Energy transition in the power sector, which is a structural transformation of existing fossil
fuel-based power systems to more sustainable forms by increasing the renewable energy …

This paper presents a novel deep learning-based travel behaviour choice model. Our
proposed Residual Logit (ResLogit) model formulation seamlessly integrates a Deep Neural …

Mixed logit models with unobserved inter-and intra-individual heterogeneity hierarchically
extend standard mixed logit models by allowing tastes to vary randomly both across …

The emergence of electric bikes (e-bikes) has brought a paradigm shift in shared mobility
with a promise to move towards the mission of sustainable cities. Whereas an in-depth …

Variational inference methods have been shown to lead to significant improvements in the
computational efficiency of approximate Bayesian inference in mixed multinomial logit …

This study explored the effectiveness of various employer-based travel demand
management strategies in promoting multimodality and mode substitution among …

This paper discusses capabilities that are essential to models applied in policy analysis
settings and the limitations of direct applications of off-the-shelf machine learning …

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 …

Multinomial logit models have been widely used in the analysis of categorical crash data.
When the regional information of the data is available, the dependence structure needs to …

This paper i) compares parametric and semi-parametric representations of unobserved
heterogeneity in hierarchical Bayesian logit models and ii) applies these methods to infer …