A vehicle control device of an embodiment includes a detector that detects some or all of a degree of awakeness of a driver of a vehicle, an orientation of a face of the driver, and an orientation of a line of sight of the driver, and a driving controller that subjects the vehicle to a lane change by controlling at least one of a speed and steering of the vehicle, in which the driving controller changes a mode of the lane change on the basis of a detection result from the detector.

The driver monitoring device includes a processor configured to detect an opening/closing state of eyes of a driver of a vehicle based on a facial image in which a face of the driver is shown, judge whether the driver has fallen asleep based on the opening/closing state of the eyes, and judge whether the driver is talking. The processor is configured not to judge that the driver has fallen asleep while it is judged that the driver is talking.

The invention enables assessment and monitoring of attentiveness of a driver of a vehicle. The invention provides systems, methods and computer program products that determine a driver specific baseline degree of eye openness for a vehicle driver, and thereafter monitor and determine driver attentiveness or alertness based on the determined driver specific baseline degree of eye openness.

An information presenting apparatus is used in an autonomous vehicle capable of switching between autonomous driving control and manual driving control. The information presenting apparatus determines a response action for checking that the driver is ready to take over when the autonomous driving control is switched to the manual driving control, performs control for requesting the driver to perform the response action determined, and detects the response action performed by the driver.

The present disclosure relates to a method for determining the fatigue of a driver of a motor vehicle, wherein the fatigue is determined while taking into account the steering behavior of the driver, characterized in that the method includes the following steps: determination of a hysteresis of the steering system or the fatigue detection system, and taking into account the detected hysteresis in the determination of the fatigue of the driver. Furthermore, the disclosure relates to a device that is set up to execute the method.

A method for adapting a driving strategy of a transportation vehicle driving in at least semi-automated state, wherein the adapting takes place based on at least one occupant condition, captured by at least one sensor system, of an occupant, wherein a sleep phase is determined by the at least one sensor system during a sleeping condition of the occupant, wherein the driving strategy is adapted by a control device based on the determined sleep phase. An apparatus for adapting a driving strategy of a transportation vehicle driving in at least semi-automated state having at least one sensor system for capturing an occupant condition of an occupant, and a control device for adapting the driving strategy, wherein the at least one sensor system determines a sleep phase during a sleeping condition of the occupant, and wherein the control device adapts a driving strategy based on the determined sleep phase.

A closed eye determination device includes an eye opening degree detection unit that detects a degree of eye opening of a driver from each of a series of face images of a driver in time series in a latest certain period of time being acquired by a driver monitor camera, a local minimum value extraction unit that extracts a local minimum value of the degree of eye opening from a change in time series of the degree of eye opening in the certain period of time, a reference lower limit value-setting unit that sets, as a reference lower limit value of the degree of eye opening, a local minimum value in order corresponding to a blinking number of the driver in the certain period of time in order from the smallest local minimum value among local minimum values of the degree of eye opening in the certain period of time, a threshold value setting unit that sets a closed eye determination threshold value, based on the reference lower limit value, and a closed eye determination unit that determines that an eye of the driver is closed when the degree of eye opening detected from an image acquired by the driver monitor camera after the certain period of time is less than or equal to the closed eye determination threshold value.

A system, method, and computer program product for detecting, in real time, a fatigue level of a vehicle operator. Multiple physiological indicators of an individual vehicle operator can be monitored at different instances when the operator's level of fatigue is known and can be quantified. A statistical model of the vehicle operator's fatigue can be developed from the data from the multiple instances. In future instances, the statistical model can be applied to real-time physiological data collected from the operator during operation of the vehicle to determine a fatigue level. A warning can be provided when the statistically-calculated fatigue level exceeds a threshold level.

Interacting with the driver based on the driver's context can keep help keep the driver alert. The context can be determined determining driver characteristics including the interests and by monitoring the circumstances surrounding the driver, such as the state of the driver using sensors included in the vehicle, the state of the vehicle, and the information about the driver's current locale. The characteristics and the monitored circumstances define the context of driver. Information of interest to the driver is obtained and is used to generate actions that are recommendable to the driver based on the driver's context. The actions are used to keep the driver alert.

A vehicle that provides an advanced driver assistance system (ADAS) recommendation function and a method of controlling the vehicle are provided. The vehicle includes a collection unit that is configured to collect behavior information of a driver and a controller that is configured to determine an advanced driver assistance system (ADAS) mode recommendable to the driver based on the collected behavior information and to output the determined ADAS mode.