Abstract: A computer-implemented method for providing a digital road map for testing an at least partially automated vehicle system. the method includes: accessing a database in which are stored permissible characteristics of the road properties for a multitude of road properties; creating at least one road map section by one of the possible characteristics being selected for the road map section for the first of the multitude of road properties, in each particular case in automated fashion from the database; providing the digital road map, the digital road map including the at least one road map section.

Abstract: A computer-implemented method for detecting an obstacle on a route ahead of a first vehicle. In the method, information on a second vehicle driving ahead on the route is recorded in the first vehicle by at least one sensor of the first vehicle. In the first vehicle, depending on the recorded information, a computer detects an avoidance maneuver of the second vehicle due to an obstacle or detects that the second vehicle has driven over an obstacle. An obstacle is detected on the route depending on the detected avoidance maneuver or the detection that the vehicle has driven over an obstacle. A measure for protecting the vehicle and/or the obstacle is initiated depending on the detected obstacle.

Abstract: A method for controlling a vehicle. In the method, data of a digital road map are read in, zones are determined for the digital road map, and possible sequences of trips along a road of the digital road map are ascertained as a function of the determined zones. Furthermore, it is ascertained, as a function of sensor data and/or current driving data of the vehicle, whether a current or predicted traffic situation is outside the possible sequences or corresponds to a possible sequence that is determined as being outside an intended operating range. If the current or predicted traffic situation is outside the possible sequences or corresponds to the possible sequence outside the intended operating range, a measure is determined and the vehicle is controlled as a function of the measure that is taken.

Abstract: A computer-implemented method for controlling a vehicle. The method includes: data of a digital road map are read in, zones are determined for the digital road map, possible sequences of drives along a road of the digital road map are ascertained as a function of the determined zones, a behavior of the vehicle or of a vehicle system of the vehicle is ascertained in a simulation for at least one of the possible sequences, and the vehicle is controlled in accordance with one of the possible sequences as a function of a comparison of the ascertained behavior with at least one predetermined requirement.

Abstract: A computer-implemented method for testing a vehicle system. In the method, data of a digital road map are read in, zones are determined for the digital road map, possible sequences of drives along a road of the digital road map are ascertained as a function of the determined zones, a behavior of the vehicle or of a vehicle system of the vehicle is ascertained in a simulation for at least one of the possible sequences, and it is determined as a function of a comparison of the ascertained behavior with at least one predetermined requirement whether the vehicle system exhibits an error or a weakness.

Abstract: A computer-implemented method for providing a digital road map for testing an at least partially automated vehicle system. the method includes: accessing a database in which are stored permissible characteristics of the road properties for a multitude of road properties; creating at least one road map section by one of the possible characteristics being selected for the road map section for the first of the multitude of road properties, in each particular case in automated fashion from the database; providing the digital road map, the digital road map including the at least one road map section.

Abstract: An anticipatory monitoring and prediction system can include methods for generating effective, accurate predictions of other traffic objects in the vicinity of an ego-car. The invention proposes to combine approximate probability distributions (ADPs) of agent states with Attractor Functions (AFs) for generating distributed probabilistic representations of the potential future states of the observed traffic objects. AFs are selected based on both the current road context, in which the ego-car is situated, and the current states of all participating objects. The generated predictions can be used to filter incoming sensory information for better object state estimations, rate the nature of the behavior of other traffic objects by comparing generated predictions with actual perceived sensor information, or infer accident likelihoods by comparing the predicted state distributions of objects and the ego-car. Warning and information signals or control commands can be issued in a driving assistance system.

Abstract: A belt retractor for a safety belt has a brake surface (38), a blocking mechanism (18), a brake element (24) which can prevent a steering in of the blocking mechanism (18), and a magnetic actuator (28). The brake element (24) is pressed against the brake surface (38) by means of the magnetic actuator (28).

Abstract: A belt retractor for a safety belt has a brake surface (38), a blocking mechanism (18), a brake element (24) which can prevent a steering in of the blocking mechanism (18), and a magnetic actuator (28). The brake element (24) is pressed against the brake surface (38) by means of the magnetic actuator (28).