CDI-Type I: Freeway Corridor Operations Design and Implementation

计算思维（CT）在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善交通运营的所有主要组成部分来大幅提高道路运输生产力：数据收集和处理;模型校准和状态估计;以及实时控制的规划，设计和实施。土发委会的主题是拟议工作的三项主要研究任务。道路网络是一个由高速公路和城市街道组成的大型互联系统，车辆和驾驶员在其上移动并相互作用，形成一个复杂的、非线性的、社会物理动态交通系统。连接点有可编程控制装置（交叉口信号、匝道仪表、限速信息标志、通行费、旅客信息和建议等）。来调节交通的发展。通过为这些控制设备开发和实施复杂的反馈策略，可以实现道路网络效率的大幅提高。制定这些政策所需的研究需要基于数学分析和模拟来了解底层动态交通系统的行为。这是第一个主要任务。数据到模型交通系统的非线性动态模型的规格和校准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。该研究将开发模型参数的统计估计程序，存档数据和模拟的可视化，以及基于模型的实时交通传感器数据处理。这是第二个主要任务。虚拟组织交通管理部门必须实施反馈控制策略，但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，以训练后者的计算思维，并教育前者的制度和其他现实世界的限制面临的运输人员。这种合作需要真正的伙伴关系基础上的信任，以及电子手段的协助，以促进地理上和体制上相距遥远的群体之间的合作。建立这种协作并实现所提出的反馈算法是第三个主要任务。

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.