發(fā)布時(shí)間：2018-10-09 17:53

【摘要】：近年來(lái),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(lái)的是城市交通擁堵的問(wèn)題,這個(gè)問(wèn)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(yùn)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(wèn)題方面己經(jīng)顯的無(wú)能為力。為此,需要一些新的技術(shù)和手段從根本上來(lái)解決交通問(wèn)題,智能交通系統(tǒng)是目前解決這一問(wèn)題的有效方法。 以城市區(qū)域的交通信號(hào)控制為研究對(duì)象,利用模糊邏輯、神經(jīng)網(wǎng)絡(luò)等智能控制方法,對(duì)城市交通信號(hào)控制展開(kāi)研究,以緩解城市交通擁堵,提高交通運(yùn)輸效益。 對(duì)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(diǎn)設(shè)計(jì)了一種單交叉口兩級(jí)模糊控制方法。在單交叉口信號(hào)控制的基礎(chǔ)上,綜合考慮多個(gè)交叉口之間的關(guān)聯(lián),設(shè)計(jì)了一種針對(duì)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(chē)輛的平均延誤作為信號(hào)控制的性能評(píng)價(jià)指標(biāo),綜合考慮相鄰交叉口之間道路上車(chē)輛的排隊(duì)長(zhǎng)度、各交叉口車(chē)輛的平均達(dá)到率等因素,以此來(lái)決定相位的切換順序和綠燈分配時(shí)間,仿真結(jié)果驗(yàn)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(duì)城市區(qū)域多交叉口的信號(hào)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(shì),彌補(bǔ)了各自的缺點(diǎn),有效地提高了整個(gè)系統(tǒng)對(duì)知識(shí)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(hào)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(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：U491.54

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