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

该奖项的研究目标是研究用于商用乘用车的下一代、主动的、驾驶员辅助的主动安全控制系统(ASCS)。与现有方法相比，ASCS的主要创新成分是使ASCS的规范和操作适应于个体驾驶员的习惯和驾驶技能(例如，攻击性或胆小)，以及他/她当前的认知状态(例如，注意力是否集中)。通过使用计算神经科学和自适应控制理论领域最新开发的技术，这项研究将开发算法，从汽车传感器和行为(例如，眼动)测量中捕获驾驶员、车辆和环境的状态，随后将用于调整和定制ASC以适应特定情况，以实现最大性能(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，实现数据的可靠融合，从而为车辆提供态势感知，并持续监测驾驶员的(再)行动。如果成功，这项研究将使目前乘用车的主动安全系统达到新的性能水平，从而降低事故率，提高舒适性和燃油经济性。工程专业的研究生和本科生以及当地高中教师将通过国家科学基金会的REU和RET项目以及佐治亚理工学院、S、普拉和Dash本科生研究奖学金项目参与到这项研究中来。本科生和高中生将积极参与数据收集和分析。代表不足的群体将特别有针对性地参与该奖项下的研究活动，直接通过积极招聘，并通过与行业合作伙伴福特汽车公司的合作间接进行，例如以暑期实习的形式。

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.