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现场实验，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，据观察，持环保态度的人不太可能选择汽车，而更有可能选择公共交通和非机动交通工具。在项目的第二次分析中，使用机器学习模型测试了数据预处理和GPS数据频率对精度和可解释性的影响。三是对出行方式推荐系统的文献进行了全面的回顾，总结了不同的算法、数据类型以及这些工具的影响；一篇手稿正在审核中，两篇正在准备中。

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.