TASCC: Driver-Cognition-Oriented Optimal Control Authority Shifting for Adaptive Automated Driving (CogShift)

自动驾驶的发展要求人类驾驶员和车辆控制员之间相互理解和协调，以避免需求的冲突和不匹配，从而实现理想的驾驶性能，平稳、快速的过渡，从而提高复杂操作场景下的驾驶安全性。然而，自动驾驶过程中的这种人车协作会影响驾驶员的注意力和认知，考虑这些影响是很重要的，以防止对驾驶的任何负面影响。该项目旨在实现自适应自动驾驶过程中驾驶员和车辆控制器之间的安全接触和平稳、快速的控制权转移。为此，我们将首先对驾驶员与车辆控制器交互时的注意力和认知控制特征进行全面的研究。然后，系统地开发和验证了考虑驾驶员认知的最优控制权转移系统。这一跨学科的研究挑战将使用来自工程学、认知神经科学和人类因素的研究人员的独特组合来解决。这项研究不仅将有助于自动驾驶领域的尖端技术创新，还将在与自动化交互时人类注意力和认知控制的科学方面取得重大进展。

The emerging development of automated driving demands a mutual understanding and a smooth coordination between human driver and vehicle controller, so as to avoid conflict and mismatch in demands, and instead achieve desirable driving performance, smooth and swift transitions which enhance driving safety during complex operating scenarios. However, such driver-vehicle collaboration during automated driving will impact on the driver's attention and cognition and it is important to consider these effects in order to prevent any negative impact on driving. This project aims to achieve a safe engagement and smooth and swift control-authority shift between the driver and the vehicle controller during adaptive automated driving. To this aim, we will first conduct a comprehensive study of driver attention and cognitive control characteristics when interacting with the vehicle controller. An optimal control authority shifting system which considers driver cognition will then be systematically developed and validated. This cross-disciplinary research challenge will be addressed using a unique combination of researchers from engineering, cognitive neuroscience and human factors. The research will not only contribute to the cutting-edge technology innovations in automated driving, but will also result in a major advance in the science of human attention and cognitive control when interacting with automation.