- Author: Martin Krähling, Ibeo
- Contact details: firstname.lastname@example.org
The AdCoS Adapted Automation has been developed for highly automated driving on highways by Ibeo. Two subsystems provided by partners have been implemented in the vehicle to address human factors issues in vehicle automation. At first, a driving style classifier has been developed by DLR to estimate the preferred driving style of the individual human during periods of manual driving. The driving behaviour of the automation is then adapted in real-time to meet the preferences of the human driver and thus increase the acceptance and the trust in the automated system. Secondly, a cognitive distraction classifier has been developed by TWT, employing i.e. facial video data and behavioural data. This system detects the level of cognitive distraction of the driver, which can be used to trigger a warning system, or adapt the automation style to when the driver is not sufficiently attending the traffic situation.