本文選題：公共交通 + 多源數(shù)據(jù)��； 參考：《北京工業(yè)大學(xué)》2015年碩士論文

【摘要】：通勤出行是城市居民出行的主體,隨著城市的不斷擴(kuò)張發(fā)展,居民職住分離的現(xiàn)象越發(fā)明顯,通勤出行時(shí)間不斷延長(zhǎng)的問題凸顯出來。而公共交通作為通勤出行中服務(wù)受眾最廣的交通方式,其在解決居民通勤出行難題上的強(qiáng)大優(yōu)勢(shì)越來越被重視。研究居民公共交通通勤出行行為,分析通勤出行時(shí)間的影響因素及特征,對(duì)于提高居民通勤出行效率具有重要意義。首先,論文利用交通供需理論,從需求和供給兩個(gè)角度,科學(xué)地梳理公共交通通勤出行時(shí)間影響因素,并根據(jù)影響因素的普遍性,從宏觀和微觀層面對(duì)其進(jìn)行分類。確定了包括城市空間布局、經(jīng)濟(jì)發(fā)展水平、交通政策法規(guī)、交通出行成本、基礎(chǔ)設(shè)施條件和企業(yè)運(yùn)營(yíng)水平等因素在內(nèi)的影響因素集,并分析了各因素與通勤出行時(shí)間的關(guān)系。然后,論文在介紹了公交IC卡數(shù)據(jù)、軌道AFC數(shù)據(jù)、公交GPS數(shù)據(jù)、交通小區(qū)數(shù)據(jù)等多源公共交通數(shù)據(jù)結(jié)構(gòu)特點(diǎn)的基礎(chǔ)上,利用數(shù)據(jù)融合分析技術(shù),提出了公共交通通勤出行時(shí)間的提取方法,具體包括多源數(shù)據(jù)關(guān)聯(lián)匹配、出行鏈的結(jié)構(gòu)提取、通勤行為判別、出行階段起終點(diǎn)確定和出行時(shí)間計(jì)算五個(gè)步驟。論文詳細(xì)介紹了每個(gè)步驟的處理規(guī)則,確定了相應(yīng)的判斷閾值,解決了地面公交上下車站點(diǎn)匹配等難題,實(shí)現(xiàn)了公共交通通勤出行時(shí)間的提取。最后,論文選取區(qū)位因素和公共交通基礎(chǔ)條件因素,利用SPSS軟件構(gòu)建了通勤出行時(shí)間影響模型。根據(jù)交通小區(qū)內(nèi)有無(wú)軌道交通線網(wǎng),影響模型分為了兩類。論文在分別對(duì)兩類模型進(jìn)行解釋的基礎(chǔ)上,定量分析了增加地面公交和軌道交通線網(wǎng)密度、促進(jìn)城市多中心發(fā)展等措施,對(duì)縮短居民公共交通通勤出行時(shí)間的重要作用。結(jié)果表明,在有軌道交通的小區(qū),地面公交線網(wǎng)密度每增加1km/km2,居民平均的公共交通通勤出行時(shí)間會(huì)縮短0.37分鐘,而軌道交通線網(wǎng)每增加1km/km2,平均出行時(shí)間會(huì)縮短約1.61分鐘;在無(wú)軌道交通的小區(qū),地面公交線網(wǎng)密度每增加1km/km2,居民平均通勤出行時(shí)間會(huì)縮短約0.44分鐘。本文的研究可為北京市公共交通線網(wǎng)優(yōu)化和基礎(chǔ)設(shè)施建設(shè)提供決策支持,對(duì)于改善居民通勤出行狀況有重要意義。
[Abstract]:Commuter travel is the main body of urban residents' travel. With the continuous expansion and development of the city, the separation of residents and residence is becoming more and more obvious, and the problem of the continuous extension of commuter travel is highlighted. As the most widely used traffic mode in the commuter trip, public transportation is becoming more and more powerful in solving the problem of resident commuter travel. The study of commuting travel behavior and analysis of the influence factors and characteristics of commuter travel time are of great significance to improve the efficiency of commuter travel. Firstly, the thesis makes use of the theory of traffic supply and demand to scientifically comb the influence factors of public transportation commuter travel time from two perspectives and according to the shadow. The universality of the noise factors is classified from the macro and micro level. The influence factors including the urban spatial layout, the economic development level, the traffic policy and regulations, the traffic travel cost, the infrastructure conditions and the enterprise operation level are determined, and the relationship between the factors and the commuter travel time is analyzed. Then, the paper is made in this paper. On the basis of the characteristics of public traffic data structure, such as bus IC card data, track AFC data, bus GPS data, traffic district data and so on, using data fusion analysis technology, the extraction method of public transportation commuter travel time is put forward, which includes multi source data connection matching, trip chain structure extraction, commuter behavior discrimination. There are five steps to determine the end point of the line and calculate the travel time. The paper introduces the rules of each step in detail, determines the corresponding judgment threshold, solves the problems of the bus stop point matching on the ground bus and so on, and realizes the extraction of the commuter travel time of public transportation. Finally, the paper selects the location factors and the basic conditions of public transportation. The influence model of commuter travel time is constructed by using SPSS software. The impact model is divided into two categories according to or without the rail transit network in the traffic district. On the basis of the explanation of the two types of models, the paper quantitatively analyzes the measures to increase the density of the ground bus and rail transit network, and promote the development of the city's multi center. The important role of the commuter travel time of the public transportation shows that the average public transport commuter travel time will be reduced by about 0.37 minutes by the average density of the public transport network, and the average travel time will be reduced by about 0.37 minutes, and the average travel time will be reduced by about 1.61 minutes by the mass transit network in the residential area with rail transit, and the average travel time will be reduced by about 1.61 minutes. In the area, the density of the ground bus network increases by 1km/km2, and the average commuter travel time of the residents will be reduced by about 0.44 minutes. This study can provide decision support for the optimization of public transport network and infrastructure construction in Beijing, which is of great significance to the improvement of the commuter travel conditions of the residents.

【學(xué)位授予單位】：北京工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：U491.17

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本文編號(hào)：1855828