Can dynamic ride-sharing reduce traffic congestion? In this paper we show that the answer
is yes if the trip density is high, which is usually the case in large-scale networks but not in …

This study reviews existing computational methods to calculate simulation‐based dynamic
network equilibrium. We consider a trip‐based multimodal approach for the dynamic …

The objective imbalance between the taxi supply and demand exists in various areas of the
city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby …

Spatiotemporal graph neural networks (GNNs) have been used successfully in traffic
prediction in recent years, primarily owing to their ability to model complex spatiotemporal …

Real-time ride-sharing has become popular in recent years. However, the underlying
optimization problem for this service is highly complex. One of the most critical challenges …

Macroscopic fundamental diagram (MFD) is widely applied in network-level traffic control
and management with most applications necessitating a well-calibrated MFD. With various …

Affected by the nondeterministic nature of flight trajectories, the external environment, and
airport operational conditions, the prediction of the estimated time of arrival (ETA) is one of …

To meet personalized travel demand, ride-sourcing platforms provide differentiated service
modes for travelers. These service modes are usually operated independently, and because …

The integrated ride-sourcing mode, developed by third-party integrators, is a feasible
solution to market fragmentation because it integrates travel demand and vehicle supply …

Ride-sharing is increasingly recognised as a potential solution to transportation issues such
as traffic congestion and parking problems. The success of ride-sharing systems depends …