模與仿真[J];計算機(jī)仿真;2002年04期

6 張輝;陳陽舟;楊玉珍;李世偉;;基于Multi-Agent的區(qū)域交通協(xié)調(diào)控制研究[J];交通與計算機(jī);2006年02期

7 李群祖;夏清國;巴明春;潘萬鵬;;城市交通信號控制系統(tǒng)現(xiàn)狀與發(fā)展[J];科學(xué)技術(shù)與工程;2009年24期

8 于萬霞;杜太行;鄭宏興;;基于粒子群的模糊神經(jīng)網(wǎng)絡(luò)交通信號控制[J];微計算機(jī)信息;2008年07期

9 陳森發(fā),陳洪,徐吉謙;城市單路口交通的兩級模糊控制及其仿真[J];系統(tǒng)仿真學(xué)報;1998年02期

10 許倫輝,衷路生,徐建閩;基于神經(jīng)網(wǎng)絡(luò)實現(xiàn)的交叉口多相位模糊邏輯控制[J];系統(tǒng)工程理論與實踐;2004年07期

相關(guān)博士學(xué)位論文 前2條

1 孔祥杰;城市路網(wǎng)交通流協(xié)調(diào)控制技術(shù)研究[D];浙江大學(xué);2009年

2 張良智;城市區(qū)域交通控制技術(shù)研究[D];山東大學(xué);2013年

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本文編號：2260235