CPS: Large: Center for Autonomous Transportation Systems

CPS：大型：自主交通系统中心

• 批准号: 1035813
• 负责人: Ragunathan Rajkumar
• 金额: $ 240万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1035813&HistoricalAwards=false
• 关键词: CPS; Large; Center; Autonomous; Transportation

The objective of this research is to study, develop and implement a comprehensive set of techniques that will eventually enable automobiles to be driven autonomously. The approach taken is to (a) address cyber-physical challenges of reliable, safe and timely operations inside the automobile, (b) tackle a range of physical conditions and uncertainties in the external environment, (c) enable real-time communications to and from the automobile to other vehicles and the infrastructure, and (d) study verification and validation technologies to ensure correct implementations.Intellectual Merits: The project seeks to make basic research contributions in the domains of safety-critical real-time fault-tolerant distributed cyber-physical platforms, end-to-end resource management, cooperative vehicular networks, cyber-physical system modeling and analysis tools, dynamic object detection/recognition, hybrid systems verification, safe dynamic behaviors under constantly changing operating conditions, and real-time perception and planning algorithms. Multiple intermediate capabilities in the form of active safety features will also be enabled. Broader Impacts: Automotive accidents result in about 40,000 fatalities and 3 million injuries every year in the USA. The global annual cost of road injuries is $518 billion. Many accidents are due to humans being distracted. Autonomous vehicles controlled by ever-vigilant cyber-physical systems can lead to significant declines in accidents, deaths and injuries. Autonomous vehicles can also offload driving chores from humans, and make time spent in automobiles more productive. Vehicular networks can help find the best possible routes to a destination in real-time. Broader impacts in this area are amplified by the project's partnerships with companies in the transportation and agricultural technology industries, and in information technology. Broader impacts are also sought through demonstrations and outreach to attract students into science and technology, and in particular to cyber-physical systems research.

这项研究的目的是研究、开发和实施一套全面的技术，最终使汽车能够自动驾驶。 所采取的方法是（a）解决汽车内部可靠、安全和及时运行的网络物理挑战，（B）解决外部环境中的一系列物理条件和不确定性，（c）实现汽车与其他车辆和基础设施之间的实时通信，以及（d）研究验证和确认技术，以确保正确实施。该项目旨在在安全关键的实时容错分布式网络物理平台，端到端资源管理，合作车辆网络，网络物理系统建模和分析工具，动态对象检测/识别，混合系统验证，不断变化的操作条件下的安全动态行为，以及实时感知和规划算法。 还将启用主动安全功能形式的多种中间功能。更广泛的影响：在美国，汽车事故每年导致约4万人死亡，300万人受伤。全球每年因道路伤害造成的损失为5 180亿美元。许多事故是由于人类分心。由时刻保持警惕的网络物理系统控制的自动驾驶汽车可以大幅减少事故、死亡和受伤。 自动驾驶汽车还可以减轻人类的驾驶负担，并使在汽车上花费的时间更有效率。 车载网络可以帮助实时找到到达目的地的最佳路线。 该项目与运输和农业技术行业以及信息技术领域的公司建立了伙伴关系，扩大了在这一领域的更广泛影响。 还通过示范和外联活动，吸引学生参与科学和技术，特别是网络物理系统研究，以扩大影响。