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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 許添本 | |
| dc.contributor.author | Wan-Ching Ho | en |
| dc.contributor.author | 何婉菁 | zh_TW |
| dc.date.accessioned | 2021-06-17T04:59:46Z | - |
| dc.date.available | 2023-08-01 | |
| dc.date.copyright | 2018-08-01 | |
| dc.date.issued | 2018 | |
| dc.date.submitted | 2018-07-26 | |
| dc.identifier.citation | [1] 凌瑞賢 (2015). '運輸規劃原理與實務.'鼎漢國際工程顧問有限公司(第三版)
[2] 尹瑞、魏靜、李克平 (2017). 基於VISUM的程式路網改善方案適應性的探索 [3] 王圓圓 (2008). 交通影響分析中考慮交叉口延誤的交通指派 [4] 王柏元 (2014). 'TSIS 模擬軟體參數校估方法之研究-以高快速道路為例.' 交通大學運輸與物流管理學系學位論文: 1-98. [5] 台北市政府交通局 (2002). 台北都會區整體運輸規劃(二). [6] 仁剛, et al. (2009). '混合交通條件下的城市道路實用路阻函數.' 中國公路學報 22(4): 92-95. [7] 李發宗, et al. (2007). '基于 TransCAD 的城市交通指派模型研究.' 寧波工程學院學報 19(4): 10-13. [8] 林徐勳, et al. (2013). '基于 Kirchhoff 分布方程交通指派模型研究.' 科技管理研究 33(18): 203-206.上海交通大學 [9] 胡大瀛 (2008). '即時動態交通分析與預測模型 (DynaTAIWAN) 之實證分析與推廣 (第 2 年期).'交通部運輸研究所 [10] 童毅, et al. (2007). '基于 VISUM 宏觀仿真的交通影響分析方法及實例.' 中國市政工程(4): 15-17. [11] 黃中祥 (1998). '均衡交通指派模型綜述.' 系統工程 16(2): 42-47. 中國公路學報 [12] 熊堅、王朝英 (2003). 昆明城市交通指派模型研究與應用. 中國公路學報 [13] 劉安、王正 (1997). 混合交通均衡指派方法, 同濟大學. [14] 蓋春英、培育龍. 基於公路網的路段交通量預測方法研究.中國公路學報 [15] 張有恆．現代運輸學 [16] 王煒(2015).大型運輸路網矩陣推算方法研究,東南大學學報 [17] 張國強、宴克非、催叙(2003).基於VISUM模擬軟體的O-D矩陣反推,技術交通运输系统工程與信息研究 [18] 仁敏(2008).運輸需求分析軟體TransCAD、CUBE和VISUM的比較分析,東南大學學報 [19] 黃中祥、賀國光(1998),均衡交通指派模型綜述 [20] 王煒、徐吉谦(1998),城市運輸規劃理論與方法,中國公路學報 [21] Council, K. c. (2012). Canterbury VISUM Transportation Model Local Model Validation Report. [22] Dorothy, P. W., et al. (2006). Development and validation of large-scale microscopic models. [23] Flügel, S., et al. (2014). 'Evaluation of methods for calculating traffic assignment and travel times in congested urban areas with strategic transport models' report 1358: 2014. [24] Gentile, G. and K. Noekel (2009). Linear User Cost Equilibrium: the new algorithm for traffic assignment in VISUM. Proceedings of European Transport Conference 2009, Citeseer. [25] PTV GROUP, (2017). PTV VISUM17 Manual. [26] London, T. f. (2010). Traffic modelling guidelines. [27] Mitran, G., et al. (2014). The Calibration of Macroscopic Transport Sub-models Through Traffic Counting. Second International Conference on Traffic and Transport Engineering (ICTTE). [28] Ni, D., et al. (2004). 'Systematic approach for validating traffic simulation models' Transportation Research Record: Journal of the Transportation Research Board(1876): 20-31. [29] Patriksson, M. (2015). The traffic assignment problem: models and methods, Courier Dover Publications. [30] Piątkowski, B. and M. Maciejewski (2013). 'Comparison of traffic assignment in VISUM and transport simulation in MATSim.' Transport Problems 8. [31] Sheffi, Y. and W. Powell (1981). 'A comparison of stochastic and deterministic traffic assignment over congested networks.' Transportation Research Part B: Methodological 15(1): 53-64. [32] Wegmann, F. and J. Everett (2008). 