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

【摘要】：隨著城市化水平的提高，機動車數(shù)量急劇增加，，城市交通擁堵問題日益嚴重，傳統(tǒng)的交通信號控制方式已經(jīng)不能獲得良好的控制效果。因此，智能交通信號控制成為了主要控制手段。利用進化算法進行交通信號優(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。協(xié)同進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，在智能交通信號控制領域已嶄露頭角。本文對協(xié)同進化算法進行了改進，將其用于交通信號控制，取得了良好的效果。 本文結合精英策略、協(xié)同進化思想和模擬退火機制，提出了一種基于模擬退火機制的精英協(xié)同進化算法（SACEA），將其應用到交通信號控制領域。算法維持三個種群：精英種群、普通種群和隨機種群，精英個體組團，并和其他組員個體協(xié)作或對其引導來達到進化目的。算法在精英組團過程中引入隨機種群以增加種群多樣性，同時隨機個體和精英個體的合作采用快速模擬退火機制來實現(xiàn)，使算法獲得了更好的全局尋優(yōu)性和更快的收斂速度。本文通過實驗驗證了算法的有效性。 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的兩個單交叉口信號控制模型。在此基礎上利用SACEA算法對兩個模型各自進行優(yōu)化配時仿真，并和已有優(yōu)化算法進行對比，結果表明:利用SACEA算法進行優(yōu)化更能減少單交叉口平均延誤時間和平均停車率。 在分析了城市干線協(xié)調(diào)控制理論的基礎上，本文以一個綠波系統(tǒng)為例，以車輛通過干線所需平均總共時間（平均行程時間和總平均延誤時間之和）為控制目標，進一步利用SACEA算法進行了多交叉口配時優(yōu)化，并與已有算法進行對比，結果表明：利用SACEA算法進行優(yōu)化更能減少車輛通過干線所需時間。
[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.
【學位授予單位】：南京郵電大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U491.54;TP18

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