- 期刊
Artificial Intelligence (AI) Applications Using Big Data and Survey Data for Exploring the Existence of the Potential Users of Public Transportation System
摘要
The government places emphasis on increasing the usage rate of public transportation nowadays due to public transportation having many benefits for the environment. In order to understand the key factors of trip generation and identify the key trip purposes for selecting transportation modes in a target city, the cell phone data and personal trip survey data were studied by using the machine learning methods of Association Analysis and Inverse Reinforcement Learning. Findings such as hospital, park and elementary school are the most important elements implies that the facilities for mandatory task will attract more people. Also, the elderly age group has very strong tendency to use private vehicle compared to other age groups implies that attracting more young people may be a good strategy. Findings can be a reference for new policy planning, including re-planning the exiting routes of bus systems or integrating different public transportation, by the local government.