本文選題：OD預(yù)測(cè) + 非負(fù)矩陣分解　； 參考：《西南大學(xué)》2017年碩士論文

【摘要】：隨著中國(guó)城鎮(zhèn)化進(jìn)程日益加快,城市規(guī)模急劇擴(kuò)張,居民出行方式不斷變化,居民出行范圍逐步擴(kuò)大,但由于城市地理位置的限制及交通基礎(chǔ)設(shè)施的建設(shè)滯后,從而導(dǎo)致一系列制約城市經(jīng)濟(jì)發(fā)展和居民生活水平提高的城市交通問(wèn)題,包括交通擁堵、資源分配不均等。研究城市居民出行模式和交通流量波動(dòng)現(xiàn)象為解決出租車空載率過(guò)高、居民出行需求無(wú)法滿足、交通管理效率較低等交通問(wèn)題提供可能性。鑒于此,本文通過(guò)對(duì)出租車GPS數(shù)據(jù)的分析,挖掘居民出行規(guī)律及區(qū)域交通流的波動(dòng)現(xiàn)象,并提出基于非負(fù)矩陣分解的自回歸預(yù)測(cè)模型和實(shí)現(xiàn)對(duì)交通流波動(dòng)現(xiàn)象的定量分析,為交通使用者提供實(shí)時(shí)有效的出行信息和有效的交通流量波動(dòng)演化規(guī)律,從而對(duì)緩解目前的交通問(wèn)題提供實(shí)質(zhì)性地幫助及建議。面對(duì)日益嚴(yán)重的城市交通問(wèn)題,本文通過(guò)挖掘和分析海量出租車GPS軌跡數(shù)據(jù),基于矩陣分解算法和時(shí)間序列模型實(shí)現(xiàn)對(duì)起訖(Origin-Destination,OD)矩陣的預(yù)測(cè)。并通過(guò)對(duì)流量粗�；＜皬�(fù)雜系統(tǒng)波動(dòng)理論分析,本文已實(shí)現(xiàn)對(duì)區(qū)域網(wǎng)絡(luò)單節(jié)點(diǎn)流量的動(dòng)態(tài)分析、全節(jié)點(diǎn)流量的波動(dòng)規(guī)律以及區(qū)域網(wǎng)絡(luò)系統(tǒng)內(nèi)外部流量的分離分析。本文主要貢獻(xiàn)如下:(1)提出基于非負(fù)矩陣分解的自回歸模型,主要通過(guò)對(duì)OD矩陣的非負(fù)特征和可模擬的用戶出行特征,本文引入非負(fù)矩陣分解算法對(duì)用戶出行特征進(jìn)行分析和宏觀描述;同時(shí),在此基礎(chǔ)上利用自回歸模型對(duì)OD矩陣進(jìn)行預(yù)測(cè)和估計(jì)。(2)基于北京市出租車交通數(shù)據(jù),實(shí)現(xiàn)基于非負(fù)矩陣分解的自回歸(Nonnegative Matrix Factorization-Auto Regressive,NMF-AR)模型對(duì)OD矩陣的預(yù)測(cè)�；诔鲎廛嘒PS數(shù)據(jù),通過(guò)NMF-AR模型挖掘和預(yù)測(cè)用戶出行信息,同時(shí)與引入的短時(shí)交通流預(yù)測(cè)模型進(jìn)行對(duì)比分析,并且對(duì)預(yù)測(cè)精度、模型參數(shù)、數(shù)據(jù)敏感度等問(wèn)題進(jìn)行深入分析,驗(yàn)證模型的預(yù)測(cè)能力。通過(guò)對(duì)OD矩陣實(shí)時(shí)預(yù)測(cè)分析可為居民提供實(shí)時(shí)有效的出行信息,可有效降低空載率,提高運(yùn)營(yíng)效益。(3)實(shí)現(xiàn)基于流量的粗�；：蜕钊敕治鼋煌鞑▌�(dòng)情況。在北京市區(qū)域棋盤(pán)式劃分策略和區(qū)域交通網(wǎng)絡(luò)的基礎(chǔ)上,本研究對(duì)北京市出租車GPS數(shù)據(jù)進(jìn)行適當(dāng)?shù)臄?shù)據(jù)預(yù)處理工作。一方面,針對(duì)單個(gè)區(qū)域的交通流量波動(dòng)情況,本文利用粗�；椒ㄌ幚砹髁孔兓瘶�(gòu)建對(duì)應(yīng)的網(wǎng)絡(luò),同時(shí)分析節(jié)點(diǎn)車流量的波動(dòng)情況。另一方面,本文對(duì)區(qū)域網(wǎng)絡(luò)交通流量波動(dòng)的規(guī)律和演化進(jìn)行重點(diǎn)分析,并對(duì)多個(gè)區(qū)域交通流量的總體特性進(jìn)行考察,并實(shí)證分析該波動(dòng)規(guī)律�；诒本┦谐鲎廛嘒PS軌跡數(shù)據(jù),本文從真實(shí)區(qū)域出租車流量實(shí)證分析其基于時(shí)間的流量均值和標(biāo)準(zhǔn)差之間的關(guān)系。同時(shí)通過(guò)對(duì)區(qū)域網(wǎng)絡(luò)內(nèi)外部流量的分解分析,發(fā)現(xiàn)網(wǎng)絡(luò)系統(tǒng)流量波動(dòng)的演化規(guī)律。從而為交通管理部門(mén)優(yōu)化和制定交通管理策略有效信息。綜上,通過(guò)用戶出行OD矩陣建立NMF-AR預(yù)測(cè)模型、基于區(qū)域流量的粗�；治黾敖煌鲀缏涩F(xiàn)象定量分析,可為交通運(yùn)營(yíng)提供實(shí)時(shí)的出行規(guī)律,為交通監(jiān)管部門(mén)提供有效的建議,從而有助于降低出租車空載率、優(yōu)化交通應(yīng)急管理、提升城市交通運(yùn)行效率。
[Abstract]:With the rapid urbanization process in China, the urban scale is expanding rapidly, the mode of resident travel is changing, and the residents' travel scope is gradually expanding. However, because of the limitation of urban geographical location and the lagging of the construction of traffic infrastructure, a series of urban traffic problems which restrict the development of urban economy and the improvement of the living standard of residents are caused. Including traffic congestion and uneven distribution of resources. The study of urban residents' travel mode and traffic flow fluctuation is a possibility to solve the problem of overloading of taxi no-load, the inability to meet the needs of the residents and the low efficiency of traffic management. In view of this, this paper makes an analysis of the GPS data of the taxi and excavates the laws and areas of the residents' travel. The fluctuation phenomenon of the traffic flow is presented, and the autoregressive prediction model based on the non negative matrix decomposition and the quantitative analysis of the fluctuation of traffic flow are put forward to provide the traffic users with real time effective travel information and the effective evolution law of the traffic flow fluctuation, thus providing substantial help and suggestion to alleviate the current traffic problems. Facing the increasingly serious urban traffic problems, this paper realizes the prediction of