Large-scale agent-based traffic micro-simulation: Experiences with model refinement, calibration, validation and application

This paper describes the authors' continued efforts toward the development, calibration, validation and application of a large-scale, agent-based model of the Buffalo-Niagara metropolitan area. The model is developed using the TRansportation ANalysis SIMulation System (TRANSIMS), an open-source, agent-based suite of transportation models originally developed by Los Alamos National Lab (LANL). Following the network error-checking, calibration and validation phases of the model development cycle, the model was used to evaluate the impact of significant snow storm events on the performance of surface transportation network. This was done by modifying the behavior of the agents (i.e. the drivers) in the model to reflect more conservative driving behavior and vehicle dynamics limitations (such as maximum acceleration and deceleration) imposed by the impaired road surface condition. The study demonstrates that the development of regional agent-based models is technically feasible, but one that requires significant efforts in terms of network accuracy checking, model calibration and validation. Moreover, it is shown that inclement weather events reduce the ability of transportation networks to handle the travel demand, which in turn underscores the importance of effective travel demand management during such events.