Activity-based models offer the potential of a far deeper understanding of daily mobility
behaviour than trip-based models. However, activity-based models used both in research …

Ride-sourcing services offered by companies like Uber and Didi have grown rapidly in the
last decade. Understanding the demand for these services is essential for planning and …

This paper investigates the ride-acceptance behavior of drivers on ride-sourcing platforms,
considering drivers' freedom to accept or reject ride requests. Understanding drivers' …

Activity-based models have seen a significant increase in research focus in the past decade.
Based on the fundamental assumption that travel demand is derived from the need to do …

In the context of discrete choice modeling, the extraction of potential behavioral insights from
large datasets is often limited by the poor scalability of maximum likelihood estimation. This …

The potential of Machine Learning to complement, rethink, replace or improve choice
modeling has been the subject of many works throughout the last few years (Hagenauer and …

This thesis is a cross-disciplinary study of discrete choice modeling, addressing both
econometrics and machine learning (ML) techniques applied to individual choice modeling …

Trip-based models have been, for decades, the traditional approach to forecast travel
demand. In trip-based analyses, trip purpose, origins, and destinations are usually predicted …

The package Biogeme (biogeme. epfl. ch) is designed to estimate the parameters of various
models using maximum likelihood estimation. It is particularly designed for discrete choice …