The video begins at 1:18.
Abstract: Models are used for many different purposes. Some seek to impart understanding of the system under study, while others seeks to understand dynamics. Most of the models considered in this course are also used for forecasting likely future levels of demand and its impact upon the built and natural environment. Unlike models of purely physical systems these models attempt to capture the interactions between people and institutions. Social systems are considerably more complex and chaotic. They are shaped by disruptive technologies, changing markets, economic cycles, and cultural influences that a difficult to predict, much less their subtle (and sometimes not so subtle) interaction effects. Uncertainty creeps into forecasting as a result, creating risk that a policy or investment may have unintended consequences, under-perform, or be short-lived. Transportation and land use modelers have typically only weakly accommodated such realities in their forecasts. Policy-makers and investors are increasingly demanding a more explicit accounting of risk and uncertainty in forecasting. This discussion will focus on how this will affect the practice of modeling in the future.
Speaker Bio: Rick Donnelly has over 25 years of experience in the modeling and simulation of transportation systems, from the urban to national level. His current interests include agent-based modeling of freight and logistics, integrated land use-transportation models, and dynamic network modeling. Rick leads the travel modeling and simulation practice at Parsons Brinckerhoff, an international civil and transportation engineering consultancy. He is also a senior fellow at the University of Melbourne, where he earned his doctorate in engineering, and a visiting scholar at Los Alamos National Laboratory.