Stable Matching of Service Tours to Design Cooperative Policies for Transport Infrastructure Systems

运输技术已经发展到不能再作为孤立的系统来评价的地步。在当今数据、信息和通信技术无处不在的时代，城市出行选择越来越丰富：例如，拼车、汽车/自行车共享和需求响应型交通。在灾难和大规模事件中，多个机构之间的移动解决方案协调越来越具有挑战性。本研究的解决方案涉及对运输网络的供需分配模型的仔细重新检查。它结合了稳定匹配理论和网络分析对交通规划的变革性影响，以及应用于基础设施系统的博弈论。政策制定者将能够与不同的运输运营商设计合作政策，如票价捆绑、服务租赁、资产托管，以进一步鼓励像堪萨斯城和Bridj这样的合作伙伴关系。同样的方法也可用于灾害规划中的资源风险集中。该项目将支持对一些来自少数族裔的研究生、本科生和K-12 STEM学生进行交通系统和博弈论方面的培训。它将通过在交通规划中定义与初创公司和孵化器合作的新功能角色，推动创新和创业。这项研究分为两个研究重点。第一部分是核心理论的发展，包括将交通分配作为多对一稳定匹配分配博弈的模型构建和算法开发。这样做将不再像目前的方法那样假定运输供应是固定的。然后将该模型扩展为多对多博弈，使其涉及多个操作者，从而可以评估他们之间的合作策略。第二个重点是理论的应用，其中两个是灾害管理中的共享移动系统和风险分担策略。处理共享出行服务的定制模型允许决策者评估特定的共享出行服务，如共享单车或共享出租车。当模型考虑不确定性时，可以设计多个作业者之间的合作策略，将风险集中在一起，使其对单个作业者的影响最小化。该研究挑战了60多年来对交通模型的研究，该模型是考虑出行者和操作员行为的供需相互作用的替代理论。

Transportation technologies have reached a point where they can no longer be evaluated as systems in isolation. Urban travel options have become increasingly abundant in today's age of ubiquitous data and information and communications technologies: e.g. ridesharing, vehicle/bike sharing, and demand-responsive transit. Coordination of mobility solutions between multiple agencies during disasters and large scale incidents is increasingly more challenging. The solution in this study involves a careful reexamination of the supply-demand assignment models for transportation networks. It combines stable matching theory with network analysis for transformative impacts on transportation planning and game theory as applied to infrastructure systems. Policy-makers will be able to design cooperative policies with different transport operators, such as fare bundling, service leasing, asset co-location, to further encourage partnerships like that of Kansas City and Bridj. The same methodology can be used for risk pooling of resources in planning for disasters. The project will support training of a number of graduate, undergraduate, and K-12 STEM students from under-represented minorities in transportation systems and game theory. It will drive innovation and entrepreneurship by defining new functional roles in transportation planning that would engage with startup companies and incubators.The study is split into two research thrusts. The first focuses on development of the core theory, which includes model formulation and algorithm development for traffic assignment as a many-to-one stable matching assignment game. Doing so would no longer assume that the transportation supply is fixed as in current methods. The model is then expanded to a many-to-many game to involve multiple operators so that cooperative policies between them can be evaluated. The second thrust focuses on applications of the theory, two of which are shared mobility systems and risk pooling strategies in disaster management. Customizations of the model to handle shared mobility services allow policymakers to evaluate specific shared mobility services like bike sharing or shared taxis. When the model is considered under uncertainty, cooperative strategies between multiple operators can be designed to pool risks together to minimize their impacts on individual operators. The study challenges over 60 years of research in transport modeling as an alternative theory of supply-demand interaction that considers both traveler and operator behavior.