Travel demand modeling has evolved from the traditional four-step models to tour-based
models which eventually became the basis of the advanced Activity-Based Models (ABM) …

Travel demand management measures/policies are important to sustain positive changes
among individuals' travel behaviour. An integrated agent-based microsimulation platform …

Investigating travel time distribution and associated variability is important for a variety of
transport planning, traffic management, and control projects. Studies that investigated travel …

Transportation is fundamental to fulfilling our human needs and travel demand is widely
understood to be derived from the demand for activity participation. Transportation, much …

Microsimulations make use of quantitative methods to analyze complex phenomena in
populations. They allow modeling socioeconomic systems based on micro-level units such …

The travel demand prediction of an activity-based travel demand model (ABM) is based on a
hierarchical structure of multiple choices related to an individual's activity scheduling. This …

While advanced technologies and big data are widely used in the transportation study, most
transportation plans still rely on some variant of traditional four-step demand forecasting …

Activity-based transportation models simulate demand and supply as a complex system and
therefore large set of parameters need to be adjusted. One such model is Preday activity …

Calibration of simulation models and hyperparameter optimisation of machine learning and
deep learning methods are computationally demanding optimisation problems, for which …

Efforts to forecast travel demand have led to the development of complex models which
attempt to replicate human daily actions, choices, and movements. However, a growing …