CAREER: Optimizing the Selection of Added Capacity Trans- portation Infrastructure Improvements

PI: Debbie A. Niemeier， U. California at Davis，“职业：优化运输基础设施改进的选择”，交通系统的复杂性日益增加，要求工程师在特定项目的资源分配问题上提供理论指导。正在使用的具体方案模型寻求在不与其他供资类别联系的情况下，在基于工程的供资类别内优化资源。这项研究将解决这一理论差距，并将提供必要的框架，以优化未来的基础设施投资，从而提高整个交通系统的生产力，包括寿命和性能。工作计划的具体目标包括：1)建立一个新的理论优化模型，在交通基础设施项目之间动态分配资金；2)指定并评估经验模型以进行验证；3)制定新的绩效指标，将资金分配与绩效联系起来；4)制定新的指导方针，以更好地将基础设施融资政策与系统性能优化联系起来。教育机会将增加，包括研究生和本科生研究人员的机会，并通过直接利用本科生和研究生交通课程的结果。新的理论模型将允许交通运输机构在优化整体基础设施性能的框架内工作。理论和实证模型将用于制定新的政策指导方针：1)评估维持特定水平的总系统性能所需的资金数量，2)优化支出计划之间的资源分配，以及3)协助开发适当的数据库以监测长期基础设施性能。这些结果将在推进评估和维护整体基础设施系统生产力的概念方面发挥至关重要的作用，而不是专注于离散的基础设施性能。＊＊＊

Abstract Proposal: CMS 97-03319 PI: Debbie A. Niemeier, U. California at Davis "Career: Optimizing the Selection of Added Capacity Transportation Infrastructure Improvements " The increasing complexity of transportation systems demands that engineers provide theoretical guidance on the issue of program-specific resource allocation. Program-specific models in use seek to optimize resources within an engineering-based funding category without linkage to other funding categories. This research will address this theoretical gap and will provide the necessary framework to optimize future infrastructure investments in such a way that the overall transportation system productivity, including both longevity and performance, is enhanced. Specific objectives of the workplan include to: 1) develop a new theoretical optimization model to dynamically allocate funds between transportation infrastructure programs; 2) specify and evaluate an empirical model for validation; 3) develop new performance measures that relate funding allocation to performance; and 4) develop new guidelines to better link infrastructure funding policies and system performance optimization. Educational opportunities will be enhanced by including opportunities for both graduate and undergraduate researchers, and by directly utilizing the results in undergraduate and graduate transportation courses. The new theoretical model will allow transportation agencies to work within a framework that optimizes total infrastructure performance. The theoretical and empirical models will be used to develop new policy guidelines for 1) assessing the amount of funding required to maintain a specified level of total system performance, 2) optimizing resource allocations among spending programs, and 3) to assist in the development of appropriate data bases to monitor long-term infrastructure performance. These results will play a crucial role in advancing the concept of evaluating and maintaining tota l infrastructure system productivity as opposed to concentrating on discrete infrastructure performance. ***