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運輸計劃 TSSCI

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篇名 路線資訊類型對高速公路小汽車駕駛人路線移轉行為之影響
卷期 36:4、36:4
並列篇名 The Effects of Different Types of Route Information on Freeway Drivers' Enroute Switching Behavior
作者 馮正民郭奕妏
頁次 477-508
關鍵字 路線資訊類型路線移轉行為潛在變數結構方程模式排序普羅比模式Types of route informationEnroute switching behaviorLatent variablesStructural equation modelingSEMOrdered probit modelOPMTSSCI
出刊日期 200712

中文摘要

本研究重點在於探討路線資訊類型對高速公路小汽車駕駛人路線移轉行為的影響,以兩階段研究方式進行:首先採用結構方程模式衡量駕駛人內心潛在變數,確認影響路線移轉行為意向的正負向潛在變數;接著透過排序普羅比模式進一步確認影響駕駛人路線移轉行為的重要因素,分析在不同路線資訊類型下的行為反應,並將正負向潛在變數納入路線移轉行為模式,以提升路線移轉行為模式的解釋能力。本研究選擇高速公路北部區域進行案例研究,調查對象為行駛於高速公路基隆至新竹間的小汽車駕駛人,有效問卷回收 493份。根據案例分析結果顯示,本研究所推論的因果關係假設皆確立,其中「塞車容受力」及「路線移轉障礙」等負向潛在變數為牽制駕駛人改道行為意向的關鍵因素,致使駕駛人在面臨塞車時仍多半選擇維持原行駛路線;基於改善駕駛人資訊需求的觀點,藉由提供更詳實的替代路線資訊,可協助駕駛人評估改道決策,提高路線移轉行為產生率,達到擁擠管理的效果。

英文摘要

To explore the effects of different types of route information on freeway drivers’ enroute switching behavior, this paper used two stage research methods. First, this paper applied “Structural Equation Modeling (SEM)” to verify the latent variables that will positively or negatively affect drivers’ enroute switching intention and explore the causal effect between them. “Ordered Probit Model (OPM)” method was then used to confirm whether latent variables and types of route information will affect drivers’ enroute switching behavior in the stated congestion scenarios. According to the case study, the research subjects were freeway drivers traveling between Keelung and Hsinchu City. 493 valid questionnaires were collected. The results of SEM showed that all research hypotheses have been confirmed. The drivers’ enroute switching intentions were negatively impeded by the drivers’ tolerance of congestion and perceived switching barriers. Therefore, providing more applicable route information contents in terms of drivers’ opinions must be taken into great consideration. The observed results reveal that drivers’ enroute switching behavior would be motivated by providing more detailed information on alternative routes. The improvement of the route information contents may help the traffic management agency to implement congestion management strategies.

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