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.

A method of moving an autonomous vehicle to a safe zone after an accident is provided. The method includes: setting a threshold which is a criterion for determining a failure of a chassis system; determining whether a failure occurs by using the threshold; determining a control mode of twin clutches or a braking system; designating avoidance speed level in accordance with whether a following vehicle approaches; and setting a target trajectory to a safe zone and then generating braking torque on left and right wheels or controlling distribution of driving torque through the twin clutches in order to move the autonomous vehicle at the avoidance speed along the target trajectory.

A vehicle control system executes automated driving control that controls automated driving of a vehicle based on driving environment information indicating a driving environment for the vehicle. When a part of functions of the vehicle is failed during the automated driving, the vehicle control system executes emergency stop control that stops the vehicle. In the emergency stop control, the vehicle control system: acquires failure status information being information on the failed part of functions; determines, based on the failure status information and the driving environment information, a target stop position at which even the vehicle with the failed part of functions is able to arrive and stop by the automated driving; and executes the automated driving control such that the vehicle travels toward the target stop position to stop at the target stop position.

A method includes an initial trailer health assessment and real-time trailer health monitoring. The initial trailer health assessment includes autonomous pre-trip maneuvers of the autonomous vehicle during a first time period, and detecting a pre-trip vehicle health condition. A vehicle health score is calculated based on the pre-trip vehicle health condition. If the vehicle health score is at least a threshold value, real-time trailer health monitoring is performed during a trip of the autonomous vehicle during a second time period, by actively monitoring vehicle dynamics data and/or image data associated with the autonomous vehicle, to determine a fault condition of the autonomous vehicle. If the fault condition meets a first criteria, a control parameter and/or a travel plan of the autonomous vehicle is adjusted. If the fault condition meets a second criteria different from the first criteria, a signal is sent to cause the autonomous vehicle to cease movement.

Disclosed embodiments relate to identifying Electronic Control Unit (ECU) anomalies in a vehicle. Operations may include monitoring, in the vehicle, data representing real-time processing activity of the ECU; accessing, in the vehicle, historical data relating to processing activity of the ECU, the historical data representing expected processing activity of the ECU; comparing, in the vehicle, the real-time processing activity data with the historical data, to identify at least one anomaly in the real-time processing activity of the ECU; and implementing a control action for the ECU when the at least one anomaly is identified.

This application relates to the field of automobile diagnosis technologies, and discloses a method and apparatus for remotely calibrating an advanced driver assistance system (ADAS), and a computer device. A diagnosis device may establish a remote connection to a client to directly remotely calibrate the ADAS of an automobile without the limitation of a distance. Therefore, a repair factory does not need to purchase diagnosis devices for all vehicle models. Instead, the diagnosis device can remotely calibrate the ADAS for the automobiles in the repair factory. In this way, the operation costs of the repair factory are greatly reduced. By means of the remote connection established between the client and the diagnosis device, the application of the diagnosis device is no longer limited to a specific area. Instead, the diagnosis device is applicable to any place where a remote connection can be established.

The in-vehicle control system in which a plurality of ECUs for controlling in-vehicle devices are connected to be able to communicate with each other is provided with an information set setting unit for setting an information set by combining information targeting different ECUs from among the original information relating to control functions of sound ECUs, an information collecting unit for collecting present information corresponding to the original information from each of the ECUs targeted by the information set, and an abnormality detection unit for detecting any one of the ECUs targeted to be abnormal when a degree of coincidence between correct answer information calculated by an evaluation function f with the information set as an argument and an evaluation value calculated by the evaluation function with the present information corresponding to the information set as an argument is lower than a criterion.

According to one aspect, an autonomous vehicle that includes a lidar unit collects lidar point cloud data that includes false returns or false positives, and characterizes the data associated with the false returns or false positives as drivable or not drivable. The false returns or false positives may be phantom points that are not associated with actual objects which may pose collision risks. Analyzing lidar point cloud data to characterize false returns or false positives as either drivable or not drivable enables an autonomous vehicle to operate efficiently by not having to avoid non-existent collision risks. False positives may be indicated when a wet or icy road surface acts as a mirror which reflects objects, and when precipitation such as raindrops appear as objects. Characterizing such false positives as drivable facilitates the efficient operation of an autonomous vehicle as the autonomous vehicle may drive over a mirror and/or through precipitation.

An automated parking movement path is generated such that a vehicle speed and a steering angle are set so as to enable a full steering axial force to be applied within a range of being less than a maximum driving force which depends on the temperature of a steering motor. Consequently, a load on the steering motor is suppressed, and thus a rise in the temperature of a steering motor is suppressed within the movement path from a movement starting position to a movement ending position.

An active noise control device includes a determination unit configured to determine whether an abnormality has occurred in an acceleration sensor based on a direct-current component of a reference signal acquired by the acceleration sensor attached to a vehicle, and a control unit configured to, when the determination unit determines that an abnormality has occurred in any of a plurality of the acceleration sensors, stop generation of the control signal based on the reference signal acquired by the acceleration sensor that has been determined to have the abnormality, and stop updating a filter coefficient of an adaptive filter configured to perform the filtering process on the reference signal acquired by the acceleration sensor that has been determined to have no abnormality.