Implementation of Activity-Based Model Training: All Hell Didn't Break Loose
Corresponding Author: Kyeil Kim, Atlanta Regional Commission
Presented By: Rosella Picado, WSP
Abstract
In 2016, the Atlanta Regional Commission (ARC) adopted the newly developed activity-based model (ABM) as the official travel demand model for regional travel forecasting in metro Atlanta, phasing out the trip-based model (TBM). Transition to this advanced model posed some challenges to potential users primarily due to the significant difference in model design between the two models. At the time of this modeling paradigm shift, many TBM users had not yet gained knowledge on ABMs and/or the technical skills to operate it. In addition, there were common misconceptions with regard to hardware requirements, cost to operate, and software experience. ARC’s main challenges were to resolve these misconceptions and to ensure potential ABM users have a comfortable understanding of the model.
Prior to adoption of the ABM, ARC recognized that a model is only beneficial if end users are able to apply it and make sense of the results to support regional planning decisions. In light of that, ARC surveyed the local modeling community to measure their familiarity with ABMs, their modeling needs, concerns about the new model, and willingness to participate in the training. Training consisted of four incremental sessions held over the span of five months that addressed the needs revealed by the survey. These sessions were designed to guide the trainees in ABM theory, install and operate the model, gain deeper understanding of its inputs and outputs, and learn how to use it for typical planning applications. ARC’s outreach efforts also included releasing detailed model documentation and the establishment of the ABM Focus Group. The Focus Group is a communication channel between model developers and end users, meeting quarterly to exchange updates and learn from each other as experience with the ABM grows.
This paper will discuss the challenges ARC faced with this training initiative. A training method ARC designed to maximize the effort will be presented along with a plan for deploying the training materials. Finally, the lessons learned from this initiative will be shared and recommendations for other agencies that are planning for similar trainings will be made.