A method for operating a vehicle, in particular, a vehicle for highly automated driving. The method includes a step of reading in input data. The input data include sensor data and sensor state data of a multitude of sensor units of vehicle. The method also includes a step of generating a potential field, using the input data. The input data are used as attractive potentials and repulsive potentials of the potential field. The method furthermore includes a step of determining a trajectory through the potential field in order to generate a fusion signal, using the trajectory, for fusing the input data for a sensor data fusion for a highly automated driving operation of the vehicle.

Systems and methods are provided for generating a vehicle path to operate an autonomous vehicle. A method includes using a lateral re-entry planner system to correct for a lateral reentry error. A longitudinal re-entry planner system is used to correct a longitudinal reentry error. Path correction commands are generated based upon the corrections provided by the lateral re-entry planner system and the longitudinal re-entry planner system.

A method of providing surrounding information of a vehicle includes: detecting at least one sensor-based obstacle using sensor detection information acquired through a surroundings sensor, detecting at least one image-based obstacle using image information acquired through a plurality of cameras, detecting at least one matched obstacle from the at least one sensor-based obstacle or the at least one image-based obstacle, and correcting the position of the at least one matched obstacle using at least one of a sensor-based detection result or an image-based detection result with respect to the at least one matched obstacle.

The vehicle assistance system includes an infrastructure sensor installed in a predetermined place to detect an obstacle, an onboard apparatus connected to an onboard sensor which is mounted on the vehicle and which detects an obstacle, and a server installed in a place different from that of the infrastructure sensor. In the infrastructure sensor, the abnormality determination unit compares the first obstacle information related to the obstacle detected by the sensor unit and the second obstacle information related to the obstacle detected by the onboard sensor existing in a location different from that of the sensor unit, and determines whether or not the sensor unit or the onboard sensor is abnormal based on the result of this comparison.

An automotive sensor integration module including a plurality of sensors configured to detect an object outside a vehicle, and a signal processing unit configured to output, as sensing data, a plurality of pieces of detection data output from the plurality of sensors according to any one among the plurality of pieces of detection data at a substantially same timing based on a priority signal, or output, as the sensing data, the plurality of pieces detection data according to an external pulse at a substantially same timing.

Embodiments include methods performed by a processor of an Edge computing device for generating local dynamic map (LDM) data. The processor may receive new or updated (“first”) LDM data for a service area of the Edge computing device. The processor may integrate the first LDM data into an LDM data model. The processor may determine second LDM data of the LDM data model that is relevant to a vehicle or mobile device. The processor may provide the determined second LDM data to the vehicle or mobile device.

A method for ascertaining features in an environment of at least one mobile unit for implementation of a localization and/or mapping by a control unit. In the course of the method, sensor measurement data of the environment are received, the sensor measurement data received are transformed by an alignment algorithm into a cost function and a cost map is generated with the aid of the cost function, a convergence map is generated based on the alignment algorithm. At least one feature is extracted from the cost map and/or the convergence map and stored, the at least one feature being provided in order to optimize a localization and/or mapping. A control unit, a computer program, and a machine-readable storage medium are also described.

Systems and methods for collision imminent detection are provided. A method includes collecting sensor data generated by one or more sensors of a vehicle; detecting, by a fallback control system of the vehicle based on the sensor data, an imminent collision between the vehicle and an object in an environment of the vehicle using a first process different from a second process of a primary control system of the vehicle, wherein the first process and the second process are associated with at least one of a perception or a prediction; and transmitting, by the fallback control system to the primary control system, an indication of the detected imminent collision.

A method for vehicle motion control includes receiving sensor data from a plurality of sensors of a vehicle and monitoring a vehicle response of the vehicle using the sensor data. The vehicle response is represented by a plurality of vehicle-response signals. The method further includes fusing the plurality of vehicle-response signals to obtain at least one fused signal. The method further includes determining whether to activate a vehicle stability control of the vehicle based on the at least one fused signal and commanding the vehicle to activate the vehicle stability control in response to determining to activate the vehicle stability control of the vehicle based on the at least one fused signal.

Disclosed is a detection system and a detection method for detecting external environment information of a vehicle. The detection system includes at least two groups of vehicle-mounted modules (200) arranged on different vehicles, wherein each of the vehicle-mounted modules (200) includes: at least one sensor (201), configured to acquire distance information between the vehicle and a target; a processing unit (202), configured to establish a reference coordinate system by taking the vehicle as a center and perform calculation according to a detection direction of the sensor (201) and the distance information to obtain coordinates of the target in the reference coordinate system; a communication unit (203), configured to receive target positioning information of other vehicles transmitted by a communication unit (203) of at least one of other vehicle-mounted modules (200); and the processing unit (202) generates the external environment information of the vehicle in combination with target positioning information of the vehicle and the target positioning information of at least one of other vehicles. The system overcomes the limitation that a single vehicle independently acquires the external environment information, thereby accurately detecting the external environment information of the vehicle.