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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/49071


    Title: 先進旅運需求整合模型架構之探討與高效率求解演算法之比較應用;Study on Unified Framework of Travel Demand Combined Models and Application of State-Of-Art Solution Algorithms
    Authors: 陳惠國
    Contributors: 土木工程學系
    Keywords: 研究領域:土木水利工程類
    Date: 2011-08-01
    Issue Date: 2012-01-17 17:21:56 (UTC+8)
    Publisher: 行政院國家科學委員會
    Abstract: 在這個計劃案裏,我們研提了三個連續性的研究主題,以進行為期三年的跨年度的研究,這三個研究主題均屬於運輸需求整合模型之專業範疇。第一年之研究主題為「運輸需求整合模型之統一超級路網架構的發展與驗證」。為了建構統一之整合模型超級路網架構,就必須先行瞭解現有文獻上超級路網架構之優、缺點及其可能之改善方向。一般說來,理想之超級路網可以大概劃分為兩個部份,即交通量指派(或路徑選擇)之基本路網(basic network)以及其他旅運決策的虛擬路網(virtual network)。理想之超級路網架構可以將各種整合模型視為交通量指派模型之延伸。本年度子計劃將會嘗試發展統一超級路網架構,並將會以此為依據,進一步建構完整之變動需求之四階段旅運決策整合模型,並推導其符合一般化用路人行為之均衡條件。最後將提供數值範例進行驗證。第二年之研究主題為「運輸需求整合模型之高精度效率演算法研究」,係以第一年之研究成果為基礎,研發高精度、高效率的演算法。過去文獻用來求解整合模型之演算法概分為:路段基礎式演算法,例如,全線性化之FW 演算法、以及部份線性化之多階段演算法(multistage solution algorithms);路徑基礎式演算法,例如,梯度投影法(gradient projection)、以及個體單體法(disaggregate simplicial decomposition)。但由於電腦科技與演算法之快速發展,目前已有更新之演算法發展出來,例如投影梯度法(projected gradient) 、“B” 演算法或 “OBA” 演算法。但這些演算法是不是適用於求解運輸需求整合模型?以及是否仍有改進空間?的確是一項值得深入研究之課題。一般而言,入瞭解複雜求解法之內容,撰寫電腦程式,以及進行數例測試是一項花費時間、腦力與體力之苦差事,但對研究人員而言卻是紮紮實實的訓練,也是台灣運輸規劃界能夠與國際縮小差距之契機。第三年之研究主題為「動態運輸需求整合模型之研究」。結合過去兩年之研究成果,即第一年所發展出來之運輸需求整合模型之統一超級路網架構,第二年研發之高精度效率演算法,本計劃案之第三年將進一步將研究方向延伸至動態運輸需求整合模型之範疇。動態旅運模型較傳統之靜態旅運模型增加考量旅次之時間向度,網路規模急遽增加,模型複雜度將提高許多。此外,納入時間向度考量也會衍生許多額外的課題,例如,時空路段交互影響、非中凸之可行解區域、離散化問題(counting problem)、以及先進後出之問題。這些課題都將在本年度子計劃詳加探討,並提供數值範例。 This project is mainly concerned with transportation combined models which are to be studied in three consecutive years. In the first year, currently available supernetworks for different transportation combined models will be carefully reviewed and modified, if necessary, for better representation. Of course, supernetworks for new combined models will also be proposed. A supernetwork is usually defined as an augmented network that consists of a “basic network” for route choice and a “virtual network” for other travel choices. Supernetwork representations are useful pedagogical device to interpret various combined travel choice models as an extension of the fixed demand traffic assignment problem. A nested combined model consisting of four choices subject to variable demand will be taken for demonstration. Equilibrium conditions will be derived and solutions will be obtained by a suitable algorithm. In the second year, the focus will be put on the development of more efficient algorithms for the combined models. As pointed out by Sheffi (1985), multistage solution algorithms are more efficient than the FW method for solving combined travel choice models. However, in view of fast development of traffic assignment algorithms, the multistage solution algorithms are no longer good choices for solving combined models. Instead, recent quick-precision algorithms such as projected gradient, “B” or “OBA” algorithms could be more efficient by help of the proposed new supernetwork representations. Note that realizing a complex solution algorithm in depth as well as coding it correctly is always a formidable labor intensive work. In the third year, the combined travel choice models (using the supernetwork representations developed in the first year and computer code(s) for a combined model completed in the second year) will be further extended to dynamic scenario in which additional temporal dimension will be incorporated. Mathematical properties such as uniqueness and existence will be elaborated. Subsequently workable solution algorithms will be proposed and numerical results will be provided. Useful information for practical applications may thus lead the change of way of the modeling work by practitioners currently working for consulting firms. 研究期間:10008 ~ 10107
    Relation: 財團法人國家實驗研究院科技政策研究與資訊中心
    Appears in Collections:[土木工程學系 ] 研究計畫

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