BMW

The present disclosure relates to a computer-implemented method, to a system and to a computer program for verifying tests to be used for test-driven development of at least one software component of a product, such as at least one software component of a vehicle. The method comprises obtaining (110) a natural language description of one or more requirements to be satisfied by the at least one software component, obtaining (120) a natural-language description or an executable code of one or more tests to be executed for verifying that the at least one software component satisfies the requirements, processing (130), using a large language model, LLM, the natural language description of the one or more requirements to be satisfied and the natural-language description or the executable code of the one or more tests to be executed, wherein the LLM is prompted to verify the one or more requirements to be satisfied and the one or more tests to be executed, and to provide an output based on the verification, and providing (140), via a user interface and based on the output of the large language model, information related to the verification.

The present invention relates to a method for training a machine learning model (200) having a transformer architecture (202), the method comprising: providing (S1) time series training data (203) to the machine learning model (200) as input data (204), the machine learning model (200) processing the time series training data (203) via at least one attention layer (206) of at least one encoder layer (208) of the transformer architecture (202); applying (S2) a dynamic region masking (210) of the time series training data (203) based on attention weights of the attention layer (206) to derive masked training data(212); providing (S3) the masked training data (212) to the machine learning model (200) as input data (204); performing (S4) semi-supervised contrastive learning (214) of a latent space representation (216) of the time series training data (203) and the masked training data (212) derived from the at least one encoder layer (208); and providing (S5) the thereby trained machine learning model (218) for performing a downstream task.

The present document describes a vehicle server (140) configured to manage a digital key (161) for controlling one or more vehicle functions (103) of a vehicle (100). The vehicle server (140) is configured to store target information regarding a target device (180) which is eligible to a shared digital key (181) of the digital key (161) for controlling the one or more vehicle functions (103) of the vehicle (100), and to receive a sharing request from a requesting device for a shared digital key (181) of the digital key (161). Furthermore, the vehicle server (140) is configured to verify, based on the stored target information, whether or not the requesting device is eligible to the shared digital key (181), and to cause a key sharing process for providing the shared digital key (181) on the requesting device to be performed in dependence of the verification on whether or not the requesting device is eligible to the shared digital key (181).

Die Erfindung betrifft ein Verfahren zum Ermitteln wenigstens eines Einflusswerts, welcher einen Einfluss einer Relativposition zwischen einem Fahrzeug und einer das Fahrzeug (1) nutzenden Person (P) auf ein aktuell in einer Lenkung (24) des Fahrzeugs (1) wirkendes Lenkmoment charakterisiert, bei welchem mittels einer elektronischen Recheneinrichtung (17) wenigstens ein Positionswert ermittelt wird, welcher eine mittels einer Sensoreinrichtung (25) erfasste und durch die Relativposition zwischen der das Fahrzeug (1) nutzenden Person (P) und dem Fahrzeug (1) beeinflusste Messgröße charakterisiert. In Abhängigkeit von dem Positionswert wird der Einflusswert ermittelt.

Embodiments relate to a method for improving an automatic opening of a flap of a vehicle. The method comprises obtaining a movement profile indicative of a trajectory of a user relative to the vehicle, determining, based on the movement profile, a duration between an entry of the user into a predefined area relative to the flap and a point of the trajectory and blocking or triggering, based on the duration, a machine-learning based classification of whether the movement profile indicates that the flap is to be opened.

Die Erfindung betrifft ein Verfahren zum Klassifizieren eines Fahrzustands eines Fahrzeugs (1), bei welchem mittels einer elektronischen Recheneinrichtung (17) ein Ist-Drehmomentwert (46) ermittelt wird, welcher ein aktuelles, in einer Lenkung (24) des Fahrzeugs (1) wirkendes Lenkmoment charakterisiert. Es wird ein Ist-Winkelwert ermittelt, welcher einen aktuellen Rollwinkel des Fahrzeugs (2) charakterisiert. Es wird ein Ist-Geschwindigkeitswert ermittelt, welcher eine aktuelle Fahrgeschwindigkeit des Fahrzeugs (2) charakterisiert und mit dem zugehörigen Ist-Winkelwert ein Ist-Wertepaar bildet. In Abhängigkeit von dem Ist-Wertepaar wird aus einem Referenz-Kennfeld (37), welches mehrere Referenz-Winkelwerte, mehrere Referenz-Geschwindigkeitswerte und mehrere Referenz-Drehmomentwerte umfasst und einem jeweiligen Referenz-Wertepaar, welches genau einen der Referenz-Winkelwerte und genau einen der Referenz-Geschwindigkeitswerte umfasst, genau einen der Referenz-Drehmomentwerte zuordnet, eines der Referenz-Wertepaare als zu dem Ist-Wertepaar gehörendes Wertepaar ausgewählt. Es wird der dem ausgewählten Referenz-Wertepaar zugeordnete Referenz-Drehmomentwert (50) ermittelt.

Embodiments relate to a method for improving an opening of a flap of a vehicle. The method comprises obtaining a movement profile indicative of a trajectory of a user relative to the vehicle, generating an adjusted movement profile by adjusting the trajectory based on dimensions of the vehicle, estimating, by a trained machine-learning model and based on the adjusted movement profile, whether the flap is to be opened and, if it is estimated by the trained machine-learning model that the flap is to be opened, triggering the opening of the flap.

The present document describes a key management server (141) configured to manage a digital key (161) for providing a digital key-based service for a vehicle (100). The key management server (141) is configured to receive a key generation request for generating a digital key (161). Furthermore, the key management server (141) is configured to generate the digital key (161) and metadata for the digital key (161), to cause the metadata to be signed using an issuer key, thereby providing an issuer signature, and to cause a key tracking receipt to be signed using a tracking key, thereby providing a tracking signature. Furthermore, the key tracking server (141) is configured to provide a key attestation (162) of the digital key (161) to the vehicle (100), wherein the key attestation (162) is indicative of the digital key (161), of the metadata, of the issuer signature and of the tracking signature.

The present disclosure relates to performing a bus-aligned maneuver by a driving automation system feature of a vehicle. The bus-aligned maneuver is aligned with an upcoming driving maneuver of a bus. The bus is detected in a vicinity of the vehicle at least based on automotive sensor data captured by one or more automotive sensors of the vehicle. Then, the upcoming driving maneuver of the detected bus is determined based on one or more of the automotive sensor data, bus data and/or map data, based on the upcoming driving maneuver of the detected bus, the bus-aligned maneuver is detected. Finally, the vehicle is caused to perform the bus-aligned maneuver.

The present document describes a key entity (160) comprising a storage area (166) for storing a shared digital key (161) for controlling one or more vehicle functions (103) of a vehicle (100). The key entity (160) is configured to store restriction data with regards to a usage restriction of the key entity (160) in the storage area (166) of the key entity (160), wherein the usage restriction defines a scope of vehicle functions (103) that the key entity (160) is designated for. Furthermore, the key entity (160) is configured to send the restriction data to a sharer device (110) which comprises a digital key (111) from which the shared digital key (161) of the key entity (160) is to be derived, and in reaction to receiving a transfer request from the sharer device (110), to generate the shared digital key (161) in accordance to a set of entitlements, which is indicated within the transfer request.