Passenger travel characteristics and bus operational states: a study based on IC card and GPS data in Yinchuan, China

Abstract

In recent years, public transport has been developing rapidly and producing large amounts of traffic data. Emerging big data-mining techniques enable the application of these data in a variety of ways. This study uses bus intelligent card (IC card) data and global positioning system (GPS) data to estimate passenger boarding and alighting stations. First, an estimation model for boarding stations is introduced to determine passenger boarding stations. Then, the authors propose an innovative uplink and downlink information identification model (UDI) to generate information for estimating alighting stations. Subsequently, the estimation model for the alighting stations is introduced. In addition, a transfer station identification model is also developed to determine transfer stations. These models are applied to Yinchuan, China to analyze passenger flow characteristics and bus operations. The authors obtain passenger flows based on stations (stops), bus lines, and traffic analysis zones (TAZ) during weekdays and weekends. Moreover, average bus operational speeds are obtained. These findings can be used in bus network planning and optimization as well as bus operation scheduling.