基于MFD的城市交通路網(wǎng)控制子區(qū)域劃分與子區(qū)域邊界交叉口重要度評估方法研究
發(fā)布時間：2018-10-12 11:09
【摘要】：科技的發(fā)展,社會的進步,使得大中型城市的人口急劇膨脹,城市居民的出行的需求劇增。同時電商的崛起加快了物流運輸業(yè)的發(fā)展,使交通服務愈加供不應求。大中型城市交通路網(wǎng)擁堵成為全球問題。近年來,國外一些專家學者不再聚焦于單個擁堵交叉口控制策略的研究,而是從整個交通路網(wǎng)的基本屬性——宏觀基本圖(MFD)出發(fā),將整個城市路網(wǎng)進行子區(qū)劃分(劃分后的各個子區(qū)具有同質MFD特征),對相鄰子區(qū)域之間采取邊界控制方法,控制區(qū)域間輸入和輸出交通流。實踐證明,這是解決交通擁堵的一種有效方法。我國關于MFD的研究剛剛起步。如何在已有城市交通基礎設施的基礎上,通過探究城市路網(wǎng)的MFD特性,進行城市路網(wǎng)控制子區(qū)域劃分,設計有效的控制策略,成為解決城市交通擁堵的一個前沿課題。本文基于北京市望京地區(qū)浮動車的實際數(shù)據(jù),提出了基于MFD的網(wǎng)格逐層的城市路網(wǎng)控制子區(qū)域劃分的新方法。同時從高效節(jié)能的角度考慮,本文提出僅對子區(qū)域邊界上的關鍵節(jié)點進行邊界控制。充分考慮一般復雜網(wǎng)絡的基本特性和實際路網(wǎng)的拓撲結構,提出一種切實可行的交通路網(wǎng)交叉口重要度的評價方法——基于m階鄰居節(jié)點重要度的評估算法,并通過仿真分析,與已有方法進行分析和比較,驗證了該算法具有較好的可行性和精準性。為下一步實現(xiàn)部分路網(wǎng)節(jié)點的邊界控制提供理論依據(jù)。首先,本文對采集的北京市望京地區(qū)浮動車數(shù)據(jù)進行預處理。以高德地圖為基礎,繪制出其路網(wǎng)結構圖,統(tǒng)計各個路段信息。根據(jù)采集到GPS的車輛定位數(shù)據(jù),利用投影算法與道路進行匹配。依據(jù)采集到的浮動車的瞬時速度、車輛標識、車輛狀態(tài)等數(shù)據(jù)計算出本文所需交通參量,如:車流量、平均速度、平均密度等。其次,利用所求交通參數(shù),研究整體路網(wǎng)的MFD特性;對研究區(qū)域進行分析,采用網(wǎng)格逐層試湊疊加的方式進行區(qū)域劃分,并以城市路網(wǎng)的MFD(宏觀基本圖)特性,如:均勻性、離散度低、滯環(huán)現(xiàn)象等,作為一系列的評價指標用于評價區(qū)域劃分的結果。最后,對已有的一般復雜網(wǎng)絡關鍵節(jié)點選取評價方法和相關的道路交通指標進行了分析,選擇在實際路網(wǎng)中體現(xiàn)比較好的特性,如度值、繁忙度、緊密度中心性及介數(shù)中心性等,并在此基礎上提出一種新的基于m階鄰居節(jié)點重要度的關鍵交叉口評估方法,建立新的路網(wǎng)中關鍵交叉口的綜合評價指標。采用基于蟻群算法的BP神經(jīng)網(wǎng)絡進行評估過程中的權值優(yōu)化。與多種評價指標進行了對比和評估,表明本文方法的可行性和有效性。
[Abstract]:With the development of science and technology and the progress of society, the population of large and medium-sized cities expands rapidly, and the demand of urban residents to travel increases dramatically. At the same time, the rise of e-commerce accelerated the development of logistics industry, so that transport services more than demand. Traffic congestion in large and medium-sized cities has become a global problem. In recent years, some foreign experts and scholars no longer focus on the control strategy of a single congested intersection, but start from the basic attribute of the whole traffic network, which is the macroscopic basic diagram (MFD). The whole urban road network is divided into sub-areas (each sub-area has homogeneous MFD characteristics) and the boundary control method is adopted to control the input and output traffic flow between the adjacent sub-regions. Practice has proved that this is an effective method to solve traffic congestion. The research on MFD in China has just started. On the basis of the existing urban traffic infrastructure and by exploring the MFD characteristics of the urban road network, how to divide the control sub-area of the urban road network and design effective control strategies has become a frontier problem to solve the urban traffic congestion. Based on the actual data of floating vehicles in Wangjing area of Beijing, this paper presents a new method of dividing the control subareas of urban road network based on MFD. At the same time, from the point of view of high efficiency and energy saving, this paper presents boundary control only for the key nodes on the sub-region boundary. Considering the basic characteristics of general complex network and the topological structure of practical road network, a feasible evaluation method of intersection importance of traffic network is proposed, which is based on the evaluation algorithm of m-order neighbor node importance, and is analyzed by simulation. Compared with the existing methods, the proposed algorithm is proved to be feasible and