CPS: Synergy: Collaborative Research: Formal Design of Semi-Autonomous Cyberphysical Transportation Systems

CPS：协同：协作研究：半自主网络物理运输系统的形式设计

• 批准号: 1238600
• 负责人: Paul Green
• 金额: $ 35万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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: 2012-11-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1238600&HistoricalAwards=false
• 关键词: CPS; Synergy; Collaborative; Research; Formal

The goal of this research is to develop fundamental theory, efficient algorithms, and realisticexperiments for the analysis and design of safety-critical cyber-physical transportation systemswith human operators. The research focuses on preventing crashes between automobiles at roadintersections, since these account for about 40% of overall vehicle crashes. Specifically, the mainobjective of this work is to design provably safe driver-assist systems that understand driver?sintentions and provide warnings/overrides to prevent collisions. In order to pursue this goal,hybrid automata models for the driver-vehicles-intersection system, incorporating driverbehavior and performance as an integral part, are derived from human-factors experiments. Apartial order of these hybrid automata models is constructed, according to confidence levels onthe model parameters. The driver-assist design problem is then formulated as a set of partiallyordered hybrid differential games with imperfect information, in which games are orderedaccording to parameter confidence levels. The resulting designs are validated experimentally ina driving simulator and in large-scale computer simulations.This research leverages the potential of embedded control and communication technologies toprevent crashes at traffic intersections, by enabling networks of smart vehicles to cooperate witheach other, with the surrounding infrastructure, and with their drivers to make transportationsafer, more enjoyable, and more efficient. The work is based on a collaboration amongresearchers in formal methods, autonomous control, and human factors who are studying realistic andprovably correct warning/override algorithms that can be readily transitioned to productionvehicles.

本研究的目标是发展基础理论、高效算法和现实实验，以分析和设计具有人类操作员的安全关键网络物理运输系统。这项研究的重点是防止车辆在十字路口发生碰撞，因为这些事故约占车辆碰撞总数的40%。具体来说，这项工作的主要目标是设计可证明安全的驾驶员辅助系统，该系统可以理解驾驶员？发送意图并提供警告/覆盖以防止碰撞。为了实现这一目标，在人因实验的基础上，建立了以驾驶员行为和性能为一体的人车交叉口系统混合自动机模型。根据模型参数的置信度，构造了混合自动机模型的偏阶。然后将驾驶员辅助设计问题表述为一组具有不完全信息的部分有序混合微分对策，其中对策根据参数置信度进行排序。设计结果在驾驶模拟器和大型计算机模拟中得到了实验验证。这项研究利用嵌入式控制和通信技术的潜力，通过使智能车辆网络相互合作，与周围的基础设施合作，并与他们的司机合作，使交通更安全，更愉快，更高效，从而防止交通路口的碰撞。这项工作是基于正式方法、自主控制和人为因素研究人员之间的合作，他们正在研究现实的、可证明正确的警告/覆盖算法，这些算法可以很容易地过渡到生产车辆。