An agent-based model of origin destination estimation (ABODE)

This paper introduces ABODE, an agent-based model for Origin-Destination (OD) demand estimation, that can serve as a work trip distribution model. The model takes residential locations of workers and the locations of employers as exogenous and deals specifically with the interactions between firms and workers in creating a job-worker match and the commute outcomes. It is meant to illustrate that by explicitly modeling the search and hiring process, origins and destinations (ODs) can be linked at a disaggregate level that is reasonably true to the actual process. The model is tested on a toy-city as well as using data from the Twin Cities area. The toy-city model illustrates that the model predicts reasonable commute outcomes, with agents selecting the closest workplace when wage and skill differentiation is absent in the labor market. The introduction of wage dispersion and skill differentiation increases the average home to work distances considerably. Using data from Twin Cities area of Minneapolis-St. Paul, we also show that the model captures aggregate commute outcomes well. Overall, the results suggest that the behavior rules as implemented lead to reasonable patterns. Future improvements and directions are also discussed.