Efficient multimodal public transport has been recognized as an effective solution for realizing sustainable intercity transport. However, it has not been well accepted by the general public due to the poor coordination among transport modes, inconvenience caused by transfers, difficulties on route plannings, etc. To address the problem and facilitate the popularity of multimodal intercity travel, this research proposed the design of personalized multimodal travel service based on SPSS (Smart Product Service System). It not only could provide multimodal route recommendations based on individual preferences, but also could improve its performance along usage. Meanwhile, the influencing factors of multimodal intercity travel is investigated, based on which the travel choice model is developed. Besides, a few-short learning method was proposed, which could mine the individual preference even from limited historical travel data. Finally, an experimental case study was conducted that demonstrates the effectiveness of the proposed solution.

高效的多式联运已被公认为实现可持续的城际运输的有效解决方案。但是，由于交通方式之间的协调性不佳，交通不便，路线规划困难等，这一点尚未为广大公众所接受。为解决这一问题并促进多式联运城市间旅行的普及，本研究提出了SPSS（智能产品服务系统）的个性化多式联运服务的设计。它不仅可以提供基于个人偏好的多式联运路线建议，而且可以随着使用情况提高其性能。同时，研究了多式联运出行的影响因素，在此基础上建立了出行选择模型。此外，还提出了一些简短的学习方法，即使从有限的历史旅行数据中也可以挖掘个人的偏爱。最后，进行了一个实验案例研究，证明了所提出解决方案的有效性。