本文選題：交通流　切入點：優(yōu)化速度模型　出處：《廣西大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著國家經(jīng)濟的快速發(fā)展,城市化進程加快,城市道路車輛驟增而產(chǎn)生的擁堵問題,為此需要結(jié)合交通流理論研究提出合理的方案來解決道路交通的擁堵問題。對于道路交通,不僅需要提高道路的交通流量,同時需要能夠有效提高道路交通的運行效能�，F(xiàn)代社會已經(jīng)朝智能化方向發(fā)展,智能交通系統(tǒng)(ITS)是道路交通智能化的重要組成部分。本文基于交通流宏微觀模式,考慮智能交通系統(tǒng)的發(fā)展,探討道路交通控制方法,為道路交通控制推廣理論依據(jù),本文的主要研究工作如下:(1)基于交通流優(yōu)化速度模型和反饋控制理論,提出平均場的反饋控制和延時反饋控制模型。文中對這兩個控制模型進行線性穩(wěn)定性,得出穩(wěn)定性條件其中對平均場反饋控制模型進行非線性分析,導(dǎo)出描述交通擁堵的扭結(jié)-反扭結(jié)密度波的mKdV方程,并求出該mKdV方程的解。當(dāng)交通流處于不穩(wěn)定狀態(tài)時,交通流呈現(xiàn)時停時走交通,施加平均場反饋控制和延時反饋控制分別進行控制,通過采集每個時刻的每一輛車的速度和位置的變化趨勢,以此判斷抑制交通擁堵的控制效果,并且通過控制效果的對比確定平均場延遲反饋作用下的交通流控制模型對于抑制交通擁堵更為有效。(2)以宏觀交通流Nagatani的格子流體力學(xué)(LH)模型為基礎(chǔ),考慮駕駛員反應(yīng)的延遲效應(yīng),并以下游與當(dāng)前車流量差作為反饋控制策略,構(gòu)建格子流體力學(xué)(LH)反饋控制模型。通過對該模型的拉普拉斯變換得出交通流控制系統(tǒng)的傳遞函數(shù),在傳遞函數(shù)的H∞范數(shù)小于1時,求解得到系統(tǒng)的穩(wěn)定性條件。通過理論分析和數(shù)值模擬,驗證了車輛駕駛員的延遲反應(yīng)是引起交通系統(tǒng)不穩(wěn)定的重要因素,在反饋控制作用下,交通系統(tǒng)從不穩(wěn)定狀態(tài)恢復(fù)穩(wěn)定狀態(tài),擁堵的系統(tǒng)得到了有效抑制,實現(xiàn)了交通的控制。(3)基于優(yōu)化速度的全速度模型,提出了有延遲效應(yīng)的速度差模型。通過對該模型的全局穩(wěn)定性和局部穩(wěn)定性分析,并通過數(shù)值模擬,研究結(jié)果表明系統(tǒng)在有延遲效應(yīng)的情況下將更容易有效抑制交通擁堵。(4)文中應(yīng)用宏觀連續(xù)性方程,同時以延遲效應(yīng)的速度差模型作為基礎(chǔ),結(jié)合微宏觀轉(zhuǎn)換關(guān)系,導(dǎo)出具有各向異性的交通流流體力學(xué)模型。對該宏觀交通流動力學(xué)方程進行線性穩(wěn)定性分析和非線性分析,并導(dǎo)出交通密度波的KdV-burgers方程。在周期邊界條件下。應(yīng)用該宏觀流體力學(xué)模型來進行數(shù)值模擬,交通流在高低密度穩(wěn)定性增強,不穩(wěn)定區(qū)域縮小。最后,本文對智能交通系統(tǒng)的控制理論研究進行總結(jié)和展望。
[Abstract]:With the rapid development of the national economy and the acceleration of the urbanization process, the congestion problem caused by the sudden increase of urban road vehicles should be combined with the study of traffic flow theory to put forward a reasonable plan to solve the congestion problem of road traffic. It is necessary not only to increase the traffic flow on the road, but also to be able to effectively improve the operational efficiency of the road traffic. Intelligent Transportation system (ITS) is an important part of road traffic intelligence. Based on traffic flow macro and micro mode and considering the development of intelligent traffic system, this paper discusses the method of road traffic control, which is the theoretical basis for the popularization of road traffic control. The main work of this paper is as follows: (1) based on the traffic flow optimization speed model and the feedback control theory, the feedback control model and the delay feedback control model of the mean field are proposed. The stability conditions are obtained, in which the nonlinear analysis of the mean field feedback control model is carried out, and the mKdV equation describing the kink and inverse kink density wave of traffic congestion is derived, and the solution of the mKdV equation is obtained. When the traffic flow is in an unstable state, When the traffic flow is stopped, the traffic is controlled by the mean field feedback control and the delay feedback control respectively. By collecting the changing trend of the speed and position of each vehicle at each moment, the control effect of restraining the traffic congestion is judged. And through the comparison of control effects, it is determined that the traffic flow control model under the action of average field delay feedback is more effective in reducing traffic congestion. It is based on the lattice fluid dynamics (LH) model of macroscopic traffic flow Nagatani. Considering the delay effect of driver response and taking downstream and current traffic flow difference as feedback control strategy, the LH) feedback control model of lattice fluid dynamics is constructed. The transfer function of traffic flow control system is obtained by Laplace transformation of the model. When the H 鈭，

本文編號：1610418