第25回行動モデル夏の学校2026 Behavior Modeling in Transportation Networks

Abstract: This talk presents three studies. The first jointly estimates reference points and utility functions in a deep learning–based choice model, imposing economic constraints so that elasticities and willingness-to-pay measures remain behaviorally sound. The second embeds flexible machine learning representations in multiple discrete-continuous models while preserving the KKT structure, keeping satiation and other behavioral phenomena interpretable. The third study shows how LLMs can be used to generate informative Bayesian priors, reducing dependence on large survey samples. Together, these studies point to a complementary role for AI: more flexibility and better data efficiency, with the theoretical structure intact. Bio: Prateek Bansal is a Presidential Young (Assistant) Professor at the National University of Singapore (NUS). Before joining NUS in 2022, he was a Leverhulme Trust Early Career Fellow at Imperial College London and did a Ph.D. from Cornell, an MSc from UT Austin, and a BTech from IIT Delhi. Prateek leads the Behavioural Computational Science Lab at NUS and the Adaptive Mobility module at Future Cities Laboratory Global. His research group is interested in creating new methods to address challenging questions related to mobility behavior and the adoption of emerging technologies at an individual level and on an urban scale. His research has led to over 80 journal articles. Apart from the top Transportation journals, he regularly publishes in interdisciplinary journals like Nature Communications and Statistics and Computing. He serves as the Associate Editor of Transportation Research Part A: Policy and Practice and Transportation Research Part B: Methodological. He is a member of the TRB’s standing committees on Travel Data & Methods (AED17) and an elected board member of the International Association of Travel Behavior Research (IATBR).