Abstract: A method and system for providing a drowsiness alert to a driver of a vehicle are described. A drowsiness estimate data set is compared to historical drowsiness data from multiple vehicles. The drowsiness estimate data set includes current drive context data, and traffic situation data indicative of a present traffic situation for the vehicle and the position of the vehicle. The previously collected drowsiness estimate data sets of the historical drowsiness data are each associated with a determined degree of drowsiness of the respective driver when the previous drowsiness estimate data sets were collected. The degree of drowsiness is determined by a drowsiness detection system in the respective vehicle. A drowsiness risk measure is subsequently determined and, based on the drowsiness risk measure and based on a current drive context for the vehicle, a drowsiness alert may be provided to the driver.

Abstract: A method performed by a sign pertinence receiving system is disclosed for enabling a first vehicle to discard non-pertinent road sign information. The first vehicle is configured to present extracted sign information within the vehicle and/or adapt a vehicle function based on detected sign information. The system captures detected sign information from a road sign, and receives a most likely supplementary information estimate indicating supplementary information deemed to pertain to the road sign, which estimate is based on detected supplementary information captured by a second vehicle from supplementary sign information assigned to the road sign, wherein a correctness confidence value associated with the estimate exceeds a minimum correctness confidence threshold. The system determines whether the estimate pertains to the first vehicle, and refrains from presenting extracted sign information and/or from adapting a vehicle function, provided the estimate is determined to not pertain to the first vehicle.

Abstract: A method and system for providing a drowsiness alert to a driver of a vehicle are described. A drowsiness estimate data set is compared to historical drowsiness data from multiple vehicles. The drowsiness estimate data set includes current drive context data, and traffic situation data indicative of a present traffic situation for the vehicle and the position of the vehicle. The previously collected drowsiness estimate data sets of the historical drowsiness data are each associated with a determined degree of drowsiness of the respective driver when the previous drowsiness estimate data sets were collected. The degree of drowsiness is determined by a drowsiness detection system in the respective vehicle. A drowsiness risk measure is subsequently determined and, based on the drowsiness risk measure and based on a current drive context for the vehicle, a drowsiness alert may be provided to the driver.

Abstract: A method performed by a sign pertinence receiving system is disclosed for enabling a first vehicle to discard non-pertinent road sign information. The first vehicle is configured to present extracted sign information within the vehicle and/or adapt a vehicle function based on detected sign information. The system captures detected sign information from a road sign, and receives a most likely supplementary information estimate indicating supplementary information deemed to pertain to the road sign, which estimate is based on detected supplementary information captured by a second vehicle from supplementary sign information assigned to the road sign, wherein a correctness confidence value associated with the estimate exceeds a minimum correctness confidence threshold. The system determines whether the estimate pertains to the first vehicle, and refrains from presenting extracted sign information and/or from adapting a vehicle function, provided the estimate is determined to not pertain to the first vehicle.