CDI-Type I: Freeway Corridor Operations Design and Implementation

计算思维(CT)给许多服务部门带来了革命性的生产率提高，但它并没有触及生产率长期下降的道路运输服务部门。拟议的研究将通过大幅改进交通业务的所有主要组成部分来大幅提高道路运输生产率：数据收集和处理；模型校准和状态估计；以及规划、设计和实施实时控制。CDI主题在拟议工作的三项主要研究任务中占有重要地位。理解复杂性道路网络是一个由高速公路和城市街道的路段组成的相互连接的大系统，车辆和司机在这个系统上移动和相互作用，创造一个复杂的、非线性的、社会物理的动态交通系统。道路交叉口有可编程的控制设备(交叉口信号、匝道计时器、宣布限速的信息标志、通行费、旅客信息和建议等)来规范交通的演变。通过为这些控制设备开发和实施复杂的反馈策略，可以实现公路网效率的显著提高。制定这些策略所需的研究需要在数学分析和模拟的基础上了解底层动态交通系统的行为。这是第一项重大任务。从数据到模型交通系统非线性动态模型的描述和标定需要大量的历史交通数据。反馈算法的实现需要基于实时测量来估计交通系统的当前状态。这项研究将开发模型参数的统计估计、存档数据和模拟的可视化以及实时交通传感器数据的基于模型的处理的程序。这是第二项重大任务。虚拟组织交通当局必须执行反馈控制政策，但他们缺乏必要的计算思维技能和知识。因此，需要学术研究人员和运输人员之间的合作，以培训后者进行计算思维，并教育前者了解运输人员面临的体制和其他现实世界的制约因素。这种协作需要建立真正伙伴关系的信任，并借助电子手段促进地理上和体制上相距遥远的群体之间的合作。建立这种协作和实施拟议的反馈算法是第三项主要任务。

Computational Thinking (CT) brought revolutionary productivity increases in many service sectors, but it has not touched the road transportation service sector whose productivity has been declining for a long time. The proposed research will enable a major increase in road transportation productivity through a dramatic improvement in all major components of traffic operations: data collection and processing; model calibration and state estimation; and planning, design and implementation of real-time control. The CDI themes figure in the three major research tasks of the proposed effort. Understanding complexity A road network is a large interconnected system of linkssegments of freeways and urban streetson which vehicles and drivers move and interact to create a complex, nonlinear, socio-physical dynamical traffic system. Link junctions have programmable control devices (intersection signals, ramp meters, message signs announcing speed limits, tolls, traveler information and advice, etc.) that regulate the evolution of traffic. A major increase in efficiency of the road network can be achieved by developing and implementing sophisticated feedback policies for these control devices. The research needed to develop these policies requires understanding the behavior of the underlying dynamical traffic system, based on mathematical analysis and simulation. This is the first major task. Data to models The specification and calibration of nonlinear dynamical models of the traffic system require large amounts of historical traffic data. The implementation of feedback algorithms requires estimates of the current state of the traffic system, based on real-time measurements. The research will develop procedures for statistical estimation of model parameters, visualization of archived data and simulations, and model-based processing of real-time traffic sensor data. This is the second major task. Virtual organization Transportation authorities must implement the feedback control policies, but they lack necessary skills and knowledge of computational thinking. Thus collaboration between academic researchers and transportation personnel is needed to train the latter in computational thinking and to educate the former about the institutional and other real-world constraints facing transportation personnel. Such collaboration requires trust underlying a true partnership, and assistance with electronic means to facilitate cooperation among physically and institutionally remote groups. Building this collaboration and implementing the proposed feedback algorithms is the third major task.