CPS: Medium: Autonomous Driving in Mixed-Traffic Urban Environments

CPS：中：混合交通城市环境中的自动驾驶

• 批准号: 0931669
• 负责人: Umit Ozguner
• 金额: $ 149.99万
• 依托单位: Ohio State University Research Foundation -DO NOT USE
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0931669&HistoricalAwards=false
• 关键词: CPS; Medium; Autonomous; Driving; Mixed

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).The objective of this research is to scale up the capabilities of fully autonomous vehicles so that they are capable of operating in mixed-traffic urban environments. Such environments are realistic large-city driving situations involving many other vehicles, mostly human-driven. The approach is to integrate multidisciplinary advances in software, sensing and control, and modeling to address current weaknesses in autonomous vehicle design.With respect to intellectual merit, the research address significant improvements to current methods and tools to enable a number of formal methods to move from use in limited, controlled environments to use in more complex and realistic environments. The theory, tools, and design methods that are investigated have potential application for a broad class of cyber-physical systems consisting of mobile entities operating in a semi-structured environment.With respect to broader impacts, this research has the potential to lead to safer autonomous vehicles and to improve economic competitiveness, the nation's transportation infrastructure, and energy efficiency. The richness of the domain means that expected research contributions can apply not only to autonomous vehicles but, also, to a variety of related cyber-physical systems such as service robots in hospitals and rescue robots used after natural disasters. The experimental research laboratory for the project is used for undergraduate and graduate courses and supports new summer outreach projects for high-school students. Research outcomes are integrated with undergraduate and graduate courses on component-based software.

该奖项是根据2009年美国复苏和再投资法案(公法111-5)资助的。这项研究的目标是扩大全自动驾驶汽车的能力，使其能够在混合交通的城市环境中运行。这样的环境是现实的大城市驾驶情况，涉及许多其他车辆，主要是人驾驶的。该方法是整合软件、传感和控制以及建模方面的多学科进展，以解决目前自动驾驶汽车设计中的弱点。在智能价值方面，该研究致力于对现有方法和工具进行重大改进，使一些正式方法能够从在有限的受控环境中使用转向在更复杂和现实的环境中使用。所研究的理论、工具和设计方法对由运行在半结构化环境中的移动实体组成的广泛的网络物理系统具有潜在的应用。从更广泛的影响来看，这项研究有可能导致更安全的自动驾驶汽车，并提高经济竞争力、国家的交通基础设施和能源效率。该领域的丰富意味着，预期的研究贡献不仅适用于自动驾驶汽车，还适用于各种相关的网络物理系统，如医院的服务机器人和自然灾害后使用的救援机器人。该项目的实验研究实验室用于本科生和研究生课程，并支持新的高中生暑期外展项目。研究成果与基于组件的软件的本科生和研究生课程相结合。