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We investigate traveler preference heterogeneity for high occupancy toll (HOT) roads in Calgary, Canada. We employ a set of latent class discrete choice models that allows for within-class heterogeneity to be captured. This is the first use of latent class models to understand lane choice along a freeway with managed lanes. The use of a latent class structure is justified based on both an improvement in overall fit relative to conventional models and the capacity of this model to provide behavioral insights into preference heterogeneity. The proposed latent class structure captures several interesting trends, including an inversion between travel time and travel cost elasticities across different classes. Using the approach of inferring lifestyles and mobility styles from class membership several interesting trends are established. The finding of high degrees of time sensitivity relative to cost sensitivity amongst certain segments of the population has implications for setting an optimal toll price.

Accounting for preference heterogeneity for high occupancy toll lanes in a Canadian city: a latent class approach