'Minimum Travel Demand Model Calibration and Validation Guidelines for State of Tennessee.' Centre for Transportation Research. The Universit y of Tennesse. Knoxville. [33] Yousefikia, M., et al. (2013). A study on the generalized T-flowfuzzy O-D estimation. Transport and the New World City, Australasian Transport Research Forum. [34] Keiji Yajima, (2005).Characteristics of incremental assignment method [35] Cambridge Systematics, Inc. Model Validation and Reasonableness Checking Manual 7.0 Assignment Procedures Travel Model Improvement Program. U.S. Department of Transportation. [36] L. Tekiele. Michigan Department of Transportation Urban Model Calibration Target. Michigan Department of Transportation. Lansing, Michigan. June 1993. [37] Micheal Patriksson.The Traffic Assignment Problem-Models and Method. [38] Markus Friedrich(2000),PTV AG, Karlsruhe Keeping Passenger Surveys up-to-date A Fuzzy Approach [39] Mihails Savrasovs .IrinaPticina(2017). Methodology of O-D Matrix Estimation Based on Video Recordings and Traffic Counts. 16th Conference on Reliability and Statistics in Transportation and Communication,RelStat [40] P. Baso et al. Travel Forecasting Guidelines. Texas Transportation Institute. Texas A&M University System. College Station, Texas. October, 1994. [41] L. Tekiele. Michigan Department of Transportation Urban Model Calibration Target. Michigan Department of Transportation. Lansing, Michigan. June 1993. [42] Model Validation and Reasonableness Checking Manual 7.0 Assignment Procedures Travel Model Improvement Program. U.S. Department of Transportation. http://tmip.fhwa.dot.gov [43] Matthew L. James Accuracy Evaluation Tests for Assignment Models of Large Traffic Networks,1987. [44] Travel Demand Modeling with TransCAD Transportation Planning Software [45] Defermos S.C and Sparrow F.T. The traffic Assignment problem for a general network. Journal of the National Bureau of Standards. 73B(0969).pp.91-118 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71228 | - |
| dc.description.abstract | 由於運輸管理策略實際應用時風險很大，因此通常會以建模的方式先進行績效評估。然而於交通指派前，須先針對運輸需求分析軟體進行路網及旅運資料校估以反映現況，本研究使用VISUM為工具，建立一個台北市的都市路網，進行供給及需求模型之校估。
交通指派是運輸規劃中的一個重要步驟，它是將調查得到的起迄點之間的旅次分佈數據 (O-D矩陣，按照一定的規劃分配到路網中的各條道路上，從而推測各條道路上的交通量，並以此作為路網規劃及設計的依據。目前國際上較通用、較成熟的指派模型主要有:一般均衡模型、非均衡模型，而VISUM中整合的交通指派模型基本覆蓋以上幾種通用模型,本文運用VISUM對城市道路的交通模型模型進行研究。 VISUM軟體的校估流程及交通指派方法的績效評估，可供未來相關研究人員參考使用。本研究將以台北市為例，原因在於台北市區道路容量已無擴增之可能，故需提高台北市區的運輸管理；加之歷史資料庫建置完整，得以進行相關研究。本研究首先以VISUM進行建模，利用T-flowfuzzy方法更新O-D矩陣及修改道路參數，為使路網盡可能呈現實際道路狀況，再使用四種不同的交通指派方法得到各道路之交通流量，最後利用10個指標以篩選出較具優勢的方法，提供未來運輸規劃研究者一個具備效率的建模流程。 | zh_TW |
| dc.description.abstract | Due to the high risk of practical application of transportation management strategies, performance evaluation is usually performed in a modeling manner. However, before assigning traffic volume, we must first carry out road network and travel data evaluation for transport planning software to reflect the current situation. This study uses VISUM as a tool to establish a metropolitan road network in Taipei to conduct a supply and demand model assessment , and then use different assignment methods for overall comparison.
