A common behavior pattern observed on subway platforms is that pedestrians walk
downstairs from the escalator and choose a door to wait for a rail train. Interestingly …

This paper presents a novel flow update policy, namely the successive over relaxation
(SOR) iteration method, which can be implemented in traffic assignment algorithms. Most …

This study focuses on dynamic origin–destination demand estimation problem on freeway
networks. Existing studies on this problem rely on high-coverage of traffic measurements …

Sensing network-wide traffic information is fundamental for the sustainable development of
urban planning and traffic management. However, owing to the limited budgets or device …

Efficiently solving the user equilibrium traffic assignment problem with elastic demand (UE-
TAPED) for transportation networks is a critical problem for transportation studies. Most …

A data-driven model is trained to predict mixed-mode stress intensity factors (SIFs) of
composites through an artificial neural network (ANN) method. The model is based on a …

As the ride-sourcing market expands, ride-sourcing fleets have increased urban traffic
congestion, and in turn, road congestion is affecting ride-sourcing operations. It is crucial to …

This paper models and analyzes a collective incentive strategy with passenger departure
time equilibrium to maximize the total passenger surplus, which could further enhance the …

This paper introduces a parallel computing framework based on the Spectral Partitioning
(SP) method designed to enhance the computational efficiency of large-scale microscopic …

Intelligent transportation systems need to realize accurate traffic congestion prediction. The
spatio-temporal features of traffic flow are essential to analyze and predict congestion. Our …