上班族轨道交通刷卡流量可视分析

Due to public transportation system's convenience, most white-collar workers rely on it. This study focuses on analyzing traffic flow changes and mobility behaviors of white-collar workers from the massive passenger RFID card data and presents an interactive visual analytics system. Firstly, we define rules for assisting users to infer white-collar locations of working and residence. Our system empowers users to select the metro flow at different times and explore the residence location and the work location in flow snapshot view. Flow relation view displays traffic flow changes between stations and mobility behaviors of white-collar. Flow timing view focuses on exploring entire movement patterns for analyzing mobility behaviors of working days and non-working days. Finally, we run two case studies to demonstrate our system.