Traffic assignment is an important step in transportation planning. It is the distribution data of the travel time between the starting and the return points (the OD matrix, which is allocated to each road in the road network according to a certain plan, so as to infer the various items. The volume of traffic on the road is used as the basis for road network planning and design. At present, the more general and mature assignment models in the world mainly include: general equilibrium model and non-equilibrium model, and the traffic assignment model integrated in VISUM basically covers The above several general models, this paper uses VISUM to study the traffic model model of urban roads. The VISUM software calibration process and performance evaluation of traffic assignment methods can be used by future relevant researchers. This study will take Taipei as an example. The reason is that the capacity of roads in Taipei City has not been expanded. Therefore, it is necessary to improve the transportation management of Taipei City. In addition, the completion of the historical database will enable relevant research. In this study, VISUM was first used to model the road network as much as possible, and the O-D matrix was updated using the T-flowfuzzy method. Secondly, compare four methods of traffic assignment and use 10 indicators to screen out more advantageous methods to provide future transportation planning researchers with an efficient modeling process. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-17T04:59:46Z (GMT). No. of bitstreams: 1 ntu-107-R05521525-1.pdf: 6105537 bytes, checksum: aa2e3fee6552bc2ccf2b79bb4e3a81b7 (MD5) Previous issue date: 2018 | en |
| dc.description.tableofcontents | 致謝 i
摘要 ii Abstract iii 目錄 iv 圖目錄 vii 表目錄 x 第壹章 緒論 1 1.1 研究背景與動機 1 1.2 研究目的與範圍 1 1.3 研究內容 2 1.4 研究方法 3 1.5 研究流程 5 第贰章 文獻回顧 6 2.1 運輸需求分析軟體介紹 6 2.1.1 美國Cube運輸需求分析軟體介紹 6 2.1.2 美國TransCAD運輸需求分析軟體介紹 7 2.1.3 德國VISUM運輸需求分析軟體介紹 7 2.1.4 各運輸需求分析軟體比較 9 2.2 交通指派模型 15 2.2.1 交通指派模型分類 16 2.2.2 交通指派模型分類 17 2.3 流量延誤函數 29 2.3.1 定義 29 2.3.2 常用的流量延誤函數 29 2.4 O-D矩陣預測理論 31 2.5 模型績效評估 33 2.5.1 模型績效評估的意義 34 2.5.2 模型績效評估標準 36 第叁章 模型建構方法 37 3.1 供給模型建立 37 3.1.1 研究範圍定義 37 3.1.2 模型內之主要路網選擇 37 3.1.3 路網模型設定 38 3.1.4 路網正確性檢核 45 3.2 旅運需求模型建立 46 3.2.1 模型分區 46 3.2.2 小區連接線 49 3.2.3 日類型 49 3.2.4 歷史資料 49 第肆章 旅運需求模型校估 50 4.1 需求模型校估 50 4.1.1 輸入資料 50 4.1.2 路段程序輸出結果 51 第伍章 交通指派模型的驗證與比較 53 5.1 Incremental Assignment 遞增指派模型 54 5.1.1 模型參數設定 55 5.1.2 指派模型結果 56 5.2 Stochastic Assignment 隨機指派模型 63 5.2.1 模型參數設定 64 5.2.2 指派模型結果 67 5.3 Equilibrium assignment均衡指派模型 72 5.3.1 模型參數設定 73 5.3.2 指派模型結果 74 5.4 Equilibrium Lohse Method Lohse均衡模型 75 5.4.1 模型參數設定 76 5.4.2 指派模型結果 77 5.5 綜合比較與分析 78 第陆章 結論與建議 80 6.1 結論 80 6.2 建議 81 參考文獻 82 附錄 85 遞增指派法(指派比例15-15-15-10-10-10-10-5-5-5)指派結果 85 隨機指派法-Kirchhoff函數 89 隨機指派法-Logit函數(β=0.25) 94 隨機指派法-Logit函數(β=0.1) 99 隨機指派法-BoxCox函數 104 用戶均衡指派法 108 Lohse均衡指派法 113 | |
| dc.language.iso | zh-TW | |
| dc.title | 交通指派方法的驗證與比較分析-以台北市為例 | zh_TW |
| dc.title | Contrast of Traffic Assignment Methodologies and its Analysis- A Case Study of Taipei City | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 106-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 黃台生,凌瑞賢 | |
| dc.subject.keyword | VISUM,交通指派,O-D矩陣推算,路網績效評估, | zh_TW |
| dc.subject.keyword | Traffic assignment,VISUM,Traffic network validation,O-D estimation, | en |
| dc.relation.page | 118 | |
| dc.identifier.doi | 10.6342/NTU201801872 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2018-07-26 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 土木工程學研究所 | zh_TW |
| 顯示於系所單位： | 土木工程學系 | |
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