Development of an environmentally friendly ICT platform for transport management and analysis of user preferences

首先，基于广岛为期两周的实地实验，实证分析了货币激励对模式选择效用的正向影响。与此同时，持环保态度的人不太可能选择汽车，而更可能选择公共交通和非机动交通方式。研究结果在第102届TRB年会上公布。项目中的第二个分析，使用机器学习模型测试了数据预处理和GPS数据频率对准确性和可解释性的影响。结果表明，与GPS数据频率相比，数据预处理对精度的影响更大。第三个分析涉及对旅行模式推荐系统的文献进行全面回顾，总结了不同的算法、数据类型和这些工具的影响。一份手稿目前正在审查中，两份正在编写中。

Firstly, based on a two-week field experiment in Hiroshima, an empirical analysis established positive impact of monetary incentives on mode choice utility. Meanwhile, people with pro-environmental attitudes were observed to be less likely to choose cars and more likely to choose public transit and non-motorized transport modes. The findings were presented at the 102nd TRB annual meeting.Second analysis in the project, tested the impact of data preprocessing and GPS data frequency on accuracy and interpretability using machine learning models. The results show that data preprocessing have a larger impact as compared to GPS data frequency.Third analysis involves a comprehensive review of literature on travel mode recommender systems, which summarizes the different algorithms, data types, and impacts of such tools.One manuscript is currently under review and two under preparation.