目的 提高城市公共交通设施的运行效率，提升设计师的工作效率，满足用户的出行需求。方法 通过用户访谈获取用户需求，在转化成设计需求后，采用层次分析法(AHP)对设计特征进行权重排序。提取用户偏好提示词，并结合GPT4.0中获得的公共交通设施相似提示词，而后得到整合性提示词。选取相关大模型并使用整合性提示词在SD(Stable Diffusion)平台中进行方案生成。结果 以智慧公交站台为例，生成不同场景下智慧公共交通设施方案，经过专家筛选后获得优化方案集，最后邀请用户使用满意度量表对方案集进行打分以获得不同场景下的最优方案。结论 人机协同设计的智慧公交站台方案不仅能满足用户的需求，也提升了设计师的工作效率。因此，通过智慧公交站台设计实践，优化了基于AIGC辅助技术的智慧交通公共设施设计流程，对其他类型的交通公共设施设计具有指导意义。

The work aims to enhance the operational efficiency of urban public transportation facilities, improve the work efficiency of designers, and meet users' travel needs. User needs were gathered through interviews, which were then transformed into design requirements. The AHP (Analytic Hierarchy Process) was utilized to prioritize design features based on weight. User preference prompt words were extracted and combined with similar prompt words obtained from GPT-4.0 regarding public transportation facilities, resulting in integrated prompt words. Relevant large models were selected, and integrated prompt words were used to generate the design on the SD (Stable Diffusion) platform. Taking the smart bus station as an example, smart public transportation facility plans for different scenarios were generated. After screening by experts, an optimized set of plans was obtained. Users were then invited to score these plans by the Likert scale to determine the best plan for each scenario. The human-computer collaborative design of smart bus station plans can meet users' needs and also improve the work efficiency of designers. Therefore, the design practice of smart bus stations has refined the design process of smart transportation facilities supported by AIGC (Artificial Intelligence Generated Content) technology, providing guidance for the design of other types of public transportation facilities.