Many American cities are testing autonomous shuttles (AS), or self-driving minibuses, as a new mode of public transportation. Existing AS studies often rely on stated preference (SP) surveys that require participants to imagine AS scenarios, or they evaluate short-term pilot programs, thus lacking long-term user insights – particularly in car-dependent suburban contexts. To address these limitations, we conducted a revealed preference (RP) study to identify critical factors influencing AS acceptance among users of Move Nona, the longest-running AS network in the United States, located in Lake Nona, a residential suburb in Orlando, Florida. This study expanded the Technology Acceptance Model (TAM) to include six latent factors: perceived ease of use, perceived usefulness, trust in AS safety, perceived AS reliability under inclement weather conditions, personal innovativeness, and environmental awareness. Our findings indicate that perceived usefulness, ease of use, and environmental awareness positively affect AS acceptance. Contrary to previous research, however, trust and personal innovativeness have minimal impact, suggesting that as users become more familiar with AS, they prioritize essential mobility aspects, such as travel speed and convenience, over technological novelty. These insights are valuable for decision-makers planning to adopt AS to enhance local transit services, while also contributing to the broader field of behavior analysis by corroborating an extended application of TAM in examining AS user acceptance.

中文翻译：

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美国郊区对自动驾驶班车的接受度：佛罗里达州诺娜湖的一项显示偏好研究


许多美国城市正在测试自动穿梭巴士（AS）或自动驾驶小巴，作为一种新的公共交通模式。现有的自动驾驶研究通常依赖于陈述偏好（SP）调查，要求参与者想象自动驾驶场景，或者评估短期试点项目，因此缺乏长期的用户洞察——尤其是在依赖汽车的郊区环境中。为了解决这些局限性，我们进行了一项显示偏好 (RP) 研究，以确定影响 Move Nona 用户接受 AS 的关键因素。 Move Nona 是美国运行时间最长的 AS 网络，位于佛罗里达州奥兰多市的诺纳湖住宅区。这项研究扩展了技术接受模型（TAM），包括六个潜在因素：感知的易用性、感知的有用性、对 AS 安全性的信任、在恶劣天气条件下感知的 AS 可靠性、个人创新性和环境意识。我们的研究结果表明，感知有用性、易用性和环境意识对 AS 接受度产生积极影响。然而，与之前的研究相反，信任和个人创新的影响微乎其微，这表明，随着用户对自动驾驶系统越来越熟悉，他们会优先考虑基本的移动性方面，例如出行速度和便利性，而不是技术新颖性。这些见解对于计划采用 AS 来增强本地交通服务的决策者来说非常有价值，同时也通过证实 TAM 在检查 AS 用户接受度方面的扩展应用，为更广泛的行为分析领域做出了贡献。