Real-Time Monitoring of Intercity Passenger Flows Based on Big Data

Abstract

Managing population mobility is a key to urban growth and sustainable development. This study uses administrative and business data from a number of trustworthy and publicly-available websites for public transport to access passenger flows in a real-time manner. A case study is used to illustrate the application, with intercity passenger flows by public transport mode (rail or air), by rail service type and by time. Moreover, a model is developed for monitoring the implications of population movements, which can be a decision support tool for governments and policy makers to manage population mobility. The big-data approach to accessing public transport passenger movement has the following characteristics: (1) low cost, (2) a population scale, (3) instantaneous data collection/update, and (4) high quality.