CPS: Synergy: Cyber Physical Regional Freight Transportation System Start

该项目的目标是开发优化和控制技术，并将其与实时仿真模型相结合，以实现复杂网络中的负载平衡。应用案例为区域货运系统。货物在铁路和公路网络上移动，乘客也共享这些网络。尽管这些网络高度相互依赖，但如今它们各自独立运作，其结果是效率低下，造成拥堵、污染和燃料消耗过剩。例如，这些低效率可以通过跨越时间和空间的需求峰值来观察。效率低下的部分原因是缺乏信息和适当的工具，部分原因是缺乏促进更综合行动的政策和体制结构。由于将有大量的实时数据可供决策，因此问题变得更加复杂。本研究发展了一种称为COSMO的新方法的理论基础，该方法可以平衡具有时空特征的复杂动态网络的负载。与目前使用简单数学模型来预测网络状态的做法相反，该方法采用计算模拟模型，通过考虑动态和复杂的相互作用，在估计网络状态方面要准确得多。本项目开发了网络物理系统的优化和负载平衡控制部分，并将其与以货运为驱动应用领域的实时网络仿真模型相结合。该研究还探讨了如何将已确定的障碍和政策问题/激励措施纳入优化的动态货运平衡系统中的数学约束和/或控制变量。支持分析的数据可能包括货运特性、交通、天气和其他大数据量。该项目将利用洛杉矶/长滩地区港口的实时数据来验证该方法。洛杉矶/长滩港是进入西海岸的大部分货物的入境港，并提供了丰富的数据集，这些数据集将刺激该模型，特别是在涉及公路/铁路/港口网络之间相互作用的区域运输中。这一重要运输领域的基础技术可以直接应用于其他大型货运中心，也可以应用于其他应用领域，包括网络和智能电网。除了更有效地分配交通资源所产生的更广泛的影响外，该项目还提供教育推广和制作课程模块。

The objective of this project is to develop optimization and control techniques and integrate them with real-time simulation models to achieve load balancing in complex networks. The application case is the regional freight system. Freight moves on rail and road networks which are also shared by passengers. These networks today work independently, even though they are highly interdependent, and the result is inefficiencies in the form of congestion, pollution, and excess fuel consumption. These inefficiencies are observed for example by the peaks of demand across time and space. Inefficiencies exist in part due to lack of information and appropriate tools, and in part due to lack of policies and institutional structures that would promote more integrated operations. The problem is made even more complex due to the large quantities of real time data that will be available to inform the decision-making.This research develops the theoretical foundations of a new approach referred to as COSMO to balance loads across complex dynamical networks with temporal and spacial characteristics. In contrast to current practices where simple mathematical models are used to predict the states of the network the method employs computational simulation models that are far more accurate in estimating the states of the network by taking into account dynamics and complex interactions. The project develops the optimization and load balancing control segments of the cyber physical system and integrate them with real time network simulation models using freight transportation as the driving application area. The research also examines how identified barriers and policy issues/incentives can be incorporated as mathematical constraints and/or control variables in the optimized dynamic freight load balancing system. Data supporting the analysis may include freight characterization, traffic, weather, and other large data volumes. The project will utilize real time data from the port of Los Angeles /Long Beach area to validate the approach. The port of Los Angeles/Long Beach is the port of entry for much of the freight that enters the West Coast, and provides rich sets of data that will stimulate the model especially in regional transportation involving interaction between road/rail/port networks. This fundamental technology in this important transportation domain with direct applications to other large scale freight centers, can be applied to other application domains including networking and smart grid. Besides the broader impact derived from more efficient allocation of transportation resources, the project also provide educational outreach and produce course modules.