在全球永續發展觀念興起的背景下，自駕車逐漸成為傳統燃油車轉型為電動車的重要推動力量之一。由於全面汰換私人小客車面臨挑戰，許多國家與校園選擇從共享運具或自駕接駁服務開始導入。其中，包含臺灣的國立虎尾科技大學與國立成功大學，以及國外的密西根大學、亞利桑那州立大學等皆有導入校園自駕接駁車服務。然而，此類服務整體目前仍處於初期探索階段。因此，本研究以校園自駕接駁車為對象，探討使用者之接受度，針對大專校院學生與教職員進行調查。研究採量化與質性的方法設計。問卷設計階段參考整合型科技接受模型(UTAUT)為研究架構，並透過初步訪談延伸加入「感知風險」與「信任」兩大構面，以提升模型的解釋力。深度訪談則是於問卷後，作為補充和相互分析之用。
量化部分共回收250份問卷，其中有效樣本為239份。資料分析採用結構方程模型(SEM)與驗證性因素分析(CFA)，以檢視各構面之間的影響關係與整體模型的適配度。質性研究則透過深度訪談法，訪談10位受訪者，以蒐集更深入的觀點與潛在預期，作為量化分析之補充與延伸。
量化研究結果顯示，績效期望、努力期望、社會影響、便利條件與信任皆對使用者行為意圖有顯著正向影響，感知風險則呈顯著負向影響。另一方面，績效期望、努力期望、社會影響與便利條件亦顯著正向影響信任，而感知風險則對信任構面呈現顯著負向影響。質性訪談結果則顯示，受訪者皆表示願意嘗試使用校園自駕接駁服務，並主要重視接駁站點與路線規劃是否符合實際需求，以及整體服務是否能真正帶來效益與效率。此外，部分受訪者提及朋友意見會影響使用意願，顯示社會影響存在一定影響力。並有受訪者表示，若系統能與校方整合、操作更簡便，接受度會更高。由此可知，量化與質性結果相互印證，研究結果可作為校園智慧運輸系統推動與未來自駕接駁服務設計及政策規劃之參考依據。

Amid the growing emphasis on global sustainable development, autonomous vehicles (AVs) have become a key driver in the transition from conventional fuel-powered cars to electric mobility. Given frequent campus accidents and the early stage of autonomous shuttle services, this study investigates the acceptance of campus autonomous shuttles among university students and staff. A mixed-methods approach was adopted. The quantitative survey was based on the Unified Theory of Acceptance and Use of Technology (UTAUT), extended with two additional constructs: Perceived Risk and Trust. A total of 239 valid responses were collected and analyzed using Structural Equation Modeling (SEM) and Confirmatory Factor Analysis (CFA). In addition, ten in-depth interviews were conducted to enrich the findings. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, and Trust positively influence Behavior Intention, while Perceived Risk has a negative effect. Interview findings further highlight that Facilitating Conditions are the most influential factor, followed by Performance Expectancy and Social Influence. Most participants expressed willingness to use the service, particularly valuing stop location planning, ease of operation, and integration with campus systems. These findings offer practical implications for the implementation of smart campus transportation systems and serve as a reference for the future design and policy development of autonomous shuttle services.

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