GOALI/Collaborative Research: Advanced Driver Assistance and Active Safety Systems through Driver's Controllability Augmentation and Adaptation

GOALI/合作研究：通过驾驶员可控性增强和适应实现高级驾驶员辅助和主动安全系统

• 批准号: 1234286
• 负责人: Panagiotis Tsiotras
• 金额: $ 22.56万
• 依托单位: Georgia Tech Research Corporation
• 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: 2012-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1234286&HistoricalAwards=false
• 关键词: GOALI; Collaborative; Research; Advanced; Driver

The research objective of this award is to investigate the next generation, proactive, driver-assist active safety control systems (ASCS) for commercial passenger vehicles. The main novel ingredient over existing methods is the adaptation of the ASCS specifications and operation to the individual driver habits and driving skills (e.g., aggressive or timid), his/her current cognitive state (e.g., attentive or not). By using recently developed techniques from the field of computational neuroscience and adaptive control theory, this research will develop algorithms that will capture the state of the driver, the vehicle and the environment from automotive sensors and behavioral (e.g., eye movement) measurements that will be subsequently used to adapt and customize the ASCS to particular situations so as to achieve maximum performance (e.g., minimum stopping distance during emergency braking, etc). This research will take advantage of recent advances in sensor technology, which has led to the reliable fusion of data, so as to provide situational awareness for the vehicle and the persistent monitoring of the (re)actions of the driver.If successful, this research will enable new levels of performance for the current active safety systems for passenger vehicles, thus leading to decreased accident rates, increased comfort and improved fuel economy. Graduate and undergraduate engineering students as well as local high school teachers will benefit from their involvement in this research through NSF's REU and RET projects and through Georgia Tech?s PURA and Dash undergraduate research fellowship programs. Undergraduate and high-school minority students will actively participate in data collection and analysis. Under-represented groups will be particularly targeted for participation in the research activities under this award, directly through active recruitment and indirectly through the collaboration with the industry partner, Ford Motor Company, e.g., in the form of summer internships.

该奖项的研究目标是调查商用乘用车的下一代，积极主动的，驾驶员主动的安全控制系统（ASC）。现有方法的主要新颖成分是将ASC的规格和操作适应单个驾驶员习惯和驾驶技能（例如，侵略性或胆怯），他/她当前的认知状态（例如，无论是专心与否）。通过使用来自计算神经科学和自适应控制理论领域的最近开发的技术，该研究将开发算法，这些算法将捕获驾驶员，车辆和环境的状态，来自汽车传感器和行为（例如，眼动）测量值随后用来适应和自定义ASC在特定情况下，以实现最大的性能（例如，紧急制动期间的最小停车距离等）。这项研究将利用传感器技术的最新进展，这导致了数据的可靠融合，从而为车辆提供情境意识，并持续对驾驶员的（重新）行动进行持续监控。将为当前的乘用车行动安全系统提供新的绩效水平，从而导致事故发生率降低，舒适性提高和燃油经济性提高。研究生和本科工程专业的学生以及当地的高中教师将通过NSF的REU和RET项目以及佐治亚理工学院的Pura和Dash本科研究奖学金计划而受益。本科和高中少数民族学生将积极参与数据收集和分析。代表性不足的团体将特别针对通过与行业合作伙伴福特汽车公司（例如以暑期实习的形式）合作，直接通过积极招聘和间接地参加该奖项的研究活动。