CPS: TTP Option: Synergy: Traffic Operating System for Smart Cities

CPS：TTP 选项：协同：智慧城市的交通操作系统

• 批准号: 1545116
• 负责人: Roberto Horowitz
• 金额: $ 109.99万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1545116&HistoricalAwards=false
• 关键词: CPS; TTP; Option; Synergy; Traffic

Each commuter in the United States lost on average $818 in 2015 due to congestion. More than 66% of congestion happens on city streets. The situation is steadily getting worse as the number of cars on roads increases and is expected to double by 2050. Solving the mobility problem by building new roads is not feasible. Instead, we need to use emerging technologies such as intelligent transportation systems; connected vehicles and autonomous vehicles; and new services, e.g. car sharing, ride on demand, last mile delivery services, to improve transportation efficiency on city streets. To that end, we are developing Traffic Operating System (TOS) that utilizes the existing computation, communication and automotive technologies and facilitates the deployment of new ones. TOS will increase the throughput of the urban transportation network; reduce intersection accidents by preventing red-light running and rear end collisions; and make traffic behavior more predictable, reliable and efficient. Regions that invest in a TOS could see a return on their investment in reduced transportation network and infrastructure costs, and in enhanced business and economic growth. This project will advance research in several areas of Technology for and Engineering of Cyber-Physical System (CPS). We will develop new design, analysis, and verification tools for TOS, which will embody the scientific principles of CPS, rely on extensive use of heterogeneous sensors, large-scale data collection and processing, and will actively control the dynamics of a transportation network. We will field-test traffic estimation and prediction models using sensor measurement and signal timing data from the cities of Pasadena, Sierra Madre and Arcadia in Southern California. Field test of the combined vehicle-level and traffic-flow-level control, using actual connected vehicles and vehicle-to-infrastructure (V2I) communication with a signalized intersection, will be conducted in the transition to practice (TTP) component of our project. The synergistic combination of research activities will yield novel scientific, technological and practical engineering implementation results in the design, state estimation, forecasting and control of CPS that involve transportation flows on networks. The investigators in this project plan to develop, simulate and test, through targeted vehicle and roadway infrastructure field test experiments, a traffic operating system that organizes existing computation, communication and automotive technologies to: (1) minimize congestion by increasing traffic throughput; (2) enhance safety by reducing driver errors through the use of cooperative adaptive cruise control (CACC) strategies that significantly increase arterial traffic throughput while preserving safety; and (3) contain the cost of parking by minimizing the number of idle vehicles and the number of vehicles searching for parking. These goals are achieved through integration of traffic measurements with the traffic management on vehicle, road link and network levels, making effective use of a dynamic traffic model and simulation. The project will demonstrate how three levels of traffic control are interconnected and we will develop new simulation and control design techniques that receive each other's output as feedback signals.

2015年，由于交通拥堵，美国每位通勤者平均损失818美元。超过66%的交通拥堵发生在城市街道上。随着道路上汽车数量的增加，情况正在稳步恶化，预计到2050年将翻一番。通过修建新建道路来解决流动性问题是不可行的。相反，我们需要使用新兴技术，如智能交通系统;联网汽车和自动驾驶汽车;以及新服务，如汽车共享，按需乘坐，最后一英里交付服务，以提高城市街道的交通效率。为此，我们正在开发交通操作系统（TOS），利用现有的计算，通信和汽车技术，并促进新技术的部署。TOS将增加城市交通网络的吞吐量;通过防止闯红灯和追尾事故来减少交叉路口事故;并使交通行为更加可预测，可靠和高效。投资于TOS的地区可以在降低交通网络和基础设施成本以及促进商业和经济增长方面看到投资回报。 该项目将推进信息物理系统（CPS）技术和工程的几个领域的研究。我们将为TOS开发新的设计、分析和验证工具，这些工具将体现CPS的科学原理，依赖于广泛使用异构传感器、大规模数据收集和处理，并将积极控制交通网络的动态。我们将使用来自南加州帕萨迪纳、马德雷山脉和阿卡迪亚等城市的传感器测量和信号定时数据，对交通估计和预测模型进行现场测试。结合车辆级和交通流量级控制的现场测试，使用实际连接的车辆和车辆到基础设施（V2 I）通信与信号交叉口，将在我们项目的过渡到实践（TTP）组件中进行。研究活动的协同组合将产生新的科学，技术和实际的工程实施结果的设计，状态估计，预测和控制CPS，涉及网络上的运输流。该项目的研究人员计划通过有针对性的车辆和道路基础设施现场测试实验，开发、模拟和测试一个交通操作系统，该系统将现有的计算、通信和汽车技术组织起来，以：（1）通过增加交通吞吐量来最大限度地减少拥堵;（2）通过使用协同自适应巡航控制（CACC）减少驾驶员错误，提高安全性在保证安全的同时显著增加主干道交通吞吐量的策略;以及（3）通过最小化空闲车辆的数量和搜索停车的车辆的数量来控制停车成本。这些目标是通过有效利用动态交通模型和仿真，将交通测量与车辆、道路连接和网络层面的交通管理相结合来实现的。 该项目将展示三个级别的交通控制是如何相互联系的，我们将开发新的模拟和控制设计技术，以接收彼此的输出作为反馈信号。