本文選題：數(shù)據(jù)挖掘　切入點(diǎn)：公交IC卡數(shù)據(jù)　出處：《哈爾濱工業(yè)大學(xué)》2017年碩士論文

【摘要】：城市居民公交出行OD是城市公共交通規(guī)劃的基礎(chǔ)資料,是城市公交線網(wǎng)布局和優(yōu)化的重要依據(jù)。傳統(tǒng)居民公交出行OD采集采用的是人工調(diào)查方法,不僅耗費(fèi)大量人力、物力,還存在采集的數(shù)據(jù)樣本量少、精度低等問題。隨著公交刷卡收費(fèi)系統(tǒng)和GPS系統(tǒng)等信息技術(shù)被逐漸引入城市公交系統(tǒng)中,隨之產(chǎn)生了大量的公交IC卡數(shù)據(jù),這為城市公共交通基礎(chǔ)數(shù)據(jù)采集開辟了新的途徑。但目前國內(nèi)多數(shù)城市公交運(yùn)營仍采用一票制模式,公交IC卡數(shù)據(jù)只有上車記錄不包含下車記錄,無法直接獲取居民出行信息。因此,如何有效地從這些數(shù)據(jù)中獲取居民公交出行OD,對城市公共交通服務(wù)水平提升有著重要的現(xiàn)實(shí)意義。為實(shí)現(xiàn)這一目標(biāo),本文將對公交IC數(shù)據(jù)和GPS數(shù)據(jù)進(jìn)行分析,以推算出居民出行OD矩陣。本文首先對公交IC卡和GPS數(shù)據(jù)進(jìn)行分析處理,根據(jù)公交IC卡數(shù)據(jù)特點(diǎn),提出了一種推算乘客刷卡比例的方法。針對一票制公交IC卡缺少乘客站點(diǎn)信息的特點(diǎn),將公交GPS記錄時間與公交IC卡刷卡時間匹配,獲取乘客上車時位置信息,識別乘客上車站點(diǎn);采用時空約束進(jìn)行乘客換乘識別,以乘客相鄰兩次刷卡記錄時間間隔和兩個站點(diǎn)間的空間距離為識別標(biāo)準(zhǔn)進(jìn)行換乘的識別。在下車站點(diǎn)識別中,在參考深圳居民出行特點(diǎn)的同時,本文提出引入地鐵IC卡數(shù)據(jù)作為補(bǔ)充數(shù)據(jù),完善乘客出行鏈,采用基于出行鏈的乘客下車站點(diǎn)概率模型進(jìn)行下車站點(diǎn)的推算。在完成上下車站點(diǎn)識別基礎(chǔ)之上,建立公交站間OD矩陣,以刷卡比例與識別成功率進(jìn)行擴(kuò)樣。根據(jù)站點(diǎn)與交通小區(qū)的空間關(guān)系,將公交站間OD矩陣轉(zhuǎn)化為居民公交出行OD矩陣。最后以深圳市為例進(jìn)行居民出行OD矩陣推導(dǎo),驗(yàn)證算法的有效性和可行性。
[Abstract]:Urban residents travel OD is the basic data of urban public transport planning, it is an important basis for the layout and optimization of urban transit network. The traditional OD collection of urban public transport travel is a manual survey method, which not only consumes a lot of manpower and material resources. There are still some problems such as small sample size and low precision. With the introduction of information technology, such as charging system and GPS system, a lot of IC card data are produced. This opens up a new way to collect the basic data of urban public transport. However, at present, most cities in China still use a one-ticket system in their public transport operations. The IC card data of public transportation only contains no record of getting off or off the bus. Therefore, how to obtain the ODO from these data effectively has important practical significance to improve the level of urban public transport service. In order to achieve this goal, In this paper, the IC data and GPS data of public transportation are analyzed to calculate the OD matrix of residents travel. Firstly, the data of IC card and GPS are analyzed and processed, according to the characteristics of IC card data, This paper presents a method of calculating the proportion of passengers swiping cards. In view of the lack of station information on IC cards of one ticket system, the GPS recording time of public transportation is matched with the time of swiping cards of public transportation IC cards, and the location information of passengers when boarding on board is obtained. Identification of passenger boarding station; use of temporal and spatial constraints to identify passenger transfer, using two adjacent swipe card recording time interval and space distance between the two stations as the identification criteria. While referring to the travel characteristics of residents in Shenzhen, this paper proposes to introduce IC card data as supplementary data to improve the passenger travel chain. The probability model of passenger and disembarkation station based on trip chain is used to calculate the station. On the basis of the identification of boarding and disembarking station, the OD matrix between bus stations is established. According to the spatial relationship between the station and the traffic district, the OD matrix between the bus stations is transformed into the OD matrix of the residents' public transport trip. Finally, taking Shenzhen City as an example, the OD matrix of the residents' trip is deduced. The validity and feasibility of the algorithm are verified.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U491.17

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