Origin-destination (OD) flow modeling is an extensively researched subject across multiple
disciplines, such as the investigation of travel demand in transportation and spatial …

Carsharing has become increasingly popular in recent years as a sustainable transportation
solution, offering individuals access to shared vehicles on a short-term basis. One-way …

Electric shared mobility is flourishing in urban transportation. However, the problem of
uneven vehicle distribution and untimely vehicle charging hampers user trip experience and …

Accurate demand prediction is an essential component of any decision support system for
smart vehicle dispatching. However, predicting real time demand at the micro-geographical …

To effectively mitigate the spread of infections during public health crises, precise and timely
distribution of medical supplies is crucial. This paper proposes the integration of the metro …

Metro passenger flow prediction is an essential aspect of intelligent transportation systems.
However, despite the emergence of deep learning technologies and the development of …

The insight into origin–destination (OD) demand patterns aids transport planners in making
the public transit system more efficient and attractive. This may encourage individuals to shift …

Short-term origin-destination (OD) matrix prediction in metro systems faces challenges of
high dimensionality, data sparsity, incomplete information, and semantic complexity. This …

A reliable prediction model is critical for the public transit system to keep it periodically
updated. However, it is a challenging task to develop a model of high precision when there …

Uncertainty quantification is important for reliability-oriented transportation operations, and it
becomes increasingly evident to complement traffic level forecasting with uncertainty …