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,