本文選題：定時信號控制 + RFID��； 參考：《重慶交通大學(xué)》2015年碩士論文

【摘要】：隨著交通擁堵問題的日益突出,如何有效地緩解交通擁堵、提高城市道路利用率已成為當(dāng)前交通領(lǐng)域研究的重點。交叉口作為城市交通道路的交匯點,及其管理控制的不當(dāng)是產(chǎn)生交通擁堵的根源,加之交通流的隨機不確定性,傳統(tǒng)的交叉口定時信號控制方式已不能取較好的效果。因此,基于實時檢測的智能交通信號控制方式已成為有效緩解交通擁堵的重要途徑之一。通過對傳統(tǒng)交通檢測技術(shù)的評述,對比分析RFID應(yīng)用于交通檢測的優(yōu)勢,本文以城市干線為研究對象,建立一種基于RFID實時檢測的,信號控制策略(信號周期、綠信比、相位差)隨交通狀態(tài)改變而改變的隨動綠波控制。首先,本文通過對干線系統(tǒng)中干線交通流、交叉口駛?cè)搿Ⅰ偝鼋煌鞯奶匦苑治?選取在干線交叉口上游、干線交叉口停車線附近以及支線交叉口附近三處布設(shè)RFID檢測點,以實現(xiàn)對上述三股交通流量的檢測與識別,并對檢測得到數(shù)據(jù)建立數(shù)據(jù)庫。通過對庫中數(shù)據(jù)的調(diào)用,研究關(guān)鍵交通參數(shù)(交通流量、平均速度、交通密度與道路占有率)、交叉口到達(dá)流量、干線擁堵層度等關(guān)鍵交通信息的采集方法。其次,采用分層求解的思想建立基于RFID檢測的綠波控制策略。具體內(nèi)容是:先以檢測計算得到的各交叉口進(jìn)口道到達(dá)流量及干線相鄰交叉口間路段的擁堵程度,在定時配時方法的基礎(chǔ)上,研究干線的公共信號周期、各交叉口綠信比的確定方法;再以檢測計算得到的平均車速,研究建立基于干線最小延誤的相位差優(yōu)化模型,實時協(xié)調(diào)干線相鄰交叉口間的相位差。最后,建立干線系統(tǒng)實例,按前面研究設(shè)定的方法,求解干線公共周期與各交叉口綠信比。再選用粒子群算法,優(yōu)化求解最小延誤模型中的相位差,并在MATLAB上對干線延誤某型進(jìn)行仿真,然后對比分析固定配時與本文所設(shè)計的優(yōu)化配時的延誤情況,得出本文所建立基于RFID檢測的綠波控制模型,對緩解干線擁堵是切實可行的。
[Abstract]:With the increasingly prominent problem of traffic congestion, how to effectively alleviate traffic congestion and improve the utilization rate of urban roads has become the focus of current traffic research. As the intersection of urban traffic roads, the improper management and control of intersection is the root cause of traffic congestion, coupled with the random uncertainty of traffic flow, the traditional intersection timing signal control method can not get better results. Therefore, intelligent traffic signal control based on real-time detection has become one of the important ways to alleviate traffic congestion. Based on the review of the traditional traffic detection technology and the comparative analysis of the advantages of RFID application in traffic detection, a real-time signal control strategy based on RFID (signal cycle, green to signal ratio) is established in this paper, which takes urban trunk line as the research object. Phase difference) a follow-up green wave control that changes with traffic conditions. First of all, through the analysis of the characteristics of the main line traffic flow, intersections in and out of the trunk line system, this paper selects three RFID detection points in the upper reaches of the main road intersection, near the parking line of the main road intersection and near the branch intersection. In order to realize the detection and identification of the above three traffic flow, and to establish the database of the detected data. The key traffic parameters (traffic flow, average speed, traffic density and road occupancy), the arrival flow at intersections and the traffic congestion layer of the trunk line are studied by using the data in the database. Secondly, the green wave control strategy based on RFID detection is established with the idea of hierarchical solution. The concrete contents are as follows: first, based on the detection calculation of the arrival flow of the intersections and the congestion degree between the adjacent intersections of the trunk line, the common signal cycle of the trunk line is studied on the basis of the timing method. Then the phase difference optimization model based on the minimum delay of the trunk line is established to coordinate the phase difference between the adjacent intersections of the trunk line in real time. Finally, an example of trunk line system is established to calculate the green letter ratio between the common cycle of trunk line and the intersection. Then the particle swarm optimization algorithm is used to solve the phase difference in the minimum delay model, and a certain type of trunk line delay is simulated on MATLAB, and then the delay between the fixed timing and the optimal timing designed in this paper is compared and analyzed. A green wave control model based on RFID detection is established in this paper, which is feasible to alleviate trunk congestion.
【學(xué)位授予單位】：重慶交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U491.54

【參考文獻(xiàn)】

相關(guān)碩士學(xué)位論文 前1條

1 丁凌;交通擁堵的分流方法研究[D];哈爾濱理工大學(xué);2013年

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本文編號：2056298