目的 针对无人驾驶出租车（Robotaxi）公众信任度不足的问题,构建以信任校准为目标的座舱人机界面（Human-Machine Interface,HMI）交互设计策略,为车企提供理论和实践参考,提升乘客信任度与产品市场接受度。方法 基于详尽可能性模型（Elaboration Likelihood Model,ELM）,从信息加工的动机与能力两个维度出发,分析乘客在不同驾驶情境下的信息加工路径变化机制,明确外周路径、中心路径及双路径协同模式,提出相应的Robotaxi座舱交互设计策略并进行HMI设计实践。结果 提出了一套适应动态情境的Robotaxi座舱交互设计框架及其具体设计策略。该框架在低认知负荷情境下通过行为状态层支持乘客对系统运行安全性的快速感知,在需要深度理解的情境中通过决策意图层与行为原因层促进中心路径的信息加工,并在高风险或异常情境下通过双路径协同机制实现信任修复,从而实现信息呈现方式与乘客认知状态的有效匹配。结论 基于ELM的座舱交互设计策略有望系统性地回应Robotaxi 乘客在动态行驶情境中的差异化认知需求,在理论层面有助于引导乘客形成与系统实际能力相匹配的校准信任,为无人驾驶出租车的人机交互设计提供了可参考的理论依据与设计实践。
Abstract
The work aims to address insufficient public trust in robotaxi, and propose an in-cabin human-machine interface (HMI) design strategy for trust calibration, so as to provide theoretical and practical references for automakers and enhance passenger trust and market acceptance of products. Based on the elaboration likelihood model (ELM), it examined how passengers' information-processing routes varied across driving scenarios in terms of motivation and ability. By integrating the peripheral route, central route, and a dual-path collaboration mode, corresponding interaction design strategies for robotaxi cabins were proposed and HMI design practices were conducted. The study developed an interaction design framework and its specific design strategies. The framework used a behavior status layer to support rapid safety perception under low cognitive load, decision intent and behavior reason layers to support deeper understanding when needed, and a dual-path collaboration mode to repair trust in high-risk or abnormal situations, so as to achieve an effective match between the information presentation method and the cognitive state of passengers. The ELM-based cabin interaction design strategy is expected to systematically address the differentiated cognitive needs of robotaxi passengers in dynamic driving scenarios. At the theoretical level, it helps guide passengers to develop calibrated trust that matches the actual capabilities of the system, and provides a referable theoretical basis and design practice for the human-machine interaction design of robotaxis.
关键词
无人驾驶出租车 /
详尽可能性模型 /
信任校准 /
人机界面 /
交互设计策略
Key words
robotaxi /
elaboration likelihood model (ELM) /
trust calibration /
human-machine interface (HMI) /
interaction design strategy
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基金
广东省高等教育学会“十五五”规划2026年度高等教育研究课题（GJXH26589）; 广东工业大学校级大学生创新训练计划项目（xj2026118450690）; 广东工业大学研究生教育建设及改革创新项目（2024yjg007）; 广东工业大学校级本科教学工程教育教学改革项目（广工大教字[2025]139号）; 广州市科技计划基础与应用基础研究项目（2025A04J3371）; 广东省哲学社会科学规划项目（GD25YYS43）
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