CPS: TTP Option: Synergy: Collaborative Research: Dynamic Methods of Traffic Control that Impact Quality of Life in Smart Cities

在最近的过去，“智能城市”一词被引入，主要是为了描述最新的技术和信息进步融入我们的日常生活。尽管智慧城市没有标准化的定义，但可以肯定的是，它涉及到许多不同的领域，影响着城市的物质资本和社会资本。智能城市与交通控制系统交织在一起，这些系统使用先进的基础设施来缓解拥堵并提高安全性。交通控制管理策略主要集中在改善高速公路和高速公路上的车辆流量，但主干道没有得到适当的使用，行人大多被忽视。本文提出将一种新的分层自适应控制范式引入到城市网络交通控制中，以适应来自多个实体(车辆、公共交通工具、自行车骑行者和行人)不断变化的运动和交互行为。这样的范例将利用网络物理系统的几个关键思想来快速和自动地定位和响应城市主干道拥堵，从而改善所有模式的出行时间和可靠性。安全性也将得到改善，因为拟议的网络物理系统发出的高级警告将提醒司机注意拥堵区域，从而使他们能够避开这些区域，或调整自己的驾驶习惯。这些发现对旅行公众的幸福感、生产力和健康产生了切实的影响。主要目标是创建一个网络控制网络(CCN)，该网络将无缝地集成各种不同的感官数据，以便创建有效的控制方案和执行序列。因此，该项目引入了一个网络物理体系结构，它将集成：(I)由不同类型传感器组成的子网络，(Ii)决策控制基板，以及(Iii)执行控制基板决策的子驱动网络(交通控制信号、可变信息标志)。这与更流行的集中式监控和数据采集(SCADA)有很大不同，因为CCN将使用分层架构，动态实例化各个子网络，以快速响应不断变化的网络-物理交互。这种方法允许网络物理系统实时适应在不同时间和空间尺度上发生的显著交通事件。因此，该工作将引入一个控制模块来实现这种动态子网络重构，并向执行网络提供决策信号输出。第二个互补的目标是开发一个不同种类的传感器网络，以可靠和准确地监测和识别显著的交通事件。该项目的其他影响包括将活动与从业人员(例如交通工程师)相结合、年度讲习班/教程以及与K-12机构的接触。

In the recent past the term "Smart Cities" was introduced to mainly characterize the integration into our daily lives of the latest advancements in technology and information. Although there is no standardized definition of Smart Cities, what is certain is that it touches upon many different domains that affect a city's physical and social capital. Smart cities are intertwined with traffic control systems that use advanced infrastructures to mitigate congestion and improve safety. Traffic control management strategies have been largely focused on improving vehicular traffic flows on highways and freeways but arterials have not been used properly and pedestrians are mostly ignored. This work proposes to introduce a novel hierarchical adaptive controls paradigm to urban network traffic control that will adapt to changing movement and interaction behaviors from multiple entities (vehicles, public transport modes, bicyclists, and pedestrians). Such a paradigm will leverage several key ideas of cyber-physical systems to rapidly and automatically pin-point and respond to urban arterial congestion thereby improving travel time and reliability for all modes. Safety will also be improved since advanced warnings actuated by the proposed cyber-physical system will alert drivers to congested areas thereby allowing them to avoid these areas, or to adapt their driving habits. Such findings have a tangible effect on the well-being, productivity, and health of the traveling public.The primary goal is to create a Cyber-Control Network (CCN) that will integrate seamlessly across heterogeneous sensory data in order to create effective control schemes and actuation sequences. Accordingly, this project introduces a Cyber-Physical architecture that will then integrate: (i) a sub-network of heterogeneous sensors, (ii) a decision control substrate, and (iii) a sub-actuation network that carries out the decisions of the control substrate (traffic control signals, changeable message signs). This is a major departure from more prevalent centralized Supervisory Control And Data Acquisition (SCADA), in that the CCN will use a hierarchical architecture that will dynamically instantiate the sub-networks together to respond rapidly to changing cyber-physical interactions. Such an approach allows the cyber-physical system to adapt in real-time to salient traffic events occurring at different scales of time and space. The work will consequently introduce a ControlWare module to realize such dynamic sub-network reconfiguration and provide decision signal outputs to the actuation network. A secondary, complementary goal is to develop a heterogeneous sensor network to reliably and accurately monitor and identify salient arterial traffic events. Other impacts of the project include the integration of the activities with practitioners (e.g., traffic engineers), annual workshops/tutorials, and outreach to K-12 institutions.