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

With prospective applications ranging from improving the understanding of the daily and
seasonal dynamics of noise exposure to raising public awareness of the associated health …

Microscopic traffic simulations have become increasingly important for research targeting
connected vehicles. They are especially appreciated for enabling investigations targeting …

The emergence of smart cities is set to transform transportation systems by leveraging real‐
time traffic data streams to monitor urban dynamics. This complements traditional …

This study examines the potential of an iterative and interactive approach to learn network
traffic dynamics and optimise tolling strategies considering time-varying stochastic traffic. A …

The widely-existed uncertainty of origin–destination (OD) demand in transportation networks
has attracted extensive attention. Most characterizations or models of stochastic OD …

With the increasing demand for traffic management and resource allocation in Intelligent
Transportation Systems (ITS), accurate origin-destination (OD) prediction has become …

This paper presents a simulation-based optimization framework for city-scale real-time
estimation and calibration of dynamic demand models by focusing on disaggregated …

The origin–destination (OD) matrix is a critical tool in understanding human mobility, with
diverse applications. However, constructing OD matrices can pose significant privacy …

Travel pattern information is essential for most transport studies and urban planning.
Transport operators must be able to predict travel patterns within the transport system in …