本文選題：交通信號(hào) + 單交叉路口��； 參考：《寧夏大學(xué)》2015年碩士論文

【摘要】：隨著經(jīng)濟(jì)的發(fā)展,私家車數(shù)量的急劇增加,城市交通擁堵問(wèn)題也日益突出。城市交叉路口作為交通路網(wǎng)控制的關(guān)鍵點(diǎn),對(duì)車輛通行效率影響巨大,交通信號(hào)控制的效果直接決定了整個(gè)交通網(wǎng)絡(luò)的性能。為了解決城市交通擁堵問(wèn)題,雖然嘗試了各種辦法,例如拓寬道路,單雙號(hào)限行,還是沒(méi)有有效的解決擁堵問(wèn)題。本文對(duì)現(xiàn)有交通控制系統(tǒng)研究后發(fā)現(xiàn),現(xiàn)有的交叉口交通信號(hào)配時(shí)不合理是造成交通擁堵的主要原因,因此本文對(duì)交叉口的交通信號(hào)控制系統(tǒng)進(jìn)行優(yōu)化設(shè)計(jì)。根據(jù)實(shí)時(shí)采集到的交通流數(shù)據(jù)應(yīng)用遺傳算法對(duì)交通信號(hào)控制系統(tǒng)進(jìn)行合理動(dòng)態(tài)優(yōu)化配時(shí)設(shè)計(jì),在一定程度上達(dá)到緩解交通擁堵,減少車輛延誤,減少車輛排隊(duì)長(zhǎng)度,提高車輛通行率的目的。本文首先在分析現(xiàn)有單交叉口的信號(hào)控制方法基礎(chǔ)上,針對(duì)當(dāng)前城市交通動(dòng)態(tài)變化的特性,指出了傳統(tǒng)控制方式的不足和缺陷,然后對(duì)遺傳算法的基本原理、基本要素等進(jìn)行分析后,針對(duì)基本遺傳算法在應(yīng)用中的局限性,對(duì)算法進(jìn)行改進(jìn)來(lái)提高運(yùn)行效率和求解的質(zhì)量。然后在分析城市單交叉路口交通流特性的基礎(chǔ)上以銀川市賀蘭山路和正源街的十字交叉路口的交通控制信號(hào)為優(yōu)化目標(biāo),首先建立了以車輛平均延誤時(shí)間最短,以相位有效綠燈時(shí)間和飽和度為約束條件的非線性函數(shù)模型,利用改進(jìn)的遺傳算法對(duì)模型進(jìn)行優(yōu)化求解,得到在固定周期下的最優(yōu)配時(shí)方案。仿真結(jié)果表明利用改進(jìn)的遺傳算法對(duì)模型優(yōu)化后交叉口車輛平均延誤有了明顯的減少。其次,針對(duì)交叉路口的交通擁堵情況,建立了以控制周期內(nèi)路口的總的車輛排隊(duì)長(zhǎng)度最小為目標(biāo),以相位有效綠燈時(shí)間和信號(hào)周期時(shí)長(zhǎng)為控制變量的交通信號(hào)優(yōu)化模型,利用改進(jìn)的遺傳算法對(duì)模型進(jìn)行仿真計(jì)算,結(jié)果表明優(yōu)化后控制周期內(nèi)路口的總延誤排隊(duì)車輛數(shù)有了明顯的減少。
[Abstract]:With the development of economy, the number of private cars increases rapidly, and the problem of urban traffic congestion becomes more and more serious.As the key point of traffic network control, urban intersections have a great impact on the traffic efficiency. The effect of traffic signal control directly determines the performance of the whole traffic network.In order to solve the problem of urban traffic congestion, although various methods have been tried, such as widening roads, restricting traffic by single and even numbers, the problem of congestion has not been solved effectively.After studying the existing traffic control system, it is found that the unreasonable traffic signal timing is the main cause of traffic congestion, so the traffic signal control system at the intersection is optimized in this paper.According to the traffic flow data collected in real time, the genetic algorithm is used to optimize the traffic signal control system in order to reduce the traffic congestion, reduce the vehicle delay and reduce the queue length to a certain extent.The purpose of increasing the vehicle traffic rate.Based on the analysis of the existing signal control methods of single intersection, this paper points out the shortcomings and defects of the traditional control methods in view of the characteristics of the current urban traffic dynamic change, and then analyzes the basic principles of genetic algorithm.In view of the limitation of the basic genetic algorithm in application, the basic elements are analyzed, and the algorithm is improved to improve the running efficiency and the quality of the solution.Then on the basis of analyzing the traffic flow characteristics of the single intersection of the city, the traffic control signal of the intersection of Helan Mountain Road and Zhengyuan Street in Yinchuan City is taken as the optimization goal. Firstly, the shortest average delay time of the vehicle is established.Based on the nonlinear function model with phase effective green time and saturation as constraints, the improved genetic algorithm is used to optimize the model, and the optimal timing scheme under fixed period is obtained.The simulation results show that the improved genetic algorithm can significantly reduce the average vehicle delay after model optimization.Secondly, the traffic signal optimization model is established to minimize the total vehicle queue length and take the phase effective green time and the signal cycle time as the control variables, aiming at the traffic congestion at the intersection.The improved genetic algorithm is used to simulate the model. The results show that the total number of queue vehicles at the intersection within the control cycle has been significantly reduced after the optimization.
【學(xué)位授予單位】：寧夏大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U491.51

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本文編號(hào)：1756899