accurate. It provides a theoretical basis for the next step to realize the boundary control of some road network nodes. Firstly, this paper preprocesses the floating vehicle data collected in Wangjing area of Beijing. Based on Amap, draw out its road network structure map, statistics each section information. According to the vehicle location data collected from GPS, the projection algorithm is used to match the road. Based on the collected data of floating vehicle's instantaneous speed, vehicle identification and vehicle status, the traffic parameters are calculated, such as: traffic flow, average speed, average density and so on. Secondly, the MFD characteristics of the whole road network are studied by using the traffic parameters sought, and the study area is analyzed, and the area is divided by the method of grid layer by layer superposition, and the MFD (macroscopic basic map) characteristics of the urban road network, such as uniformity, are used to divide the area. As a series of evaluation indexes, low dispersion and hysteresis are used to evaluate the results of regional division. Finally, the paper analyzes the existing methods of selecting and evaluating key nodes in general complex network and the related road traffic indexes, and chooses the better characteristics in the actual road network, such as degree value, busy degree, etc. On the basis of compactness centrality and meso-centrality, a new evaluation method for key intersections based on the importance of m-order neighbor nodes is proposed, and a new comprehensive evaluation index of key intersections in road network is established. The BP neural network based on ant colony algorithm is used to optimize the weights in the evaluation process. Compared with many evaluation indexes, the method is feasible and effective.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U491
本文編號：2265897
[Abstract]:With the development of science and technology and the progress of society, the population of large and medium-sized cities expands rapidly, and the demand of urban residents to travel increases dramatically. At the same time, the rise of e-commerce accelerated the development of logistics industry, so that transport services more than demand. Traffic congestion in large and medium-sized cities has become a global problem. In recent years, some foreign experts and scholars no longer focus on the control strategy of a single congested intersection, but start from the basic attribute of the whole traffic network, which is the macroscopic basic diagram (MFD). The whole urban road network is divided into sub-areas (each sub-area has homogeneous MFD characteristics) and the boundary control method is adopted to control the input and output traffic flow between the adjacent sub-regions. Practice has proved that this is an effective method to solve traffic congestion. The research on MFD in China has just started. On the basis of the existing urban traffic infrastructure and by exploring the MFD characteristics of the urban road network, how to divide the control sub-area of the urban road network and design effective control strategies has become a frontier problem to solve the urban traffic congestion. Based on the actual data of floating vehicles in Wangjing area of Beijing, this paper presents a new method of dividing the control subareas of urban road network based on MFD. At the same time, from the point of view of high efficiency and energy saving, this