Modeling Uncertainty in Land Use and Transportation Policy Impacts: Statistical Methods, Computational Algorithms, and Stakeholder Interaction

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Patterns of land use and available transportation systems play a critical role in determining the economic vitality, livability, and sustainability of urban areas. Transportation interacts strongly with land use, and both land use and transportation has substantial environmental effects, in particular on emissions, resource consumption, and open space. Government policies and investments affect patterns of land use and transportation in many, complex, and sometimes unintended ways. With prior supportthe research team has developed UrbanSim, a sophisticated simulation system to model urban development. The goal is to provide strong technical support to help government agencies and citizens make more informed decisions and to allow stakeholders to be able to consider different scenarios, packages of possible policies and investments, and then, based on these alternatives, model the effects of these scenarios over periods of twenty or more years. However, major challenges remain. Two significant ones are addressed in an integrated fashion in the research proposed : first, assessing and representing uncertainty; and second, supporting presentation of results and interaction with the simulation in an appropriate way for a wide range of stakeholders. Predicting the future is a risky business. There are numerous, complex, and interacting sources of uncertainty in urban simulations of the sort we are developing. These include measurement errors (such as missing or incorrect information in the input data), uncertainty regarding exogenous data and other input parameters (for example, regarding a macroeconomic forecast), systematic errors (for example, due to problems with sampling), and uncertainty arising from the model structure and from the stochastic nature of the simulation. Nevertheless, citizens and governments do have to make decisions, using the best available information. At the same time, it is necessary to represent the uncertainty in conclusions as well as possible, both for truthfulness and as important data to assist in selecting among alternatives. For example, iti may be desirable to select an apparently slightly less desirable alternative, if it substantially reduced uncertainty, or provided more flexibility to address situations with particularly high uncertainty. To play a useful and legitimate role in the political process, the results from modeling alternate scenarios must be presented in useful ways to elected officials and citizens in the region, in ways that let them understand the alternatives in light of what is important to them. Our primary tool for presenting these results are indicator; numeric quantitiesthat distill attributes of interest from the voluminous output of the simulation. These presentations should include clear and useful representations of uncertainty, as it propagates through the model and to the indicator values. In addition, the research may go beyond simply presenting the results to support stakeholders in being able to explore and test alternate scenarios (and the uncertainties around them), via a web interface.Intellectual MeritThis proposal is grounded in the research challenges in the two principal areas of research. 1) In computational statistics these are developing, analyzing, and validating techniques for representing and propagating uncertainty through a sophisticated modeling system. The research approach uses promising but preliminary results in Bayesian melding. New statistical methods may be needed which are adapted to the challenges posed by UrbanSim, including model stochasticity, large effects of measurement and systematic errors, high dimension of model inputs and outputs, and significant running time for the underlying model. 2) In addition to the statistical challenges, however, undertaking this approach makes extreme computational demands; and achieving acceptable performance will require algorithmic advances, as well as sound software engineering. In human computer interaction, among the research challenges are supporting meaningful stakeholder access to and interaction with complex simulations, including representations of uncertainty. Finally, in the emerging area of science of design, an important question is how to design and evaluate the system overall, in a principled way, to support such basic values as accurate presentation of results (including limitations and uncertainties) and transparency.Broader ImpactsIf this work succeeds, UrbanSim has the potential to significantly aid in public deliberation over major decisions regarding urban sprawl, economic health, sustainability, and other issues. Urban Sim is Open Source and freely available, and has attracted considerable interest and use. Further, the results in computational statistics should be applicable to a broad range of simulations of economic or environmental processes to inform public policy development and deliberation. Finally, the interaction techniques and findings should be applicable to a range of other stakeholder interactions with complex models and sources ofinformation.