A vehicular arbitration system includes: a main manager configured to receive one or more requests from a plurality of first application execution units and to determine a request for operating a predetermined on-vehicle device based on the received one or more requests and a predetermined rule; and a plurality of sub-managers respectively configured to arbitrate the request determined by the main manager and a request input from at least one second application execution unit that is different from the plurality of first application execution units and to control the on-vehicle device based on an arbitration result.

A detection arrangement for detecting a wear status of a chopping knife arrangement of a chopping device provided for processing a product flow, wherein the chopping device has a revolving chopping drum receiving the chopping knife arrangement and at least one shear bar which cooperates with the chopping knives, with a sensor arrangement which has a magnetic exciter arrangement and a flux conducting device magnetically coupled thereto. The sensor arrangement provides a pole arrangement which forms at least one magnetic pole with a pole surface for conducting magnetic flux, wherein at least a portion of the chopping knife passes the pole arrangement during a rotation of the chopping drum. A voltage induced when a chopping knife arrangement passes the sensor arrangement forms the measured magnetic value, which is used by the evaluation unit to determine the state of wear of the chopping knife arrangement.

Disclosed herein are system, method, and computer program product embodiments for determining objects that are kinematically capable, even if non-compliant with rules-of-the-road, of affecting a trajectory of a vehicle. The computing system (e.g., perception system, etc.) of a vehicle may generate a trajectory for the vehicle and a respective trajectory for each object of a plurality of objects within a field of view (FOV) of the sensing device associated with the vehicle. The computing system may identify objects of the plurality of objects with trajectories that intersect the trajectory for the vehicle and remove from such objects, objects with trajectories that at least one of exit the FOV or intersect with other objects of the plurality of objects within the FOV. The computing system may select, from remaining objects with trajectories that intersect the trajectory for the vehicle, objects with trajectories that indicate a respective collision between the object and the vehicle and assign a severity of the respective collision.

Disclosed are a device and method for controlling a traveling characteristic of a vehicle. The device includes: a user terminal configured to configure and display a screen for a setting mode, on which a parameter value that determines drivability and traveling characteristic of the vehicle is displayed and from which a driver performs a change and a setting to the displayed parameter value; a controller configured to be provided in the vehicle, to receive a parameter value that results from the driver performing the change and the setting, from the user terminal, and to apply the received parameter value to control logic for controlling a traveling state of the vehicle; and a communication unit configured to be provided in the vehicle and to make a connection between the user terminal and the control unit in such a manner that transmission and reception of the parameter value are possible.

A method of maintaining stability of a motor vehicle having a first axle, a second axle, and a steering actuator configured to steer the first axle includes determining localization and heading of the vehicle. The method also includes determining a current side-slip angle of the second axle and setting a maximum side-slip angle of the second axle using the friction coefficient at the vehicle and road surface interface. The method additionally includes predicting when the maximum side-slip angle would be exceeded using the localization, heading, and determined current side-slip angle as inputs to a linear computational model. The method also includes updating the model using the prediction of when the maximum side-slip angle would be exceeded to determine impending instability of the vehicle. Furthermore, the method includes correcting for the impending instability using the updated model and the maximum side-slip angle via modifying a steering angle of the first axle.

Process for clearing an autonomous machine including first evaluating operation at a high curvature offline location. Following acceptable operation, the machine is placed into service and evaluated at a worksite. Following acceptable worksite operation, online operating speed of the machine is increased incrementally, and performance reevaluated. Following acceptable performance characteristics, online operating speed of the machine continues to be increased and revaluated until the machine reaches maximum designated operating speed, or is evaluated as unacceptable, in which case the machine continues to operate at the last acceptable online operating speed and identifies the unacceptable performance characteristic for further evaluation.

A passenger car that has a function of being able to partially or fully drive, not in accordance with driver's intentions, includes a grip that is provided independent of an operation system of the passenger car and is configured to receive driver's operating intentions according to operation of the driver, and a control unit that is configured to determine whether a driver's operating intention has been changed to another intention via the grip and to determine, when the operating intention has been changed, whether to give an operating initiative to the driver.

A method for controlling switching of steering control rights of an autonomous vehicle, may include: performing a control to synchronize a steering angle of a steering wheel and a steering angle of a road wheel, when switching of the steering control rights from an automated driving mode to a manual driving mode is requested. The method further includes: detecting an error value between the steering angle of the steering wheel and the steering angle of the road wheel, when a hands-on state in which the steering wheel is gripped is detected in the synchronization process. In addition, the method further includes: performing a control to switch the mode of the autonomous vehicle to the manual driving mode, when the error value is less than a preset value.

The invention relates to a control System (2) for a motor vehicle (1), comprising a central vehicle Controller (3) for Controlling vehicle functions (4) and a plurality of driver assistance Systems (5). The driver assistance Systems (5) are set up to transmit a task key describing the particular assistance function thereof to the vehicle Controller (3) and to transmit a security key assigned to the particular assistance function to the vehicle Controller (3). The central vehicle Controller (3) is set up to identify a particular task of the driver assistance Systems (5) on the basis of the transmitted task keys, to carry out a security check by virtue of the vehicle Controller (3) checking, on the basis of the security keys transmitted in each case for the respectively identified tasks, whether the particular security key complies with at least one security level assigned to the particular task, and, if the security check was successful, to control the vehicle functions (4) according to respective control commands transmitted by the driver assistance System (5) in Order to perform the respective assistance functions. The invention also comprises a method for operating such a control System (2) and a motor vehicle (1) having such a control System (2).

Techniques for generating simulations for evaluating a performance of a controller of an autonomous vehicle are described. A computing system may evaluate the performance of the controller to navigate the simulation and respond to actions of one or more objects (e.g., other vehicles, bicyclists, pedestrians, etc.) in a simulation. Actions of the objects in the simulation may be controlled by the computing system (e.g., by an artificial intelligence) and/or one or more users inputting object controls, such as via a user interface. The computing system may calculate performance metrics associated with the actions performed by the vehicle in the simulation as directed by the autonomous controller. The computing system may utilize the performance metrics to verify parameters of the autonomous controller (e.g., validate the autonomous controller) and/or to train the autonomous controller utilizing machine learning techniques to bias toward preferred actions.