A device for determining driving warning information, comprising: - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with driving relevant data; wherein the driving relevant data comprises: a distance to a relevant road marker, a curvature of a relevant lane marker, and a driver identity, and the driving relevant data further comprises one or more of: a vehicle speed, a vehicle acceleration, a steering angle, a status of a turn indicator, an accelerator pedal position, a brake pedal position, a driver interaction with on board systems, and the driving relevant data further comprises; a time of day; a light condition; and a weather condition; wherein, the processing unit is configured to implement an artificial neural network to process the driving relevant data to generate driving awareness data; wherein the artificial neural network comprises a recurrent neural network configured with an internal cycle within the recurrent neural network, wherein a feedback connection is used to form the internal cycle, wherein output from the recurrent neural network is fed back into the recurrent neural network; and wherein the driving awareness data comprises one or more than one of: a likelihood that a lane departure on the left is not intended; a likelihood that a lane departure on the right is not intended; a level of driver attention; a level of driver fatigue, a likelihood that taking into account the driving relevant data the vehicle speed is too high; and wherein, the output unit is configured to output driving warning information based on the driving awareness data. - an input unit; - a processing unit; and - an output unit; wherein, the input unit is configured to provide the processing unit with driving relevant data; wherein the driving relevant data comprises: a distance to a relevant road marker, a curvature of a relevant lane marker, and a driver identity, and the driving relevant data further comprises one or more of: a vehicle speed, a vehicle acceleration, a steering angle, a status of a turn indicator, an accelerator pedal position, a brake pedal position, a driver interaction with on board systems, and the driving relevant data further comprises; a time of day; a light condition; and a weather condition; wherein, the processing unit is configured to implement an artificial neural network to process the driving relevant data to generate driving awareness data; wherein the artificial neural network comprises a recurrent neural network configured with an internal cycle within the recurrent neural network, wherein a feedback connection is used to form the internal cycle, wherein output from the recurrent neural network is fed back into the recurrent neural network; and wherein the driving awareness data comprises one or more than one of: a likelihood that a lane departure on the left is not intended; a likelihood that a lane departure on the right is not intended; a level of driver attention; a level of driver fatigue, a likelihood that taking into account the driving relevant data the vehicle speed is too high; and wherein, the output unit is configured to output driving warning information based on the driving awareness data. wherein, the input unit is configured to provide the processing unit with driving relevant data; wherein the driving relevant data comprises: a distance to a relevant road marker, a curvature of a relevant lane marker, and a driver identity, and the driving relevant data further comprises one or more of: a vehicle speed, a vehicle acceleration, a steering angle, a status of a turn indicator, an accelerator pedal position, a brake pedal position, a driver interaction with on board systems, and the driving relevant data further comprises; a time of day; a light condition; and a weather condition; wherein, the processing unit is configured to implement an artificial neural network to process the driving relevant data to generate driving awareness data; wherein the artificial neural network comprises a recurrent neural network configured with an internal cycle within the recurrent neural network, wherein a feedback connection is used to form the internal cycle, wherein output from the recurrent neural network is fed back into the recurrent neural network; and wherein the driving awareness data comprises one or more than one of: a likelihood that a lane departure on the left is not intended; a likelihood that a lane departure on the right is not intended; a level of driver attention; a level of driver fatigue, a likelihood that taking into account the driving relevant data the vehicle speed is too high; and wherein, the output unit is configured to output driving warning information based on the driving awareness data.