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  • 學位論文

旅次分配推估方法之研究

Estimation Of Trip Distribution

指導教授 : 卓訓榮

摘要


運輸規劃中,交通起迄流量是基本且重要的資料,傳統的調查方法大多費時耗力且成本高,然而在交通流量大時,進行母體調查並不容易;本研究目的在利用可獲得資料推估交通旅次起迄資料,交通量的產生源自於運輸需求,然而,運輸需求是一種衍生需求,意即運輸並非旅行者真正目的,旅行者是為達成某種社會經濟活動而產生對運輸的需求;在古典引力模式中,僅探討可量測的變項,如:人口分佈、相異兩質點的距離,但是,交通旅次產生的潛在需求是不易被量測的,更重要的是,這種不易被量測的潛在需求正是交通量產生之泉源。本研究嘗試利用數學式來描述這些抽象的變項,建構一個可推估旅次資料的引力模式。 本研究亦對以路段資訊反推高速公路起迄表之可行性進行研究探討,構建以路段資訊推估高速公路旅次起迄分佈矩陣之模式,並以國道一號沿線北自汐止、南至岡山的電子收站資料作模式驗證,以暸解模式之可行性,希望藉此避免傳統調查方法之困難又可獲得可靠的高速公路車輛起迄表。

並列摘要


In transportation planning, traffic flow of origin-destination is an vital and basic data. Traditional survey method expend a large number of labor power and material resources, the more important thing is that it's not easy to survey population while the traffic flow is large. The aim of this study is to modify the classical gravity model, and to use available data estimating origin-destination trip matrices. Traffic is based on transportation demand, however, transportation demand is a derived demand. It means that transportation is not the main purpose of traveler, the traveler requires transportation because of they want to achieve some economics activity. In classical gravity model ,it merely discuss the measurable variable, it doesn't care about the unmeasurable variable, like population , distance between origin and destination. But, the potential demand producted by transportation is uneasy to be measure, the more critical is that the potential demand it is a source of traffic. This study use mathematical-type to describe the abstract variables, and provide a model for estimating highway trip matrices. Another, this study construct a model for estimating based on link information as well. Finally, using available data to realize the feasibility of the model in this study.

參考文獻


Alemeida, M. W. and Goncalves, M. B. (2001), “A methodology to incorporate behavioural aspects in trip-distribution models with an application to estimate student flow,” Environment and planning A, Vol. 33.
Bell, M.G.H. (1991), “The estimation of origin–destination matrices by constrained generalized least squares.” Transportation Research, Part B, Vol. 23, pp. 257–265.
Cascetta, E. (1984), “Estimation of trip matrices from traffic counts and survey data: a generalized least squares estimator.” Transportation Research, Part B, Vol. 18, pp. 289–299.
Goncalves, M. B. (1993), ”The development of a new gravity-opportunity model for trip distribution”, Environment and planning A, Vol. 25, pp. 517-826.
Huff, D.L. (1963), “A probability analysis of shopping center trade areas”,Land economics, Vol. 39 ,pp. 81-90.

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