Collaborative Research: Advancing Fairness for Emerging Infrastructure Systems with High Operational Dynamics

合作研究：促进具有高运营动态的新兴基础设施系统的公平性

• 批准号: 2309667
• 负责人: Yu Yang
• 金额: $ 29.05万
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2026-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2309667&HistoricalAwards=false
• 关键词: Collaborative; Research; Advancing; Fairness; Emerging

This collaborative research project will advance national equity and welfare by developing diverse fairness measures to support policy-making for emerging infrastructure systems with disadvantaged populations involved. Emerging infrastructure systems, such as shared e-scooter systems, are increasingly impacting existing civil infrastructures like public transit, but it remains unclear how to systematically and reliably quantify fairness in such systems due to high operational dynamics. This award will contribute to a deeper and more comprehensive understanding of the role of fairness and the associated tradeoffs that arise when considering fairness in the design and operations of these emerging infrastructure systems. The research findings will be integrated into undergraduate and graduate courses to educate students on the challenges of measuring and promoting fairness in civil infrastructures amid the impact of emerging technologies. Moreover, the project team will prepare educational material based on the findings for the Successful Transition and Enhanced Preparation for Undergraduates Program at the University of Florida and the High School Virtual Summer Research Program at the Stevens Institute of Technology to attract high school graduates, particularly women and minorities.This project aims to create a novel framework for designing diverse fairness measures that can effectively evaluate fairness in emerging infrastructure systems where conflicting interests from stakeholders and inherent complex dynamics pose unique challenges. The framework will use multi-level utility functions to qualify the positive and negative impacts of an emerging system on various population groups. These utility evaluations will be mapped to a fairness value by a social welfare function that combines multiple fairness perspectives. Additionally, the project will develop new optimization models for addressing operational dynamics to preserve fairness and effective exact solution methods, such as a customized Benders decomposition method based on theoretical analysis and a specialized generation and selection procedure for high-quality Benders cuts. A data-driven approach will be employed to construct an uncertainty set to compute a robust estimation of the price of fairness for any given fairness level under a specific fairness measure. A case study on shared micro-mobility systems and extensive experiments using publicly available real-world data will be conducted to analyze the tradeoffs and provide insights for policy-making.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这一合作研究项目将通过制定各种公平措施来促进国家公平和福利，以支持涉及弱势群体的新兴基础设施系统的决策。新兴的基础设施系统，如共享电动滑板车系统，正在越来越多地影响现有的民用基础设施，如公共交通，但由于高度的运营动态性，如何系统地、可靠地量化此类系统的公平性仍不清楚。该奖项将有助于更深入、更全面地了解公平的作用，以及在考虑这些新兴基础设施系统的设计和运营中的公平性时出现的相关权衡。研究结果将被纳入本科和研究生课程，以教育学生在新兴技术的影响下衡量和促进民用基础设施公平性的挑战。此外，项目小组将根据佛罗里达大学本科生成功过渡和强化准备项目和史蒂文斯理工学院高中虚拟暑期研究项目的调查结果编写教育材料，以吸引高中毕业生，特别是妇女和少数族裔。该项目旨在创建一个新颖的框架，用于设计各种公平措施，以有效地评估在新兴基础设施系统中，利益相关者的利益冲突和固有的复杂动态构成了独特的挑战。该框架将使用多层次效用函数来定性一个新兴系统对不同人口群体的积极和消极影响。这些效用评价将被映射到一个公平值的社会福利函数，结合多个公平的角度。此外，该项目还将开发新的优化模型，用于解决操作动态问题，以保持公平性和有效的精确求解方法，例如基于理论分析的定制Benders分解方法以及用于高质量Benders切割的专门生成和选择程序。将采用数据驱动的方法来构建一个不确定性集，以计算在特定公平措施下任何给定公平水平的公平价格的稳健估计。该奖项反映了NSF的法定使命，通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。