paper presents boundary control only for the key nodes on the sub-region boundary. Considering the basic characteristics of general complex network and the topological structure of practical road network, a feasible evaluation method of intersection importance of traffic network is proposed, which is based on the evaluation algorithm of m-order neighbor node importance, and is analyzed by simulation. Compared with the existing methods, the proposed algorithm is proved to be feasible and accurate. It provides a theoretical basis for the next step to realize the boundary control of some road network nodes. Firstly, this paper preprocesses the floating vehicle data collected in Wangjing area of Beijing. Based on Amap, draw out its road network structure map, statistics each section information. According to the vehicle location data collected from GPS, the projection algorithm is used to match the road. Based on the collected data of floating vehicle's instantaneous speed, vehicle identification and vehicle status, the traffic parameters are calculated, such as: traffic flow, average speed, average density and so on. Secondly, the MFD characteristics of the whole road network are studied by using the traffic parameters sought, and the study area is analyzed, and the area is divided by the method of grid layer by layer superposition, and the MFD (macroscopic basic map) characteristics of the urban road network, such as uniformity, are used to divide the area. As a series of evaluation indexes, low dispersion and hysteresis are used to evaluate the results of regional division. Finally, the paper analyzes the existing methods of selecting and evaluating key nodes in general complex network and the related road traffic indexes, and chooses the better characteristics in the actual road network, such as degree value, busy degree, etc. On the basis of compactness centrality and meso-centrality, a new evaluation method for key intersections based on the importance of m-order neighbor nodes is proposed, and a new comprehensive evaluation index of key intersections in road network is established. The BP neural network based on ant colony algorithm is used to optimize the weights in the evaluation process. Compared with many evaluation indexes, the method is feasible and effective.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U491
【參考文獻】
相關期刊論文 前10條
1 馬萬經(jīng);廖大彬;;網(wǎng)絡交通流宏觀基本圖:回顧與前瞻[J];武漢理工大學學報(交通科學與工程版);2014年06期
2 盧守峰;王杰;劉改紅;邵維;;基于流量和出租車GPS數(shù)據(jù)的城市道路網(wǎng)絡宏觀基本圖[J];公路交通科技;2014年09期
3 林曉輝;;基于MFD的路網(wǎng)周邊交通控制策略與仿真[J];中外公路;2014年04期
4 張喜平;李永樹;劉剛;王蕾;;節(jié)點重要度貢獻的復雜網(wǎng)絡節(jié)點重要度評估方法[J];復雜系統(tǒng)與復雜性科學;2014年03期
5 杜怡曼;吳建平;賈宇涵;許明;;基于宏觀基本圖的區(qū)域交通總量動態(tài)調控技術[J];交通運輸系統(tǒng)工程與信息;2014年03期
6 任曉龍;呂琳媛;;網(wǎng)絡重要節(jié)點排序方法綜述[J];科學通報;2014年13期
7 許明;吳建平;杜怡曼;謝峰;肖云鵬;;基于三部圖的路網(wǎng)節(jié)點關鍵度排序方法[J];北京郵電大學學報;2014年S1期
8 姬楊蓓蓓;;基于仿真實驗驗證宏觀基本圖的存在性[J];武漢理工大學學報(交通科學與工程版);2013年05期
9 王建強;代磊磊;李婭;王運霞;;基于交通流運行特征的城市干線關鍵交叉口判別方法[J];交通信息與安全;2013年03期
10 盧凱;徐建閩;鄭淑鑒;王世明;;協(xié)調控制子區(qū)快速動態(tài)劃分方法研究[J];自動化學報;2012年02期
相關會議論文 前1條
1 鐘章建;黃瑋;馬萬經(jīng);姚佼;;面向協(xié)調控制的交通小區(qū)劃分算法設計與實現(xiàn)[A];2008第四屆中國智能交通年會論文集[C];2008年
相關碩士學位論文 前4條
1 杜雨弦;復雜網(wǎng)絡中節(jié)點重要度評估算法的研究[D];西南大學;2015年
2 馬囡囡;加權復雜網(wǎng)絡節(jié)點重要度分析及其在城市交通網(wǎng)絡中的應用[D];長沙理工大學;2013年
3 趙強;基于關鍵交叉口交通狀態(tài)判別的配時參數(shù)計算[D];吉林大學;2007年
4 陳曉明;交通控制子區(qū)動態(tài)劃分指標研究[D];吉林大學;2007年
，本文編號：2265897
本文鏈接：http://sikaile.net/guanlilunwen/wuliuguanlilunwen/2265897.html
最近更新
教材專著
