基于模糊邏輯的城市交通信號優(yōu)化控制
發(fā)布時間：2018-07-15 16:50
【摘要】：隨著機動車輛的迅速增加,城市交通擁堵問題日益加劇,制約著經(jīng)濟社會的發(fā)展,給居民的出行帶來了很大的不變,解決城市交通擁堵變得尤為重要。提升交通信號的控制效率已成為解決交通擁堵的一種有效方法。本文針對目前交叉口信號控制方法和控制子區(qū)劃分方法的不足,結(jié)合智能控制理論,在交叉口信號控制方案的選擇、交叉口重要性評估、控制子區(qū)的動態(tài)劃分等方面進行了探討分析,具體的研究內(nèi)容如下:(1)系統(tǒng)地介紹了交通信號控制理論和模糊控制理論,在交叉口信號控制中分別采用了單級模糊控制器和兩級模糊控制器,研究了不同交通流下兩種控制器的控制效果,通過分析控制器輸入變量的選擇,確定了不同交通流下控制器結(jié)構的配置。(2)針對在單交叉口信號控制中控制模型單一導致不能很好適應交通流變化的問題,提出了一種將單級模糊控制和兩級模糊控制兩種策略相結(jié)合的組合控制模型,并利用SOM神經(jīng)網(wǎng)絡實現(xiàn)了兩種控制策略的切換。針對兩級模糊控制器控制規(guī)則和隸屬度函數(shù)人工設定的不足,利用混沌遺傳算法優(yōu)化兩級模糊控制器參數(shù)。同時為了保證控制的實時性,結(jié)合滑動時間窗,根據(jù)實時采集數(shù)據(jù)實現(xiàn)交通狀態(tài)的快速識別和兩級模糊控制器參數(shù)在線優(yōu)化。通過實例仿真,對提出的組合優(yōu)化控制模型進行了驗證。(3)以交叉口連接度、高峰車流量和車道占有率作為評價指標,應用熵權TOPSIS法對交叉口的重要性進行分析,給出了交叉口重要性評價的具體步驟,實現(xiàn)了城市區(qū)域路網(wǎng)的關鍵節(jié)點選擇。(4)針對多數(shù)交通控制子區(qū)劃分方法只考慮兩交叉口關聯(lián)度而忽略了關鍵交叉口的重要性的問題,提出了基于關鍵交叉口交通控制子區(qū)的動態(tài)劃分方法,以關鍵交叉口為起點遍歷四周交叉口,利用模糊推理求得兩相鄰交叉口之間的關聯(lián)度,在此基礎上,通過計算協(xié)調(diào)交叉口與關鍵交叉口的周期差確定控制子區(qū)的劃分,并結(jié)合實例對提出的子區(qū)劃分方法進行了分析研究。
[Abstract]:With the rapid increase of motor vehicles, the problem of urban traffic congestion is becoming more and more serious, which restricts the development of economy and society, and brings great invariance to the travel of residents, so it becomes more and more important to solve the urban traffic congestion. Improving the control efficiency of traffic signals has become an effective method to solve traffic congestion. In view of the deficiency of the current signal control method and the control sub-area division method of intersection, combining with the intelligent control theory, the selection of signal control scheme and the importance evaluation of intersection are discussed in this paper. The dynamic division of the control sub-area is discussed and analyzed. The specific research contents are as follows: (1) the traffic signal control theory and fuzzy control theory are introduced systematically. The single stage fuzzy controller and two stage fuzzy controller are used in the intersection signal control. The control effect of the two controllers under different traffic flow is studied, and the selection of the input variables of the controller is analyzed. The configuration of controller structure under different traffic flow is determined. (2) aiming at the problem of single control model in single intersection signal control, it can not adapt to traffic flow change well. This paper presents a combined control model which combines single-stage fuzzy control and two-level fuzzy control, and realizes the switching of the two control strategies using SOM neural network. Aiming at the deficiency of manual setting of control rules and membership function of two-stage fuzzy controller, the parameters of two-stage fuzzy controller are optimized by chaos genetic algorithm. At the same time, in order to ensure the real-time control, combined with sliding time window, according to the real-time data acquisition, the fast identification of traffic state and the on-line optimization of two-stage fuzzy controller parameters are realized. Through the example simulation, the combined optimal control model is verified. (3) the importance of intersection is analyzed by using entropy weight TOPSIS method, taking intersection connectivity, peak traffic flow and lane occupancy as evaluation indexes. The concrete steps of the importance evaluation of intersections are given, and the selection of key nodes in urban regional road network is realized. (4) considering only the correlation degree of two intersections in most traffic control subareas, the importance of key intersections is neglected. This paper presents a dynamic division method based on traffic control sub-area of key intersection. It uses key intersection as the starting point to traverse around intersection and use fuzzy inference to obtain the correlation degree between two adjacent intersections. The division of the control sub-area is determined by calculating the period difference between the coordinated intersection and the key intersection, and the proposed subarea division method is analyzed and studied with an example.
【學位授予單位】：蘭州交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U491.54
[Abstract]:With the rapid increase of motor vehicles, the problem of urban traffic congestion is becoming more and more serious, which restricts the development of economy and society, and brings great invariance to the travel of residents, so it becomes more and more important to solve the urban traffic congestion. Improving the control efficiency of traffic signals has become an effective method to solve traffic congestion. In view of the deficiency of the current signal control method and the control sub-area division method of intersection, combining with the intelligent control theory, the selection of signal control scheme and the importance evaluation of intersection are discussed in this paper. The dynamic division of the control sub-area is discussed and analyzed. The specific research contents are as follows: (1) the traffic signal control theory and fuzzy control theory are introduced systematically. The single stage fuzzy controller and two stage fuzzy controller are used in the intersection signal control. The control effect of the two controllers under different traffic flow is studied, and the selection of the input variables of the controller is analyzed. The configuration of controller structure under different traffic flow is determined. (2) aiming at the problem of single control model in single intersection signal control, it can not adapt to traffic flow change well. This paper presents a combined control model which combines single-stage fuzzy control and two-level fuzzy control, and realizes the switching of the two control strategies using SOM neural network. Aiming at the deficiency of manual setting of control rules and membership function of two-stage fuzzy controller, the parameters of two-stage fuzzy controller are optimized by chaos genetic algorithm. At the same time, in order to ensure the real-time control, combined with sliding time window, according to the real-time data acquisition, the fast identification of traffic state and the on-line optimization of two-stage fuzzy controller parameters are realized. Through the example simulation, the combined optimal control model is verified. (3) the importance of intersection is analyzed by using entropy weight TOPSIS method, taking intersection connectivity, peak traffic flow and lane occupancy as evaluation indexes. The concrete steps of the importance evaluation of intersections are given, and the selection of key nodes in urban regional road network is realized. (4) considering only the correlation degree of two intersections in most traffic control subareas, the importance of key intersections is neglected. This paper presents a dynamic division method based on traffic control sub-area of key intersection. It uses key intersection as the starting point to traverse around intersection and use fuzzy inference to obtain the correlation degree between two adjacent intersections. The division of the control sub-area is determined by calculating the period difference between the coordinated intersection and the key intersection, and the proposed subarea division method is analyzed and studied with an example.
【學位授予單位】：蘭州交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U491.54
【參考文獻】
相關期刊論文 前10條
1 程海鵬;湯自安;湯e，
本文編號：2124736
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