Face recognition and vehicle's driver behavior

Abstract

This project is a part of a large EPSRC project supported by JLR. This research activity focusing on characterisation of human driver attention and cognition control when interacting with automated driving, and development of an optimal control authority shifting system considering driver cognition for applications to adaptive automated cars. The autonomous vehicle is one of the next generation trends in vehicle development. According to SAE International Standard J3016, Level 3 vehicle automation, or highly automated driving (HAD), presents an exciting new development in the field of driving research and technology. Although at present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in non-driving activities (NDAs), HAD may in the future allow drivers to more freely engage in NDAs during much of the time while the automated system monitors and reacts to the driving environment. HAD is not entirely autonomous and at some points during a journey (for example when approaching a complex or less predictable driving scenario, such as temporary road works) the driver will be required to disengage from their NDA and return to the driving task. This suggests a new form of driver interaction with the vehicle and poses new challenges in the science of driving, namely how to achieve a pleasurable driving experience that allows for engagement in NDAs. Therefore, the task of driver monitoring will change from monitoring the drivers’ inattention level while driving to monitoring the drivers’ attention level while engaged in a NDA. The measurement of attention level will play an important role in determining when a driver can be given control of the vehicle. Through this project, you will have an excellent opportunity to address a future challenge in autonomous vehicles using artificial intelligence techniques including computer vision,