4 papers
Using machine learning metrics to provide deeper insights into the performance of choice models
Lorenzo Muñoz, Stephane Hess, Thomas O. Hancock +1
Machine learning (ML) techniques are increasingly drawing interest in the choice modelling (CM) field. The focus has primarily been on comparing the performance of these contrastin…
A Bayesian latent class reinforcement learning framework to capture adaptive, feedback-driven travel behaviour
Georges Sfeir, Stephane Hess, Thomas O. Hancock +5
Many travel decisions involve a degree of experience formation, where individuals learn their preferences over time. At the same time, there is extensive scope for heterogeneity ac…
Can large language models assist choice modelling? Insights into prompting strategies and current models' capabilities
Georges Sfeir, Gabriel Nova, Stephane Hess +1
Large Language Models (LLMs) are becoming widely used to support various workflows across different disciplines, yet their potential in discrete choice modelling remains relatively…
Choice Sets and Smart Card Data In Public Transport Route Choice Models: Generated vs. Empirical Sets
Georges Sfeir, Filipe Rodrigues, Ravi Seshadri +1
This study evaluates path sets generation for route choice models in multimodal public transportation networks, using both conventional (network algorithms) and empirical (smart ca…