【摘要】：區(qū)域交通信號控制的子區(qū)劃分是對大規(guī)模城市路網(wǎng)執(zhí)行區(qū)域信號控制的基礎。由于路網(wǎng)內(nèi)交通流的復雜性以及時變特性,固定不變的子區(qū)方案大大降低了信號控制系統(tǒng)的實時應變能力。因此,對控制區(qū)域?qū)嵭袆討B(tài)的子區(qū)劃分逐漸成為研究熱點。針對目前子區(qū)劃分指標選取和劃分方法存在的不足,本文提出了一種基于自組織映射神經(jīng)網(wǎng)絡算法的子區(qū)劃分方法,結(jié)合劃分過程中與關聯(lián)性相關的動態(tài)指標的選取以及關鍵交叉口的實時判別,實現(xiàn)了控制區(qū)域的動態(tài)劃分。在城市路網(wǎng)交通流運行特性分析方面,論文基于城市道路交叉口與路段的實測交通流數(shù)據(jù),對路網(wǎng)內(nèi)交通流的運行特性進行了分析。路網(wǎng)交通需求的傳遞是以交通流在時間和空間上的傳播作為載體,本文采用交通需求在空間上的傳遞特性表征區(qū)域之間存在的關聯(lián)特性。此外,論文介紹了宏觀基本圖的原理,并以此來研究路網(wǎng)的宏觀交通特性。城市路網(wǎng)交通流運行特性研究為動態(tài)子區(qū)的劃分奠定了理論基礎。在區(qū)域信號控制的動態(tài)子區(qū)劃分方面,論文主要針對動態(tài)子區(qū)劃分所涉及的交叉口關聯(lián)性影響因素和劃分計算方法進行了深入的研究。通過對控制區(qū)域內(nèi)關鍵交叉口的實時判別、影響交叉口之間關聯(lián)特性因素的仿真分析以及自組織映射神經(jīng)網(wǎng)絡的計算原理等動態(tài)子區(qū)劃分問題的研究,本文提出了一種基于自組織映射神經(jīng)網(wǎng)絡算法的動態(tài)子區(qū)劃分方法。本文選取昆山市中心城區(qū)為研究對象,對基于自組織映射神經(jīng)網(wǎng)絡算法的動態(tài)子區(qū)劃分方法效果進行了評估。論文采用基于自組織映射神經(jīng)網(wǎng)絡算法的動態(tài)子區(qū)劃分方法和基于“合并指數(shù)”的動態(tài)子區(qū)劃分方法對昆山市的路網(wǎng)劃分進行演算。并采用基于路網(wǎng)空間交通分布和基于區(qū)域信號控制效益兩個方面分別對兩種劃分方法進行評價。評估結(jié)果顯示,本文所提出的動態(tài)子區(qū)劃分方法能夠很好將交通相似性高的交叉口和路段劃分到一個控制子區(qū),且對劃分的控制子區(qū)執(zhí)行協(xié)調(diào)控制時能夠取得良好的控制效益。
[Abstract]:The subdivision of regional traffic signal control is the basis of regional signal control for large-scale urban road network. Because of the complexity and time-varying characteristics of traffic flow in the road network, the fixed sub-area scheme greatly reduces the real-time strain capacity of the signal control system. Therefore, the dynamic subdivision of the control area has gradually become a research hotspot. In view of the shortcomings of the current subdivision index selection and partition method, this paper proposes a subzone partition method based on self-organizing mapping neural network algorithm. The dynamic division of the control area is realized by combining the selection of correlation related dynamic indexes and the real-time identification of key intersections in the process of partition. In the aspect of analysis of traffic flow characteristics of urban road network, based on the measured traffic flow data of intersection and section of urban road, the operation characteristics of traffic flow in urban road network are analyzed in this paper. The transport of road network traffic demand is based on the transport flow in time and space as the carrier. This paper uses the transport demand in the space to express the correlation between the regions. In addition, the principle of macroscopic basic map is introduced, and the macroscopic traffic characteristic of road network is studied. The study of traffic flow characteristics of urban road network lays a theoretical foundation for the division of dynamic subareas. In the area of dynamic sub-area division of regional signal control, this paper mainly focuses on the influence factors of intersection correlation and the calculation method of dynamic sub-area division. Through the real-time identification of key intersections in the control area, the simulation analysis of the factors affecting the intersections' correlation characteristics, and the study of the dynamic sub-area partition problem, such as the calculation principle of self-organizing mapping neural networks, etc. In this paper, a dynamic subregion partition method based on self-organizing mapping neural network algorithm is proposed. In this paper, the effect of dynamic subarea partition method based on self-organizing mapping neural network algorithm is evaluated. In this paper, the dynamic subarea partition method based on self-organizing mapping neural network algorithm and the dynamic sub-area partition method based on "merge index" are used to calculate the road network division in Kunshan City. The two partition methods are evaluated based on the spatial traffic distribution of road network and the benefit of regional signal control respectively. The evaluation results show that the proposed method can well divide the intersection and section with high traffic similarity into a control sub-area, and can achieve good control efficiency when performing coordinated control for the divided control sub-area.
【學位授予單位】：東南大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：U491.54

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