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姓名	揭揚(Yang Jie)  查詢紙本館藏	畢業系所	土木工程學系
論文名稱	(Understanding the unique route flow solution of traffic assignment modeling with entropy assumption)
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摘要(中)	本文主要介紹兩個熵基礎式的交通量指派中的路徑選擇模型。第一個模型為極大熵用路人均衡模型（Maximum entropy user-equilibrium，MEUE）。第二個模型為熵基礎式的交通量分配模型（Entropy-based traffic assignment，EBTA）。這兩個模型是Chen的雙目標一般化熵基礎式的交通量分配模型的特殊例子（Chen，2015a）。這兩個模型都體現路徑集合唯一性及比例原則的特點。並且，兩個交通量指派模型都具有路徑唯一解的特性。對於求解MEUE模型我們探討了TAPAS演算法（Bar-Gera,2010）以及提出了一種新的變異演算法，並比較了兩者間的運算效率及數值結果。進而，我們發展了一種新的PAS基礎式的演算法求解EBTA模型並驗證了其收斂性及數值結果。
摘要(英)	In this thesis, we focus on two entropy-based route choice models of traffic assignment, namely maximum entropy user-equilibrium (MEUE) and entropy-based traffic assignment (EBTA). These two problems are two special cases of Chen’s two-objective model formulation for the entropy-based traffic assignment (Chen, 2015a). And the properties of route set consistency and proportionality are assumed and be contained in these two problems which are regarded as the condition of unique route flow solution as well. Therefore, the solution algorithm for the MEUE named TAPAS (Bar-Gera, 2010) would be discussed exhaustively and a mixed variant algorithm are also provided for comparing. Furthermore, we propose a new primal PAS-based algorithm called meta-TAPAS for solving the EBTA problem. The performance of such new algorithm is also detailed discussed and examined.
關鍵字(中)	★ 交通量指派 ★ 熵基礎式 ★ MEUE ★ EBTA ★ 唯一路徑流量解	關鍵字(英)	★ traffic assignment ★ entropy-based ★ MEUE ★ EBTA ★ unique route flow solution
論文目次	ABSTRACT I 摘要 II ACKNOWLEDGEMENT IV TABLE OF CONTENTS V LIST OF FIGURES VII LIST OF TABLES VIII CHAPTER I. INTRODUCTION 1 1.1 RESEARCH BACKGROUND 1 1.2 NEED OF THE STUDY 3 1.2.1 Solution precision 3 1.2.2 Computational efficiency 3 1.2.3 Route flow non-uniqueness 4 1.3 THESIS STRUCTURE 5 CHAPTER II. LITERATURE REVIEW 6 2.1 REVIEW OF SOLUTION ALGORITHMS 6 2.1.1 Early convergent algorithms and F-W algorithm 8 2.1.2 Quick and precision algorithm 9 2.2 THEORIES FOR DETERMINING ROUTE FLOW 11 2.3 SUMMARY 15 CHPTER III. MAXIMUM ENTROPY USER-EQUILIBRIUM TRAFFIC ASSIGNMENT 17 3.1 MODEL FORMULATIONS 18 3.1.1 Chen’s two-objective model formulation 18 3.1.2 Bar-Gera’s MEUE model formulations 19 3.2 ALGORITHMIC STRUCTURE 24 3.2.1 Remove cyclic flows 24 3.2.2 PAS identification and flow shift 26 3.2.3 Redistribute flows by proportionality 30 3.2.4 Algorithmic structure of TAPAS and its variant 35 3.3 RESULT ANALYSIS 39 3.3.1 Convergence performance 40 3.3.2 Analysis of route set consistency and proportionality 43 3.4 SUMMARY 46 CHAPTER IV PARTIAL WEIGHTED ENTROPY-BASED TRAFFIC ASSIGNMENT 47 4.1 MODEL FORMULATIONS 47 4.2 ALGORITHMIC STRUCTURE 52 4.2.1 Identify and construct PASs 53 4.2.2 Flow shift and redistribution 55 4.2.3 Algorithmic structure of meta-TAPAS 61 4.3 CASE STUDY AND RESULT ANALYSIS 64 4.3.1 Convergence performance 67 4.3.2 Analysis of proportionality and equilibrium condition 71 4.4 SUMMARY 76 CHAPTER V CONCLUSION AND FUTURE RESEARCH DIRECTIONS 78 5.1 CONCLUSION 78 5.2 FUTURE RESEARCH DIRECTIONS 79 APPENDIX I: NOTATION 80 REFERENCE 81
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指導教授	陳惠國(Huy-Kuo Chen)	審核日期	2015-7-22
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