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

土地利用模式和现有交通系统在决定城市地区的经济活力、宜居性和可持续性方面发挥着关键作用。交通运输与土地利用密切相关，土地利用和交通运输都对环境产生重大影响，特别是在排放、资源消耗和开放空间方面。政府的政策和投资以许多复杂的、有时是意想不到的方式影响着土地使用和交通的模式。在之前的支持下，研究团队开发了UrbanSim，这是一个复杂的模拟系统，用于模拟城市发展。其目标是提供强有力的技术支持，帮助政府机构和公民做出更明智的决策，并使利益相关者能够考虑不同的情景、一揽子可能的政策和投资，然后，基于这些备选方案，对这些情景在20年或更长时间内的影响进行建模。然而，重大挑战依然存在。在提出的研究中，以综合的方式解决了两个重要的问题：首先，评估和表示不确定性；其次，为广泛的利益相关者以适当的方式支持结果的呈现和与模拟的交互。预测未来是一件冒险的事情。在我们正在开发的这种城市模拟中，有许多复杂的、相互作用的不确定性来源。这些误差包括测量误差（如输入数据中缺失或不正确的信息）、外生数据和其他输入参数的不确定性（例如，关于宏观经济预测）、系统误差（例如，由于抽样问题）以及由模型结构和模拟的随机性质引起的不确定性。然而，公民和政府确实必须利用现有的最佳信息做出决定。与此同时，有必要尽可能地表示结论中的不确定性，这既是为了真实性，也是为了帮助在备选方案中进行选择的重要数据。例如，选择一个明显不太理想的替代方案可能是可取的，如果它实质上减少了不确定性，或者提供了更大的灵活性来处理具有特别高不确定性的情况。为了在政治进程中发挥有用和合法的作用，模拟备选方案的结果必须以有用的方式呈现给该地区的民选官员和公民，让他们根据对他们重要的事情了解备选方案。我们展示这些结果的主要工具是指标；从模拟的大量输出中提取感兴趣的属性的数值量。当不确定性通过模型和指标值传播时，这些表示应该包括对不确定性的清晰和有用的表示。此外，研究可能不仅仅是简单地展示结果，以支持利益相关者能够通过网络界面探索和测试替代方案（以及围绕它们的不确定性）。这个建议是基于两个主要研究领域的研究挑战。1)在计算统计学中，这些是通过复杂的建模系统来开发、分析和验证表示和传播不确定性的技术。该研究方法利用了贝叶斯融合的初步结果。我们需要新的统计方法来适应UrbanSim带来的挑战，包括模型的随机性、测量和系统误差的大影响、模型输入和输出的高维以及底层模型的大量运行时间。2)然而，除了统计方面的挑战外，采用这种方法对计算的要求也很高；实现可接受的性能将需要算法的进步，以及健全的软件工程。在人机交互中，研究挑战之一是支持有意义的利益相关者访问和与复杂模拟的交互，包括不确定性的表示。最后，在设计科学的新兴领域，一个重要的问题是如何设计和评估整个系统，以一种原则性的方式，以支持这样的基本价值观，如准确地呈现结果（包括局限性和不确定性）和透明度。更广泛的影响如果这项工作取得成功，UrbanSim有可能极大地帮助公众审议有关城市扩张、经济健康、可持续性和其他问题的重大决策。Urban Sim是开源和免费的，并且已经吸引了大量的兴趣和使用。此外，计算统计的结果应适用于广泛的经济或环境过程的模拟，以便为公共政策的制定和审议提供信息。最后，交互技术和发现应该适用于与复杂模型和信息来源的一系列其他利益相关者的交互。

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.