A method for monitoring an electric steering device of a vehicle while the vehicle is driving, the method including generating a nominal movement direction signal that characterizes a current nominal movement direction of the vehicle and processing the nominal direction movement signal in at least one electronic control device; feeding surroundings data into the at least one electronic control device wherein the surroundings data is generated by a sensor device of the vehicle that scans surroundings of the vehicle touch free, wherein the surroundings data characterizes surroundings of the vehicle and is configured to be processed by a first driver assistance system, wherein the surroundings data facilitates detecting a current actual movement direction of the vehicle; generating an actual movement direction signal by the at least one electronic control device based on the surroundings data wherein the actual movement direction signal characterizes a current actual movement direction of the vehicle.

A sensor abnormality determination device of a four-wheel drive vehicle including a drive source, main drive wheels and sub-drive wheels, a power transmitting member, a first connecting/disconnecting device, a second connecting/disconnecting device, a first sensor, and a rotation sensor, the sensor abnormality determination device comprises a first sensor abnormality determining portion determining that the first sensor is abnormal when the rotation sensor detects the rotation of the power transmitting member and it is presumed that the four-wheel drive vehicle is in the four-wheel drive state, when the first sensor detects that the first connecting/disconnecting device is in the disconnecting state, and when the rotation sensor detects the rotation of the power transmitting member after the second connecting/disconnecting device is switched to the disconnecting state.

A computer-implemented method for safeguarding a system against false positives. The method includes: receiving a time series of a criticality, the system including a functionality that is triggered when the criticality meets a first predetermined criterion; computing a time series of a reference, the reference being a comparison criticality for a triggering of the functionality; computing a time series of an error measure at least based on the time series of the criticality and the time series of the reference, a triggering of the functionality being classified as a false positive when a portion of the time series of the error measure meets a second predetermined criterion; and identifying at least one near-false positive, a non-triggering of the functionality being classified as a near-false positive when a portion of the time series of the error measure meets a third predetermined criterion, but not the second predetermined criterion.

In various embodiments, methods and systems are provided for processing data pertaining to a vehicle event for a vehicle. In accordance with an exemplary embodiment, vehicle sensor data is obtained from one or more vehicle sensors pertaining to the vehicle event. Also in an exemplary embodiment, an assessment of the vehicle event is determined via a processor, including as to a fault or a severity, or both associated with the vehicle event, based on the vehicle sensor data.

In one embodiment, a method for monitoring a localization function in an autonomous driving vehicle (ADV) can use known static objects as ground truths to determine when the localization function encounter errors. The known static objects are marked on a high definition (HD) map for the real-time driving environment. When the ADV detects one or more known static objects, the ADV can use sensor data, locations of the one or more static objects, and one or more error tolerance parameters to create a localization error tolerance area surrounding a current location of the ADV. The ADV can project the tolerance area on the HD map, performs a localization operation to generate an expected location of the ADV on the HD map, and determines whether the generated location falls within the projected tolerance area. If the generated location falls outside the projected tolerance area, indicating a localization function of the ADV encounter errors, the ADV can generate an alarm to alert a human driver to switch to a manual driving mode. If no human driver is available in the ADV, the ADV can activate a vision-based fail-safe localization procedure.

A control unit for a vehicle is configured to detect a signalling installation ahead, wherein the signalling installation has at least one signal transmitter. The control unit is configured to ascertain digital map information indicating and/or allowing an association between the at least one signal transmitter and at least one possible direction of travel of the vehicle at the signalling installation. The control unit is further configured to operate a driving function of the vehicle on the basis of the digital map information.

An automatic processing system, a system on chip and a method for monitoring a processing module are described herein. The automatic driving processing system comprises: an automatic driving processing module, configured for receiving an input data stream and processing the input data stream based on a deep learning model so as to generate a processing result; a fault detection module, configured for generating a control signal and a fault detection stimulating data stream, and receiving the processing result from the automatic driving processing module; and a multi-way selection module, configured for receiving an automatic driving data stream as well as the control signal and the fault detection stimulating data stream, and selectively outputting the automatic driving data stream or the fault detection stimulating data stream to the automatic driving processing module based on the control signal, as an input data stream.

A backup control unit for controlling motion of a heavy-duty vehicle during a minimum risk maneuver, where the backup control unit is arranged to receive data indicative of a planned sequence of vehicle control commands from a main vehicle control unit. The backup control unit comprises a first vehicle model configured to map the planned sequence of vehicle control commands into a desired vehicle behavior and is arranged to obtain a measured vehicle behavior from one or more vehicle sensors. Also, the back-up control unit is arranged to determine an adjusted sequence of vehicle control commands based on the planned sequence of vehicle control commands and on a deviation between the desired vehicle behavior and the measured vehicle behavior, and to transmit the adjusted sequence of vehicle control commands to a motion support device, MSD, control unit of the vehicle.

A vehicle includes a power supplier, a junction block configured to supply power from the power supplier, an integrated central control unit configured to receive the power from the junction block, a controller configured to be receive the power through the integrated central control unit and to control at least one load unit of the vehicle, and a control unit configured to identify a power failure location of the vehicle and to determine a power supply method of the junction block during an autonomous driving of the vehicle, based on power monitoring information of each of the integrated central control unit, the junction block, and the controller and predetermined condition information, the predetermined condition information including power supply state information and power supply method information of each load unit corresponding to each of a plurality of pieces of power failure location information.

A method for improving the availability of an energy storage or transformation, EST, system of a vehicle. The method comprises providing an EST system model of coupled EST components of the EST system, identifying a fault or error in an EST condition parameter of the EST system, estimating an output value of the EST condition parameter based on the EST system model, identifying a vehicle situation which, in case of an at least temporary lack of operability of the EST system, belong to a predetermined group of vehicle situations defined as hazardous, and in response to identifying the vehicle situation belonging to the predetermined group of vehicle situations defined as hazardous, operating the EST system despite the fault or error in the EST condition parameter using the estimated output value of the EST condition parameter based on the EST system model.