Benjamin Cottreau, PhD.

Benjamin Cottreau, PhD.

Transport Economics, Explainable and Causal Machine Learning

Resilience of public transport in the face of disruptions: Insights from explainable machine learning

Published in Transportation Research Part A: Policy and Practice, 2025

How to detect disruptions with fine-grained demand data? This work provides a fully interpretable modelling framework using tree-based learning.

Recommended citation: Cottreau, B., Celbiş, M.G., Manout, O., & Bouzouina, L. (2025). "Detection of subway service disruptions and contribution of alternative stops to public transit resilience." Transportation Research Part A: Policy & Practice. https://doi.org/10.1016/j.tra.2025.104550
Download Paper | Download Bibtex

Spatio-temporal impacts of unplanned service disruptions on public transit demand

Published in Transportation Research and Interdisciplinary Perspectives, 2025

This paper shows the impact of metro disruptions on public transport demand. It uses a Gaussian Mixture Model (GMM) to cluster the disruptions relative to the intensity of their impact, and shows what attributes are the most representative of each class using a MultiNomial Logit (MNL)

Recommended citation: Cottreau, B., Manout, O., & Bouzouina, L. (2025). "Spatio-temporal impacts of unplanned service disruptions on public transit demand." Transportation Research Interdisciplinary Perspective. DOI: https://doi.org/10.1016/j.trip.2025.101354
Download Paper | Download Bibtex

Spatio‐temporal patterns of the impact of COVID‐19 on public transit: An exploratory analysis from Lyon, France

Published in Regional Science Policy & Practice, 2023

This paper focuses on the impact of COVID-19, as a large scale and long-term disruption, on public transport demand.

Recommended citation: Cottreau, B., Adraoui, A., Manout, O., & Bouzouina, L. (2023). " Spatio-temporal patterns of the impact of COVID-19 on public transit: an exploratory analysis from Lyon, France." Regional Science Policy & Practice. DOI: https://doi.org/10.1111/rsp3.12718
Download Paper | Download Bibtex