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Estimation of daily bicycle traffic using machine and deep learning techniques
A data-driven travel mode share estimation framework based on mobile device location data
Predicting disruptions and their passenger delay impacts for public transport stops
Introducing synthetic pseudo panels: application to transport behaviour dynamics
Should I stay or should I go? Investigating route switching behavior from revealed preferences data
A time-use activity-pattern recognition model for activity-based travel demand modeling
Comparing cities’ cycling patterns using online shared bicycle maps
Discovering urban activity patterns in cell phone data
Learning-based framework for transit assignment modeling under information provision
Large-scale application of MILATRAS: case study of the Toronto transit network