Method and apparatus are disclosed for mobile device tethering for a remote parking assist system of a vehicle. An example vehicle includes first and second wireless modules and a processor. The processor estimates a region of probability representative of possible locations of a mobile device based on a first signal strength indicator. When the region of probability overlaps a virtual boundary, the processor polls a key fob, estimates a distance of the key fob from the vehicle based on a second signal strength indicator, and when the key fob is within the virtual boundary, enable autonomous parking.

A vehicle integrated controller includes an in-vehicle communication module configured to communicate with at least one controller mounted on the vehicle; a collection module configured to collect collection information including controller information, which is information on the at least one controller, through the in-vehicle communication module; and an aging abnormality processor configured to calculate an aged state or an abnormal state of the at least one controller based on the collection information, and when there exists a controller (hereinafter, “control target controller”) in the aged state or abnormal state among the at least one controller, calculate a value of a control parameter for the control target controller to maintain basic performance.

A vehicle system includes an electronic control unit. The electronic control unit is configured to execute a first program, a second program, and a third program. The first program is configured to recognize an object present around a vehicle, the second program is configured to store information related to the recognized object as time-series map data, and the third program is configured to predict a future position of the object based on the stored time-series map data. The first program and the third program are configured to be (i) first, individually optimized based on first training data corresponding to output of the first program and second training data corresponding to output of the third program, and (ii) then, collectively optimized based on the second training data corresponding to the output of the third program.

A system for control of an automated device includes a control system configured to operate a device during an operating mode corresponding to a first state in which the control system automatically controls operation, the operating mode prescribing that a user monitor the device operation during automated control, and a scheduling module configured to, during the operating mode, receive a request for the user to temporarily stop monitoring in order to perform a task unrelated to the device operation, allocate a time period during which automated control is maintained and the user stops monitoring, the time period including a non-monitoring period having a duration based on a minimum amount of time for the task, and put the device into a temporary state at initiation of the allocated time period during which the user stops monitoring and automated control is maintained.

A controller as a control apparatus for a hybrid vehicle determines whether or not to perform switching from a first traveling mode in which a hybrid vehicle is caused to travel using torque of a motor without using torque of an engine to a second traveling mode in which the hybrid vehicle is caused to travel using at least the torque of the engine. The controller, when determining that switching is to be performed from the first traveling mode to the second traveling mode, performs control to reduce output torque of the motor by a predetermined amount. After this control, the controller shifts a first clutch from a released state to an engaged state so that the torque of the motor is transmitted to the engine via the first clutch, and cranks the engine using the motor to start the engine.

A computer-implemented method for controlling a vehicle. The method monitors one or more characteristics of one or more users within the vehicle, and compares the one or more characteristics of the one or more users with one or more corresponding baseline characteristics of the one or more users. The method further determines, based on the comparison, that a difference between the one or more characteristics and the one or more corresponding baseline characteristics of the one or more users exceeds a threshold value, and performs a controlling action associated with the vehicle, wherein the controlling action may be taking a higher level of autonomous control over the vehicle; varying speed and handling of the vehicle; and overriding the one or more characteristics of the one or more users in order to avoid an accident.

The present disclosure relates to a method of driving a motor vehicle. The method determines position data relating to at least one of a current position or a predicted future position of the motor vehicle detecting, using at least one sensor device, surroundings data relating to a surrounding environment of the motor vehicle, determining at least one driving intervention based on the surroundings data, and controlling at least one vehicle system of the motor vehicle to execute the determined at least one driving intervention. The at least one driving intervention executed by a selected software module that is selected based on the surroundings data, and the selected software module is selected from a plurality of software modules based on the position data. Each software module is configured to execute the at least one driving intervention.

A system for implementing an automobile electronic control function includes a plurality of automobile parts and an integrated unit VIU, and the VIU is configured to obtain control information of the plurality of automobile parts. The VIU is configured to control the plurality of automobile parts based on the control information. The plurality of automobile parts include automobile parts having only an execution function, and/or automobile parts having a part of an electronic control function and an execution function.

A system for implementing an automobile electronic control function includes a plurality of automobile parts and an integrated unit VIU, and the VIU is configured to obtain control information of the plurality of automobile parts. The VIU is configured to control the plurality of automobile parts based on the control information. The plurality of automobile parts include automobile parts having only an execution function, and/or automobile parts having a part of an electronic control function and an execution function.

A vehicle system includes an electronic control unit. The electronic control unit is configured to execute a first program, a second program, and a third program. The first program is configured to recognize an object present around a vehicle, the second program is configured to store information related to the recognized object as time-series map data, and the third program is configured to predict a future position of the object based on the stored time-series map data. The first program and the third program are configured to be (i) first, individually optimized based on first training data corresponding to output of the first program and second training data corresponding to output of the third program, and (ii) then, collectively optimized based on the second training data corresponding to the output of the third program.