CPS: Synergy: Collaborative Research: Multiple-Level Predictive Control of Mobile Cyber Physical Systems with Correlated Context

CPS：协同：协作研究：具有相关上下文的移动信息物理系统的多级预测控制

• 批准号: 1239483
• 负责人: John Stankovic
• 金额: $ 31.7万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1239483&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Multiple

Cyber physical systems (CPSs) are merging into major mobile systems of our society, such as public transportation, supply chains, and taxi networks. Past researchers have accumulated significant knowledge for designing cyber physical systems, such as for military surveillance, infrastructure protection, scientific exploration, and smart environments, but primarily in relatively stationary settings, i.e., where spatial and mobility diversity is limited. Differently, mobile CPSs interact with phenomena of interest at different locations and environments, and where the context information (e.g., network availability and connectivity) about these physical locations might not be available. This unique feature calls for new solutions to seamlessly integrate mobile computing with the physical world, including dynamic access to multiple wireless technologies. The required solutions are addressed by (i) creating a network control architecture based on novel predictive hierarchical control and that accounts for characteristics of wireless communication, (ii) developing formal network control models based on in-situ network system identification and cross-layer optimization, and (iii) designing and implementing a reference implementation on a small scale wireless and vehicular test-bed based on law enforcement vehicles. The results can improve all mobile transportation systems such as future taxi control and dispatch systems. In this application advantages are: (i) reducing time for drivers to find customers; (ii) reducing time for passengers to wait; (iii) avoiding and preventing traffic congestion; (iv) reducing gas consumption and operating cost; (v) improving driver and vehicle safety, and (vi) enforcing municipal regulation. Class modules developed on mobile computing and CPS will be used at the four participating Universities and then be made available via the Web.

网络物理系统（CPS）正在融入我们社会的主要移动系统，例如公共交通、供应链和出租车网络。过去的研究人员已经积累了设计网络物理系统的重要知识，例如军事监视、基础设施保护、科学探索和智能环境，但主要是在相对固定的环境中，即空间和移动多样性有限的环境中。 不同的是，移动 CPS 与不同位置和环境中的感兴趣现象进行交互，并且有关这些物理位置的上下文信息（例如，网络可用性和连接性）可能不可用。这一独特的功能需要新的解决方案将移动计算与物理世界无缝集成，包括动态访问多种无线技术。 所需的解决方案通过以下方式解决：（i）创建基于新型预测分层控制并考虑无线通信特性的网络控制架构，（ii）开发基于现场网络系统识别和跨层优化的正式网络控制模型，以及（iii）在基于执法车辆的小型无线和车载测试台上设计和实现参考实现。 研究结果可以改善所有移动交通系统，例如未来的出租车控制和调度系统。该应用的优点是：（i）减少司机寻找顾客的时间； (ii) 减少乘客等待的时间； (iii) 避免和防止交通拥堵； (iv) 减少燃气消耗和运营成本； (v) 提高驾驶员和车辆安全，以及 (vi) 加强市政监管。基于移动计算和 CPS 开发的课程模块将在四所参与大学使用，然后通过网络提供。