Spatiotemporal travel behavior modeling and analysis for better public transport systems

The public transportation system is crucial in alleviating urban congestion. The widespread of smart card automated fare collection (AFC) system produces massive data recording passengers’ day-to-day transport dynamic, which provides unprecedented opportunities to researchers and practitioners to understand and improve transit services. This project aims to make full use of the transit operational data (mainly smart card data) to enhance transit services. The main body of the research project is spatiotemporal behavior patterns mining.