本文選題：出租車客流　切入點：空間異質(zhì)性　出處：《西南交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：出租車運輸行業(yè)憑借獨有的優(yōu)勢,一直以來在城市交通旅客運輸市場占據(jù)一席之地,出租車已經(jīng)成為城市交通系統(tǒng)中重要組成之一�？煽康某鲎廛嚳土餍枨箢A(yù)測可以幫助交通管理部門和運輸服務(wù)企業(yè)對車租車市場的合理調(diào)控。一方面,可提高交通管理部門和運輸服務(wù)企業(yè)對資源的合理分配,提高盈利;另一方面,居民出行選擇將更加靈活自由。然而,隨著城市的多點多級發(fā)展以及區(qū)域發(fā)展的差異,城市出租車客流分布的規(guī)律在空間局部的表現(xiàn)也不相同。本文利用紐約市出租車數(shù)據(jù)資料,通過分析城市出租車客流與各種空間上明確的社會人口和內(nèi)置環(huán)境變量之間的關(guān)系,對其空間變化進行研究。運用地理加權(quán)回歸模型(GWR)建立出租車客流的空間異質(zhì)性模型,并且將估計參數(shù)的空間變化可視化。主要研究內(nèi)容如下:1)根據(jù)出租車運輸特點對城市出租車客流需求進行相關(guān)基礎(chǔ)理論研究;2)重點研究地理加權(quán)回歸模型的結(jié)構(gòu),回歸模型參數(shù)的估計方法;3)使用數(shù)據(jù)庫和GIS軟件對數(shù)據(jù)篩選、計算;4)使用處理得來的數(shù)據(jù)建立了基于地理加權(quán)回歸的出租車客流影響因素分析模型;5)將模型估計參數(shù)的空間變化可視化,深入分析各影響因素對局部區(qū)域出租車客流的影響。研究結(jié)果表明,在處理分析空間變化的問題上,地理加權(quán)回歸模型的模型擬合度和變量解釋準確度都優(yōu)于普通多元線性回歸模型;城市的空間結(jié)構(gòu)對出租車客流分布的影響顯著,并且參數(shù)估計值存在較為明顯的空間異質(zhì)性。這些結(jié)果為預(yù)測出租車客流作為空間變量的函數(shù)提供了有價值的見解,這可以對出租車定價,出租車行業(yè)監(jiān)管和城市規(guī)劃產(chǎn)生重要意義。
[Abstract]:By virtue of its unique advantages, the taxi transportation industry has always occupied a place in the urban transportation and passenger transportation market. Taxi has become one of the important components of the urban transportation system. Reliable taxi passenger demand prediction can help traffic management departments and transport service enterprises to regulate the car rental market reasonably. On the one hand, On the other hand, residents will be more flexible and free in their travel choices. However, with the multi-point and multi-level development of the city and the difference of regional development, The distribution law of urban taxi passenger flow is also different in spatial part. This paper analyzes the relationship between urban taxi passenger flow and various spatial clear social population and built-in environmental variables by using the taxi data of New York City. The spatial variation of taxi passenger flow is studied. The spatial heterogeneity model of taxi passenger flow is established by using geographical weighted regression model (GWR). And visualize the spatial variation of the estimated parameters. The main research contents are as follows: (1) based on the characteristics of taxi transportation, the basic theory of urban taxi passenger demand is studied. (2) the structure of the geo-weighted regression model is studied. Estimation of regression model parameters using database and GIS software to filter the data, Calculation 4) using the processed data to establish the analysis model of the influencing factors of taxi passenger flow based on geographical weighted regression (5) to visualize the spatial variation of the estimated parameters of the model. The effects of various factors on the taxi passenger flow in local areas are analyzed in depth. The results show that, in dealing with the problem of spatial change, The model fitting degree and variable interpretation accuracy of the geo-weighted regression model are better than those of the ordinary multivariate linear regression model, and the spatial structure of the city has a significant effect on the taxi passenger flow distribution. These results provide valuable insights for predicting taxi passenger flow as a function of spatial variables, which can be used to price taxis. Taxi industry regulation and urban planning have important significance.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U492.434

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本文編號：1591306