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支持新兴基础设施系统的决策，从而促进国家公平和福利，弱势群体也将参与其中。新兴的基础设施系统，如共享电动滑板车系统，对公共交通等现有民用基础设施的影响越来越大，但由于此类系统的高运行动态，如何系统可靠地量化公平性尚不清楚。该奖项将有助于更深入、更全面地理解公平性的作用，以及在这些新兴基础设施系统的设计和运营中考虑公平性时产生的相关权衡。研究结果将整合到本科和研究生课程中，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，项目团队将根据研究结果为佛罗里达大学的“成功转型和加强本科生准备”项目和史蒂文斯理工学院的“高中虚拟暑期研究项目”准备教育材料，以吸引高中毕业生，特别是女性和少数族裔。本项目旨在创建一个新的框架，用于设计各种公平措施，以有效评估新兴基础设施系统中的公平性，在这些系统中，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限定新系统对不同人口群体的积极和消极影响。这些效用评估将通过结合多种公平观点的社会福利函数映射到公平值。此外，该项目将开发新的优化模型，以解决操作动力学问题，以保持公平性和有效的精确解决方法，例如基于理论分析的定制Benders分解方法，以及高质量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。将对共享微移动系统进行案例研究，并使用公开可用的真实世界数据进行广泛的实验，以分析权衡并为决策提供见解。该奖项反映了美国国家科学基金会的法定使命，并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。