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Using explainable machine learning to understand how urban form shapes sustainable mobility
Travel impedance, the built environment, and customized-bus ridership: A stop-to-stop level analysis
Transit electrification state of the art: A machine-learning based text mining approach
Time-Series fuel consumption prediction assessing delay impacts on energy using vehicular trajectory
Spatial disparity of individual and collective walking behaviors: A new theoretical framework
Sharing behavior in ride-hailing trips: A machine learning inference approach
Revisiting residential self-selection and travel behavior connection using a double machine learning
Revealing influences on carsharing users’ trip distance in small urban areas
Potential of machine learning for prediction of traffic related air pollution
Nonlinear, threshold and synergistic effects of first/last-mile facilities on metro ridership
Nonlinear effects of the built environment on metro-integrated ridesourcing usage
Non-linear associations between the built environment and the physical activity of children
Modeling time-of-day car use behavior: A Bayesian network approach
Machine learning estimates of plug-in hybrid electric vehicle utility factors
Machine learning approach to ship fuel consumption: A case of container vessel