The aim of this review article is to provide a synoptic and critical evaluation of the extensive
research that has been performed in demand forecasting in the scheduled passenger …

Passenger flow forecast is the prerequisite and foundation for urban rail transit planning and
operation. With the continuous expansion of rail network scale and the surge of passenger …

This study aims to combine the modeling skills of deep learning and the domain knowledge
in transportation into prediction of metro passenger flow. We present an end-to-end deep …

Currently, deep learning has been successfully applied in many fields and achieved
amazing results. Meanwhile, big data has revolutionized the transportation industry over the …

High-precision short-term inbound passenger flow prediction is of great significance to the
daily crowd management and line rescheduling in urban rail systems. Although current …

Short-term prediction of passenger volume is a complex but critical task to urban rail
companies, which desire prediction methods with high accuracy, time efficiency and good …

The COVID-19 pandemic is a significant public health problem globally, which causes
difficulty and trouble for both people's travel and public transport companies' management …

An accurate origin–destination (OD) passenger flow prediction system is crucially important
for urban metro operation and management. However, there are still lacking targeted …

Short-term origin–destination (OD) flow prediction is vital for operations planning, control,
and management in urban railway systems. While the entry and exit passenger demand …

Traffic prediction is highly significant for intelligent traffic systems and traffic management.
eXtreme Gradient Boosting (XGBoost), a scalable tree lifting algorithm, is proposed and …