Machine learning

A Two-Step Model for Predicting Travel Demand in Expanding Subways

In many cities, subways are expanding with new or extended lines being built and put into operations. The prediction of future travel demand in subway with the planned expansion is of significant importance because such information is crucial for new …

Statistical characteristics and transportation mode identification of individual trajectories

Entering big data era, individual GPS trajectory data has created great opportunities for human mobility and collective behavior studies. Individual GPS trajectories can be collected by location-based services on mobile phones. However, GPS data …

Transportation modes recognition using a Light Gradient Boosting Machine

To investigate different traffic modes for resident’s travel trajectories, a classification model was constructed based on Light Gradient Boosting Machine (LightGBM) to categorize transportation modes according to resident’s GPS trajectories. First, …

Predicting subway passenger flows under different traffic conditions

Passenger flow prediction is important for the operation, management, efficiency, and reliability of urban rail transit (subway) system. Here, we employ the large-scale subway smartcard data of Shenzhen, a major city of China, to predict dynamical …