天堂国产午夜亚洲专区-少妇人妻综合久久蜜臀-国产成人户外露出视频在线-国产91传媒一区二区三区

當(dāng)前位置:主頁 > 科技論文 > 路橋論文 >

基于LBS軌跡的出行活動(dòng)鏈模式識(shí)別研究

發(fā)布時(shí)間:2018-05-30 04:09

  本文選題:城市交通 + 出行鏈; 參考:《大連交通大學(xué)》2015年碩士論文


【摘要】:互聯(lián)網(wǎng)技術(shù)的變革、移動(dòng)通信技術(shù)的應(yīng)用、智能交通技術(shù)的成熟,為傳統(tǒng)的出行信息調(diào)查、出行行為研究、出行需求預(yù)測(cè)提供了新的思路。本文的研究目的,是希望建立一種方法,能夠有效地從利用智能手機(jī)定位及相關(guān)位置信息所采集到的出行軌跡數(shù)據(jù)中,提取出出行方式、活動(dòng)類型等信息,從而提升居民出行調(diào)查的效率、降低調(diào)查過程中的主觀性、減少調(diào)查周期和費(fèi)用,為城市交通規(guī)劃與管理提供數(shù)據(jù)支撐和決策支持。本文的研究結(jié)合了出行鏈、模式識(shí)別、被動(dòng)式居民出行信息調(diào)查和手機(jī)位置服務(wù)(LBS)等理論和技術(shù)基礎(chǔ)。在研究活動(dòng)鏈和出行鏈結(jié)構(gòu)的基礎(chǔ)上,建立了出行活動(dòng)鏈模式,劃分了出行過程子模式和活動(dòng)過程子模式,并分析了其模式特征,研究了出行活動(dòng)鏈模式和出行軌跡之間的對(duì)應(yīng)關(guān)系;利用手機(jī)定位和傳感器模塊,結(jié)合基于LBS的豐富位置信息的采集思想,構(gòu)建了出行軌跡數(shù)據(jù)的采集方法,并且應(yīng)用了軌跡插值來補(bǔ)全軌跡中的缺失點(diǎn),采用Kalman濾波來實(shí)現(xiàn)軌跡降噪,提出滑窗判別的方法將軌跡劃分成出行段和活動(dòng)段;建立了出行過程子模式和活動(dòng)過程子模式的特征向量,并給出了從出行軌跡參數(shù)向量中提取子模式特征向量的方法,采用頻率分布圖和F-score的方法對(duì)特征向量在兩兩分類間的可分性進(jìn)行了定性和定量的分析,進(jìn)而采用了決策樹、BP網(wǎng)絡(luò)、RBF網(wǎng)絡(luò)和支持向量機(jī)等分類器對(duì)樣本數(shù)據(jù)進(jìn)行識(shí)別。最后以大連市為背景實(shí)地采集了出行軌跡數(shù)據(jù),并利用這些數(shù)據(jù)應(yīng)用上述方法進(jìn)行了實(shí)證研究,對(duì)于數(shù)據(jù)補(bǔ)全、濾波、分段、識(shí)別等方法的效果進(jìn)行了評(píng)價(jià),結(jié)果表明本文所應(yīng)用的方法對(duì)于利用LBS軌跡來進(jìn)行出行活動(dòng)鏈模式識(shí)別能夠取得較好的效果。
[Abstract]:The innovation of Internet technology, the application of mobile communication technology and the maturity of intelligent transportation technology provide a new way of thinking for traditional travel information investigation, travel behavior research and travel demand prediction. The purpose of this paper is to establish a method, which can extract the information of travel mode, activity type and so on from the travel path data collected by using the location information of smart phone and related location information. In order to improve the efficiency of residents' travel survey, reduce the subjectivity of the survey process, reduce the investigation cycle and costs, and provide data support and decision support for urban traffic planning and management. This paper combines the theory and technology of trip chain, pattern recognition, passive travel information survey and mobile location service (LBS). On the basis of studying the structure of activity chain and trip chain, this paper establishes the travel activity chain pattern, divides the travel process sub-pattern and the activity process sub-pattern, and analyzes its pattern characteristics. The corresponding relationship between trip activity chain mode and trip trajectory is studied, and the acquisition method of trip trajectory data is constructed by using mobile phone location and sensor module, combined with the idea of collecting abundant location information based on LBS. The path interpolation is used to compensate the missing points in the whole trajectory, and the Kalman filter is used to reduce the trajectory noise. A sliding window discriminating method is proposed to divide the trajectory into travel segment and active segment. The Eigenvectors of travel process subpattern and activity process subpattern are established, and the method of extracting subpattern eigenvector from trip path parameter vector is given. The qualitative and quantitative analysis of the separability of feature vectors between pairwise classification is carried out by means of frequency distribution map and F-score, and then the classifiers such as decision tree BP neural network and support vector machine are used to identify the sample data. Finally, taking Dalian as the background, we collect the travel track data in the field, and use these data to carry on the empirical research with the above methods, and evaluate the effect of the data complement, filtering, segmentation, recognition and so on. The results show that the method proposed in this paper can achieve good results for pattern recognition of trip activity chain using LBS locus.
【學(xué)位授予單位】:大連交通大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:U495

【參考文獻(xiàn)】

中國(guó)期刊全文數(shù)據(jù)庫 前2條

1 茍博;黃賢武;;支持向量機(jī)多類分類方法[J];數(shù)據(jù)采集與處理;2006年03期

2 雋志才;鮮于建川;;交通信息作用下的活動(dòng)-出行決策行為研究[J];中國(guó)公路學(xué)報(bào);2008年04期

中國(guó)重要會(huì)議論文全文數(shù)據(jù)庫 前1條

1 楊兆升;王媛;;基于手機(jī)探測(cè)車的交通信息采集方法研究[A];第一屆中國(guó)智能交通年會(huì)論文集[C];2005年

中國(guó)碩士學(xué)位論文全文數(shù)據(jù)庫 前1條

1 賈揚(yáng)洋;基于LBS的實(shí)時(shí)交通信息系統(tǒng)的設(shè)計(jì)和實(shí)現(xiàn)[D];河南大學(xué);2009年

,

本文編號(hào):1953849

資料下載
論文發(fā)表

本文鏈接:http://www.sikaile.net/kejilunwen/daoluqiaoliang/1953849.html


Copyright(c)文論論文網(wǎng)All Rights Reserved | 網(wǎng)站地圖 |

版權(quán)申明:資料由用戶35e51***提供,本站僅收錄摘要或目錄,作者需要?jiǎng)h除請(qǐng)E-mail郵箱bigeng88@qq.com