A freight asset choice model for agent-based simulation models

Abstract

Agent-based models (ABM) for transportation operations have been largely focused on passenger trips, while recent developments in the field began the incorporation of freight-related operations. However, these models rarely incorporate freight-related strategic asset decisions: fleet and distribution center (DC) ownership. These attributes are important for modeling freight transportation behavior in ABMs. This research develops behavioral models that jointly predict fleet ownership and distribution center control for freight-related firms in an ABM framework. A seemingly unrelated Tobit regression is estimated using large-scale data from more than 11 million establishments. The model is estimated using a Bayesian approach that allows for the quantification of the coefficients’ variability. Model results indicate that firms with higher revenue have an increased propensity to own fleet and (or) DC and prefer larger fleets and more DC space. Furthermore, Transportation firms generally have more heavy-duty trucks and much fewer medium-duty trucks, while firms in all other sectors strongly prefer medium-duty fleets. Food Services and other Retail firms have the greatest preference for owning or leasing their own DCs, followed by Manufacturing, Wholesale, and Transportation firms. A case study is developed for the city of Chicago using a high-performance ABM framework designed for simulating large-scale transportation systems. Transportation modelers and policymakers can use findings and methods from this research to study freight operations in large cities.