Abstract Machine Learning (ML) approaches are increasingly being investigated as an
alternative to Random Utility Models (RUMs) for modelling passenger mode choice. These …

In recent decades, transportation planning researchers have used diverse types of machine
learning (ML) algorithms to research a wide range of topics. This review paper starts with a …

The COVID-19 pandemic has resulted in unprecedented changes in the activity patterns and
travel behaviour around the world. Some of these behavioural changes are in response to …

Whereas deep neural network (DNN) is increasingly applied to choice analysis, it is
challenging to reconcile domain-specific behavioral knowledge with generic-purpose DNN …

While deep neural networks (DNNs) have been increasingly applied to choice analysis
showing high predictive power, it is unclear to what extent researchers can interpret …

Researchers often treat data-driven and theory-driven models as two disparate or even
conflicting methods in travel behavior analysis. However, the two methods are highly …

To ensure safety against the COVID-19, along with all other countries, Bangladesh as a
least-developed country needs to deal with the changes in travel behavior, particularly …

Bangladesh is one of the world's strongest emerging economies. This nation is working on
improving women's empowerment, with more women entering meaningful employment, and …

We propose an agent-based mixed-logit model (AMXL) that is estimated with inverse
optimization (IO) estimation, an agent-level machine learning method theoretically …

Abstract We present a Gaussian Process–Latent Class Choice Model (GP-LCCM) to
integrate a non-parametric class of probabilistic machine learning within discrete choice …