The present invention relates to a method for providing a route stipulation for a route system of a vehicle, comprising the following steps: providing a plurality of detected trajectories of further vehicles in a route section to be used, ascertaining a trajectory stipulation from the detected trajectories, ascertaining a deviation zone from the detected trajectories, wherein the deviation zone is determined on the basis of a deviation of at least individual detected trajectories from the trajectory stipulation, determining the route stipulation at least on the basis of the trajectory stipulation and the deviation zone.

The present invention relates to a method for providing a route stipulation for a route system of a vehicle, comprising the following steps: providing a plurality of detected trajectories of further vehicles in a route section to be used, ascertaining a trajectory stipulation from the detected trajectories, ascertaining a deviation zone from the detected trajectories, wherein the deviation zone is determined on the basis of a deviation of at least individual detected trajectories from the trajectory stipulation, determining the route stipulation at least on the basis of the trajectory stipulation and the deviation zone.

An in-vehicle communication system includes a first relay apparatus installed in a first area of a vehicle, and a second relay apparatus installed in a second area and are connected via a communication main line. A main control apparatus and an auxiliary control apparatus are connected to the first relay apparatus and a controlled apparatus is connected to the second relay apparatus, each connected via a communication branch line. The first input apparatus is installed in the first area and inputs information to the main control apparatus and the auxiliary control apparatus. The second input apparatus is installed in the second area and inputs information to the main control apparatus and the auxiliary control apparatus via the first relay apparatus and the second relay apparatus. The first relay apparatus and the controlled apparatus communicate via an auxiliary communication line provided into both the first area and the second area.

A method for controlling a vehicle, an electronic device, a storage medium, and a vehicle are provided, related to a field of artificial intelligence technology, in particular to a field of autonomous driving and a field of computer vision. The method for controlling a vehicle includes: determining, in response to a request of switching to an autonomous driving mode, whether the vehicle is in a safe state; and controlling, in response to the vehicle being in the safe state, the vehicle to switch from a manual driving mode to the autonomous driving mode during travelling.

A method for predicting a future action of an object for a driving assistance system for a highly automated mobile vehicle. At least one sensor signal from at least one vehicle sensor of the vehicle is read in, the sensor signal representing at least one piece of kinematic object information concerning the object that is detected by the vehicle sensor at an instantaneous point in time. A planner signal from a planner of the autonomous driving assistance system is read in, the planner signal representing at least one piece of semantic information concerning the object or the surroundings of the object at a point in time in the past. The kinematic object information is fused with the semantic information to obtain a fusion signal. A prediction signal is determined using the fusion signal, the prediction signal representing the future action of the object.

In various embodiments, methods, systems, and vehicles are provided for executing a lane change for a host vehicle. In various embodiments, a method includes: receiving, by a processor, an indication that a lane change from an initial lane to an intended lane is desired for the host vehicle; defining, by the processor, an initial lane center target, a negotiation target, and an intended lane center target based on the desired lane change; and controlling, by the processor, the host vehicle to at least one of the initial lane center target, the negotiation target, and the intended lane center target based on a finite state machine, wherein the initial lane center target is at or in proximity to a determined center of the initial lane, wherein the intended lane center target is at or in proximity to a determined center of the intended lane, and wherein the negotiation target is offset from the initial lane center target and within the initial lane.

A technique for providing a user-adapted service to a user of a client device is disclosed. A method implementation of the technique is performed by the client device and comprises obtaining (902), via a manual input by the user, a digital representation of personality data of the user, and processing (S904) the digital representation of the personality data to provide a user-adapted service to the user. The client device may be a vehicle and providing the user-adapted service to the user may comprise adapting a driving configuration of the vehicle to a personality of the user.

A transport facilitation system can receive a pick-up request from a computing device of a user of a transportation arrangement service, the pick-up request comprising a unique identifier and a pick-up location. Using the unique identifier, the system can perform a lookup in a database for a profile indicating vehicle setup preferences for the user, and select a service vehicle to service the pick-up request. The system can further determine a seat assignment within the service vehicle for the user, and based on the vehicle setup preferences indicated in the profile, the system transmit a set of configuration instructions to the service vehicle, the set of configuration instructions to configure one or more adjustable components of the service vehicle for the user.

A computer generates an accident risk definition model to estimate a probability of hazard occurrence as an accident risk by inputting first in-vehicle sensor data collected in the past and hazard occurrence data having information on hazard occurrence from the first in-vehicle sensor data preset therein, generates accident risk estimation data by inputting second in-vehicle sensor data collected in the past to the accident risk definition model and estimating the probability of the hazard occurrence, generates an accident risk prediction model to predict the accident risk after a predetermined time by inputting first biological index data corresponding to the second in-vehicle sensor data and the accident risk estimation data, calculates second biological index data from second biological sensor data by acquiring the second biological sensor data of a driver, and predicts the accident risk after the predetermined time by inputting second biological index data to the accident risk prediction model.

A method of multi-sensor data fusion includes determining a plurality of first data sets using a plurality of sensors, each of the first data sets being associated with a respective one of a plurality of sensor coordinate systems, and each of the sensor coordinate systems being defined in dependence of a respective one of a plurality of mounting positions for the sensors; transforming the first data sets into a plurality of second data sets using a transformation rule, each of the second data sets being associated with a unified coordinate system, the unified coordinate system being defined in dependence of at least one predetermined reference point; and determining at least one fused data set by fusing the second data sets.