Collaborative Research: CPS: Medium: Population Games for Cyber-Physical Systems: New Theory with Tools for Transportation Management under Extreme Demand

交通网络需求的突然激增会破坏这些网络规划和运营的平衡条件。对人口在极端需求下的战略选择缺乏了解，可能会导致矛盾的结果，例如旨在拯救生命的疏散反而造成道路上的大规模伤亡，或者开辟新建道路增加而不是减少旅行时间。本项目将设计管理人口战略选择的系统和程序（例如，是疏散还是就地避难，采取哪些逃生路线）和当局的行动（例如，哪些区域要疏散以及以何种顺序、将交通路由到何处、是否在给定方向上关闭一些道路或开放额外的车道）。该项目产生的工具将使更好的响应系统能够帮助地方当局管理极端需求，例如当整个县必须疏散以保护居民免受野火的侵害时。该项目将开发一个建模和仿真工具链，以预测交通瓶颈的位置及其严重程度，以及预期的旅行时间和延误，从而确定结果的频谱，识别最坏的情况，并使当局能够做出明智的决策。该技术方法植根于人口游戏，它模拟了大量竞争资源的代理之间的战略非合作互动的动态。然而，该项目将偏离现有理论的平衡焦点，并将提供瞬态分析工具，不仅考虑代理商的策略修订，还考虑大量的网络和物理动态，如交通流中的动态，交叉口的响应信号控制，向代理商传播信息，以及危险的演变，如火灾传播。研究任务，使该项目的愿景的“网络物理人口博弈论”包括表征瞬态行为与系统理论的方法，占不确定性的战略修订模型，扩展理论的用户偏好的连续体，重新思考随机过程的基础上的动态模型，修改理论的短期视野的时间紧迫的行动，学习动态模型的数据，并制定广泛的形式之间的游戏人口和一个单一的代理人，由人口响应疏散命令的动机。此外，该项目将确定控制措施（如响应信号政策、道路封闭、禁用某些转弯），以关闭数据-决策-行动循环，并将动态转向理想的结果，避免不安全的结果。该奖项反映了NSF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。

A sudden surge in demand in traffic networks disrupts the equilibrium conditions upon which these networks are planned and operated. Lack of understanding of the population's strategic choices under extreme demand may result in paradoxical outcomes, such as evacuations aiming to save lives instead resulting in mass casualties on the road or opening up of new roads increasing rather than decreasing travel time. This project will devise systems and procedures for managing the strategic choices of populations (e.g., whether to evacuate or shelter in place, which escape routes to take) and the actions of the authorities (e.g., which zones to evacuate and in which sequence, where to route the traffic, whether to close some roads or open extra lanes in a given direction). The tools resulting from this project will enable better response systems to assist local authorities in managing extreme demand, such as when entire counties have to be evacuated to protect the residents from a wildfire. The project will develop a modeling and simulation tool chain to predict traffic bottleneck locations and their severity together with expected travel times and delays, thus determining the spectrum of outcomes, identifying worst cases, and enabling the authorities to make informed decisions.The technical approach is rooted in population games, which model the dynamics of strategic noncooperative interactions among large populations of agents competing for resources. The project, however, will depart from the equilibrium focus of the existing theory and will offer transient analysis tools that account for not only the strategy revisions of the agents, but also a host of cyber and physical dynamics, such as queueing dynamics in traffic flow, responsive signal control at intersections, information dissemination to agents, and evolution of hazards, such as fire propagation. The research tasks to enable the project's vision of a "cyber-physical population game theory" include characterizing transient behavior with system-theoretic methods, accounting for uncertainty in strategy revision models, extending the theory to a continuum of user preferences, rethinking the stochastic processes underlying the dynamical models, modifying the theory for short-term horizons for time-critical operations, learning dynamical models from data, and formulating extensive form games between a population and a single agent, motivated by the population response to evacuation orders. In addition, the project will identify control actions (such as responsive signal policies, road closures, disabling certain turns) to close the data-decision-action loop and steer the dynamics towards desirable outcomes and avoiding unsafe ones.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.