Data-enabled Decision-Making in Emerging Co-opetitive Transportation Markets with Ambiguity

最近的通信和技术进步，以及日益丰富的传感器和用户数据，使新的合作机制和运输服务匹配需求成为可能。这些新发现的功能突出了运输系统从中央控制、公共拥有和运营的基础设施到分散系统元素的变化。这些系统涉及在竞争环境中运作的多个利益相关者，其中个人或设施可能通过潜在的共同市场问题联系在一起，从而从合作中受益。也就是说，这些环境是合作竞争的。该研究项目的总体目标是开发和测试在新出现的合作竞争环境中构建动态、不确定和分散运输问题的概念，并创建有效的、数据支持的优化和平衡算法，以支持这些未来运输服务的运营。已开发的方法将有助于操作点对点系统，在这种系统中，个人可以成为供应商，也可以成为系统聚合者。模型和解决方案方法将利用个性化信息为单个系统用户定制服务，并更好地了解未来的交通系统。因此，这项工作将能够评估新的市场概念和调节它们的机制。通过开发一个以博客文章、小品和视频片段形式提供电子学习片段的在线图书馆，并努力让代表性不足的人和第一代大学生参与进来，该项目将扩大代表性不足的群体参与研究，并对工程教育产生积极影响。博弈论、概率建模和模糊、数据分析和模型预测控制的概念将被应用和扩展，用于实时多玩家、多层次、高维度的模糊设置。封闭形式的解将伴随着严格的数学推导和证明。将创建既可以应用于长期决策范围又可以应用于实时实现的解决方案方法。两者都将通过了解消费者/用户行为和竞争对手的行为来利用信息。这项工作旨在支持交通领域的转型，将经济学、数学和控制等不同领域的概念引入未来的市场和合作中，同时通过对建模和解决方案方法的基本贡献提供持久的价值。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。

Recent communications and technological advancements, along with a growing abundance of sensor and user data, enable new mechanisms of cooperation and matching of transportation services to demand. These newfound capabilities highlight changes in moving transportation systems from centrally controlled, publicly owned and operated infrastructures to decentralized system elements. These systems involve multiple stakeholders who operate in competitive environments wherein individuals or facilities may be linked through an underlying common market problem creating benefit from cooperation. That is, these environments are co-opetitive. The overarching objective of this research project is to develop and test concepts that frame dynamic, uncertain and decentralized transportation problems in newly arising co-opetitive environments and create efficient, data-enabled optimization and equilibrium algorithms to support the operation of these future transport services. Developed methods will aid in operating peer-to-peer systems, where individuals can become suppliers, as well as system aggregators. The models and solution methods will exploit personalized information to customize services to individual system users and to better understand transportation systems of the future. Thus, this work will enable assessment of novel market concepts and mechanisms for regulating them. Through the development of an on-line library of e-learning snippets in the form of blog posts, vignettes and video clips, and efforts to involve underrepresented persons and first-generation college students, this project will broaden participation of underrepresented groups in research and positively impact engineering education.Concepts from game theory, probability modeling and ambiguity, data analytics, and model predictive control will be employed and extended for use in real-time multi-player, multi-level, ambiguous settings with high dimensionality. Closed-form solutions will be accompanied by rigorous mathematical derivation and proof. Solution methods that can be applied both for long-term decision horizons and real-time implementations will be created. Both will take advantage of information through learning about consumer/user behavior and that of competitors. This work aims to support transformation of the field of transportation, bringing concepts from diverse areas of economics, mathematics and control to envision and run markets and collaborations of the future, while simultaneously providing lasting value through fundamental contributions to both modeling and solution methodology.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.