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: 1235539
• 负责人: Laurent Itti
• 金额: $ 15万
• 依托单位: University of Southern California
• 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 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1235539&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研究商用乘用车的下一代主动式驾驶员辅助主动安全控制系统（ASCS）。与现有方法相比，主要的新颖成分是ASCS规范和操作适应于个体驾驶员习惯和驾驶技能（例如，好斗或胆怯），他/她当前的认知状态（例如，注意或不注意）。通过使用计算神经科学和自适应控制理论领域最近开发的技术，这项研究将开发算法，从汽车传感器和行为（例如，眼睛运动）测量，这些测量随后将用于使ASCS适应和定制特定情况以实现最大性能（例如，紧急制动时的最小停车距离等）。这项研究将利用传感器技术的最新进展，从而实现可靠的数据融合，从而为车辆提供态势感知和对驾驶员（反应）行为的持续监控。如果成功，这项研究将使当前乘用车主动安全系统的性能达到新的水平，从而降低事故率。提高舒适性和燃油经济性。研究生和本科工程专业的学生以及当地的高中教师将受益于他们通过NSF参与这项研究？的REU和RET项目，并通过格鲁吉亚技术？的PURA和Dash本科研究奖学金计划。本科和高中少数民族学生将积极参与数据收集和分析。代表性不足的群体将特别有针对性地参与本奖项下的研究活动，直接通过积极招募，间接通过与行业合作伙伴福特汽车公司的合作，例如，以暑期实习的形式。