Freight Mode Choice: A Regret Minimization and Utility Maximization Based Hybrid Model

Abstract

With the introduction of automated vehicles, the performance of the trucking industry is expected to be improved. In fact, this may impact the entire freight transportation system as trucks possess the highest mode share in freight transportation. To investigate this impact, a hybrid utility–regret-based mode choice model accommodating for shipper level unobserved heterogeneity is proposed in this study. It recognizes that not all attributes influencing shipment mode are evaluated following a homogenous decision rule (solely random utility maximization/solely random regret minimization). The proposed model system is developed using 2012 Commodity Flow Survey data. To demonstrate the applicability of the proposed model system, a detailed policy analysis is conducted considering several futuristic scenarios such as implementation of automation and controlled access of truck traffic to an urban region. The results indicate that introduction of automation in the freight industry would be more beneficial for long-haul hire truck mode than short-haul private truck mode. An increase in truck shipping time due to re-routing of truck traffic away from urban regions causes a modal shift from truck to parcel and “other” mode (rail, water or multiple modes).