Summer Webinar Series: A Variational Autoencoder Approach for Route Choice Set Generation

In the context of route choice modeling, choice set generation is a challenging task, since the consideration set is generally unknown to the modelers, and the full choice set cannot be enumerated in real size networks. The proposed variational autoencoder approach (VAE) is motivated by the idea that the chosen alternatives must belong to the consideration set. The VAE approach explicitly considers maximizing the likelihood of including the chosen alternatives in the choice set, and infers the underlying generation process. The VAE approach for route choice set generation is exemplified using a real dataset. VAE-CNL model has the best performance in terms of goodness-of-fit and prediction performance, compared to models estimated with conventionally generated choice sets.

Shlomo Bekhor is a professor in the Faculty of Civil and Environmental Engineering at the Technion – Israel Institute of Technology, and serving as Faculty Dean since 2019. He has a BSc in Aeronautical Engineering from ITA, Sao Jose dos Campos, Brazil. MSc and PhD degrees in Transportation Engineering were obtained at the Technion. He teaches and conducts research in transportation planning and network equilibrium models and has special interest in route choice modeling.

Presented by the Transportation Research Board Subcommittee AEP30(2)/AEP40 on Route Choice and Spatio-Temporal Behavior