Abstract: A driver assistance method by a control device is to receive driving environmental data from identically constructed motor vehicle sensor technologies of a first motor vehicle, as well as from at least one further motor vehicle, which drive on a set road section in an at least partially autonomous driving mode. Each motor vehicle may provide a road section model for each of the motor vehicles with an algorithm recorded in each respective motor vehicle. The control device examines the road section models and/or the algorithms for a feasibility of the at least partially autonomous driving mode for the first motor vehicle, evaluates the algorithms of each motor vehicle based on a comparison of the road models, and sets that algorithm, which satisfies the set feasibility criterion with the highest probability, as the target algorithm.

Abstract: Disclosed is a parking assistance method for a drive with a motor vehicle. A parking assistance device determines a navigation destination of the drive of the motor vehicle, receives occupancy state data from at least one data source external to the motor vehicle of an availability of free parking spaces at the navigation destination and ascertains at least one location of a free parking space based on the received occupancy state data. The parking assistance device examines whether the navigation destination satisfies a preset criterion, including a minimum probability of a driver-specific favoring and/or frequency, and predetermines an information content for parking space data for the drive depending on whether the navigation destination satisfies the preset favoring criterion. The parking assistance device provides parking space data with the predetermined information content and transfers the provided parking space data to an output device.

Abstract: The application relates to a method for verifying characteristic features of a neural network, comprising obtaining the neural network as well as an identifier assigned to the neural network, determining the characteristic features of the neural network, calculating a first hash code using a predetermined hash function from the characteristic features of the neural network, obtaining a second hash code assigned to the identifier from a secure database, as well as verifying the neural network by comparing the first hash code to the second hash code. The application furthermore comprises a computer software product which can be downloaded to the internal memory of a digital computer and which comprises software code sections with which the steps according to the method described here are carried out when the software is executed on a computer.