the Origin-Destination (OD) matrix based on the matrix decomposition algorithm and the time series model by mining and analyzing the mass taxi GPS trajectory data. Through the rough modeling of the traffic and the analysis of the wave theory of the complex system, this paper has realized the regional network single. The dynamic analysis of node flow, the fluctuation law of the full node flow and the separation and analysis of the internal and external flow of the regional network system. The main contributions of this paper are as follows: (1) the autoregressive model based on the non negative matrix decomposition is proposed. The non negative matrix decomposition algorithm is introduced in this paper mainly through the non negative characteristics of the OD matrix and the simulated user travel characteristics. The characteristics of user travel are analyzed and macroscopically described; at the same time, the OD matrix is predicted and estimated by the autoregressive model. (2) based on the Beijing taxi traffic data, the prediction of the OD matrix based on the Nonnegative Matrix Factorization-Auto Regressive (NMF-AR) model based on the non negative matrix decomposition is based on the prediction of the OD matrix. Taxi GPS data, through NMF-AR model mining and prediction of user travel information, and compared with the introduction of short-term traffic flow prediction model, and in-depth analysis of the prediction accuracy, model parameters, data sensitivity and other issues to verify the prediction ability of the model. Through the real-time prediction analysis of the OD matrix can provide the residents with real information. The effective travel information can effectively reduce the no-load rate and improve the operation efficiency. (3) realize the rough modeling based on the traffic flow and analyze the fluctuation of traffic flow. On the basis of the regional chessboard division strategy and regional traffic network in Beijing, this study carries out the appropriate data preprocessing to the taxi GPS data in Beijing. In view of the fluctuation of traffic flow in a single region, this paper uses the coarse graining method to deal with the flow change and constructs the corresponding network, and analyzes the fluctuation of the node traffic flow. On the other hand, this paper focuses on the law and evolution of the regional network traffic flow fluctuation, and the overall characteristics of the traffic flow in multiple regions. Based on the taxi GPS trajectory data of Beijing City, this paper empirically analyses the relationship between the mean and standard deviation of the time based traffic flow from the real area taxi traffic flow. At the same time, through the analysis of the internal and external flow of the regional network, the evolution of the flow fluctuation of the network system is found. On the other hand, the traffic management department optimizes and establishes the effective information of traffic management strategy. To sum up, the NMF-AR prediction model is established by the OD matrix of user travel. Based on the roughing analysis of regional flow and the quantitative analysis of the power law phenomenon of traffic flow, it can provide real time travel rules for traffic operation and provide effective suggestions for traffic supervision departments. It helps to reduce the empty load rate of taxis, optimize traffic emergency management and improve the efficiency of urban traffic operation.

【學(xué)位授予單位】：西南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U491

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

1 張鵬;王卓;黃仕進(jìn);;交通流流體力學(xué)模型與非線性波[J];應(yīng)用數(shù)學(xué)和力學(xué);2013年01期

2 張勇;關(guān)偉;;交通流時(shí)間序列的多重分形分析[J];計(jì)算機(jī)工程與應(yīng)用;2010年29期

相關(guān)碩士學(xué)位論文 前1條

1 陳煜東;城市區(qū)域交通狀態(tài)演化過(guò)程分析[D];清華大學(xué);2008年

，

本文編號(hào)：1838978