發(fā)布時(shí)間：2018-05-27 22:20

  本文選題：單交叉口 + 多交叉口��； 參考：《南京郵電大學(xué)》2014年碩士論文

【摘要】：隨著城市化水平的提高，機(jī)動(dòng)車數(shù)量急劇增加，，城市交通擁堵問題日益嚴(yán)重，傳統(tǒng)的交通信號(hào)控制方式已經(jīng)不能獲得良好的控制效果。因此，智能交通信號(hào)控制成為了主要控制手段。利用進(jìn)化算法進(jìn)行交通信號(hào)優(yōu)化控制是一種有效途徑，但其在收斂精度和收斂速度方面還有待改進(jìn)。協(xié)同進(jìn)化算法作為一種新型智能算法，由于其具有高度的協(xié)調(diào)性，在智能交通信號(hào)控制領(lǐng)域已嶄露頭角。本文對協(xié)同進(jìn)化算法進(jìn)行了改進(jìn)，將其用于交通信號(hào)控制，取得了良好的效果。 本文結(jié)合精英策略、協(xié)同進(jìn)化思想和模擬退火機(jī)制，提出了一種基于模擬退火機(jī)制的精英協(xié)同進(jìn)化算法（SACEA），將其應(yīng)用到交通信號(hào)控制領(lǐng)域。算法維持三個(gè)種群：精英種群、普通種群和隨機(jī)種群，精英個(gè)體組團(tuán)，并和其他組員個(gè)體協(xié)作或?qū)ζ湟龑?dǎo)來達(dá)到進(jìn)化目的。算法在精英組團(tuán)過程中引入隨機(jī)種群以增加種群多樣性，同時(shí)隨機(jī)個(gè)體和精英個(gè)體的合作采用快速模擬退火機(jī)制來實(shí)現(xiàn)，使算法獲得了更好的全局尋優(yōu)性和更快的收斂速度。本文通過實(shí)驗(yàn)驗(yàn)證了算法的有效性。 本文在觀察研究單交叉口車流量分布特性的基礎(chǔ)上，分別建立了以單交叉口的平均延誤最小和平均停車率最小為目標(biāo)的兩個(gè)單交叉口信號(hào)控制模型。在此基礎(chǔ)上利用SACEA算法對兩個(gè)模型各自進(jìn)行優(yōu)化配時(shí)仿真，并和已有優(yōu)化算法進(jìn)行對比，結(jié)果表明:利用SACEA算法進(jìn)行優(yōu)化更能減少單交叉口平均延誤時(shí)間和平均停車率。 在分析了城市干線協(xié)調(diào)控制理論的基礎(chǔ)上，本文以一個(gè)綠波系統(tǒng)為例，以車輛通過干線所需平均總共時(shí)間（平均行程時(shí)間和總平均延誤時(shí)間之和）為控制目標(biāo)，進(jìn)一步利用SACEA算法進(jìn)行了多交叉口配時(shí)優(yōu)化，并與已有算法進(jìn)行對比，結(jié)果表明：利用SACEA算法進(jìn)行優(yōu)化更能減少車輛通過干線所需時(shí)間。
[Abstract]:With the improvement of urbanization level, the number of motor vehicles has increased rapidly, traffic congestion in cities is becoming more and more serious, and the traditional traffic signal control methods have been unable to obtain good control effect. Therefore, intelligent traffic signal control has become the main control means. But it still needs to be improved in the convergence precision and convergence speed. As a new intelligent algorithm, coevolution algorithm has come to the fore in the field of intelligent traffic signal control because of its high coordination. This paper has improved the coevolution algorithm and applied it to the communication signal control, which has achieved good results.
In this paper, combining elite strategy, coevolutionary thought and simulated annealing mechanism, an elite cooperative evolution algorithm (SACEA) based on simulated annealing mechanism is proposed, which is applied to the field of traffic signal control. The algorithm maintains three populations: Elite population, ordinary population and random species group, elite individual groups, and collaborating with other group individuals. The algorithm introduces the random population to increase the population diversity in the elite group process, and the cooperation of the random and elite individuals adopts the fast simulated annealing mechanism to achieve better global optimality and faster convergence speed. This paper proves the effectiveness of the algorithm by experiments. Sex.
On the basis of observing the flow distribution characteristics of the single intersection vehicle, this paper sets up two single intersection signal control models with the goal of the minimum average delay and the minimum average parking rate of the single intersection. On this basis, the SACEA algorithm is used to optimize the timing simulation of the two models respectively, and the optimization algorithm is carried out with the existing optimization algorithms. The results show that the optimization of SACEA algorithm can reduce the average delay time and average parking rate of single intersection.
On the basis of the analysis of the coordinated control theory of urban trunk lines, this paper takes a green wave system as an example, taking the average total time (average travel time and the sum of the average delay time) as the control target by the vehicle through the trunk line, and further optimizes the timing of the multiple intersection using the SACEA algorithm, and compares the results with the existing algorithms. It shows that using SACEA algorithm to optimize can reduce the time required for vehicles to pass through the main road.
【學(xué)位授予單位】：南京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U491.54;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 孟偉;韓學(xué)東;洪炳昒;;蜜蜂進(jìn)化型遺傳算法[J];電子學(xué)報(bào);2006年07期

2 樊曉珂;;城市交通擁堵問題研究[J];中國公共安全(學(xué)術(shù)版);2007年01期

3 鄭長江,王煒;混合交通流條件下信號(hào)交叉口配時(shí)優(yōu)化設(shè)計(jì)[J];公路交通科技;2005年04期

4 袁晶矜;袁振洲;;信號(hào)交叉口服務(wù)水平評(píng)價(jià)體系指標(biāo)的分析及應(yīng)用[J];公路交通技術(shù);2006年04期

5 李淑華;我國城市交通擁堵成因及對策初探[J];中國人民公安大學(xué)學(xué)報(bào)(自然科學(xué)版);2003年03期

6 張昌祿;翟潤平;;交通干線信號(hào)協(xié)調(diào)控制方法綜述[J];中國人民公安大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年01期

7 梁杰;徐建閩;;周期不同的多交叉口協(xié)調(diào)控制方法[J];公路交通科技;2013年08期

8 萬偉;陳鋒;;基于遺傳算法的單交叉口信號(hào)優(yōu)化控制[J];計(jì)算機(jī)工程;2007年16期

9 應(yīng)偉勤;李元香;SHEU Phillip C-Y1;吳昱;余法紅;;演化多目標(biāo)優(yōu)化中的幾何熱力學(xué)選擇[J];計(jì)算機(jī)學(xué)報(bào);2010年04期

10 張?zhí)m;雷秀娟;馬千知;;基于粒子群優(yōu)化算法的多交叉口信號(hào)配時(shí)[J];計(jì)算機(jī)應(yīng)用研究;2010年04期

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