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題 名 | 應用基因演算法於捷運列車運行計畫之研究=A Genetic Algorithm Model for MRT Train Service Planning |
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作 者 | 王晉元; 林誌銘; | 書刊名 | 運輸計劃 |
卷 期 | 36:1 2007.03[民96.03] |
頁 次 | 頁115-145 |
分類號 | 557.85 |
關鍵詞 | 捷運; 列車運行計畫; 雙層次規劃問題; 基因演算法; MRT; Train service plan; Bi-level programming problem; Genetic algorithm; |
語 文 | 中文(Chinese) |
中文摘要 | 過去探討即時交通資訊對駕駛人路線移轉行為意向的研究,較缺乏直接納入即時交通資訊接受度與路線移轉障礙等潛在變數。為釐清廣播資訊對高速公路小汽車駕駛人路線移轉行為意向的影響關係,本研究採兩階段研究方法,首先應用探索性因素分析萃取潛在變數,接著以結構方程模式確認潛在變數及其間因果關係。針對行駛於高速公路基隆至新竹間的小汽車駕駛人進行問卷調查,取得潛在認知與態度之有效樣本。模式分析結果顯示,駕駛人所認知的廣播資訊價值與使用態度,顯著且正向影響路線移轉行為意向,至於路線移轉障礙則會負向牽制改道意願,所提出模式假設經檢定後均成立。本研究並依據研究結果探討其政策意涵,建議後續駕駛者資訊系統之改善方向。 |
英文摘要 | In the past, studies on drivers’ route switching behavior intentions did not discuss the effects of drivers’ acceptance of real-time traffic information and switching barriers. We used a two-stage research methodology to explore the effects of real-time traffic information on freeway drivers’ switching behavior intentions. First, Exploratory Factor Analysis (EFA) method was applied to identify measurable variables in order to extract key latent variables. Then we applied Structural Equation Modeling (SEM) to confirm these variables that affect drivers’ route switching intentions and to explore the causal effect between them. A relationship model for explaining drivers’ switching behavior intentions was established and verified. The questionnaire data used in this study were randomly collected from drivers traveling between Keelung and Hsinchu City in order to explore the drivers’ acceptance of real-time traffic information, switching barriers, and their route switching intentions. The results of this study show that the relationship between these variables and all the hypotheses we made have been confirmed. The main variables which significantly and positively affect drivers’ switching behavior intentions are the perceived value and usage attitude of real-time information, while switching barriers negatively affect drivers’ switching behavior intentions. This study also provides traffic management suggestions about the content of real-time traffic information offered to drivers for traffic management agencies. |
本系統中英文摘要資訊取自各篇刊載內容。