An electronic control device is mounted on a vehicle having a sensor, and includes: a storage unit that stores a control history in which a vehicle control condition and an actual number of measurement times of the vehicle control condition are associated with each other, the vehicle control condition being a condition for performing an arbitrary vehicle control operation for each position; a position specifying unit that specifies a position of the vehicle; a determination unit that determines a current sensor capability that is a current capability of the sensor; and a selection unit that selects, from the storage unit, the vehicle control condition having the largest actual number among the vehicle control conditions that have a position within a predetermined distance from the position specified by the position specifying unit and that can be determined by the current sensor capability.

A cleaning device for a surface, such as a windshield of a vehicle, includes an active positioning system and a cleaning head. The active positioning system is configured to deploy from a storage position hidden from view within a covered storage space and to position the cleaning head upon the windshield. The active positioning system includes a first extension member and a second extension member that move relative to one another to position the cleaning head, and also move the cleaning head across the windshield along a path. The cleaning head can have a brush portion configured to agitate debris from the window, and a drying portion configured to dry the window after cleaning. The cleaning device can be controlled via a touch-screen display in the vehicle, enabling a user to direct that specific portions of the windshield be cleaned as desired.

This application discloses an intelligent vehicle control method. An intelligent vehicle control system obtains a driving mode, a driving style model, and a target speed of an intelligent vehicle at a current moment, then determines a speed control instruction based on the driving mode and the driving style model, and sends the speed control instruction to an execution system of the intelligent vehicle. This provides an intelligent vehicle control method with high comfort and good experience.

An agricultural vehicle includes: a chassis; at least one adjustable agricultural tool carried by the chassis and configured to function according to at least one operating parameter; and a controller operably coupled to the at least one adjustable agricultural tool. The controller is configured to: generate a user profile that includes at least one operating parameter setting corresponding to the at least one operating parameter; output the user profile to an external device; receive a modified user profile that includes at least one suggested parameter setting corresponding to at least one suggested operating parameter for at the least one adjustable agricultural tool; and cause adjustment of the at least one adjustable agricultural tool so the at least one adjustable agricultural tool functions according to the at least one suggested operating parameter.

A method and system for validating the calculated localization (15) of a vehicle are devised. The vehicle (1) is equipped with P independent localization data sources (2-8), with P higher than or equal to 2. The method and system involve the step of comparing data provided by each one of a subset of M, with M lower than or equal to P, of the independent localization data sources with the calculated localization, by correlating an independent localization data source among the subset M if it is above a predetermined Reliability Threshold, and the distance between the data it provides and the calculated localization is lower than a predetermined Compatibility Threshold, and disregarding an independent localization data source among the subset M if either it is below the predetermined Reliability Threshold, or the distance between the data it provides and the calculated localization is higher than the predetermined Compatibility Threshold, and the step of modifying the speed of the vehicle (1) depending on the number of correlated independent localization data sources among the subset M relative to a predetermined Voting Threshold.

A computer-implemented method for training a machine learning system to generate driving profiles of a vehicle. The method includes first travel routes are selected from a first database having travel routes, a generator of the machine learning system receives the first travel routes and generates first driving profiles for each of the first travel routes, travel routes and associated driving profiles determined during vehicle operation are stored in a second database, second travel routes and respective associated second driving profiles determined during vehicle operation are selected from the second database, a discriminator of the machine learning system receives pairs made up of one of the first travel routes with the respective associated first generated driving profile and pairs made up of second travel routes with the respective associated second driving profile determined during vehicle operation, as input variables.

A driving control system including a sensor unit, a data storage unit, a user communication means and a control unit. The sensor unit is arrangeable in a first vehicle and configured to generate at least one user-specific driving parameter of at least one user travelling with the first vehicle. The at least one user-specific driving parameter is based on a driver's driving behavior of the first vehicle. The user communication means is configured to receive an input of the user to store the at least one user-specific driving parameter in the data storage unit and activate the stored at least one user-specific driving parameter in a second vehicle to be occupied by the user. The control unit is configured to transmit the at least one user-specific driving parameter of the user from the data storage unit to the second vehicle.

An automatic driving device generates a control plan for autonomously driving a vehicle using map data. The automatic driving device determines an acquisition status of the map data. The automatic driving device generates the control plan using the map data. The automatic driving device changes the control plan according to the acquisition status of the map data.

A control system for a vehicle may include a plurality of vehicle subsystems associated with respective different dynamic vehicle control functions and a plurality of subsystem controllers associated with respective ones of the vehicle subsystems. The subsystem controllers may be configured to control actuators associated with the respective different dynamic vehicle control functions to change an operational state of components of the vehicle subsystems based on respective configuration settings. The system further includes an attribute configuration module operably coupled to the subsystem controllers. The attribute configuration module may include processing circuitry configured to save current configuration settings as a saved configuration responsive to a first actuation of a configuration mode actuator and, after an on/off cycle of the vehicle, instruct the subsystem controllers to implement the saved configuration responsive to a second actuation of the configuration mode actuator.

The present teaching relates to method, system, medium, and implementation of automatic motion planning for an autonomous driving vehicle. Information is obtained with respect to a current location of the autonomous driving vehicle operating in a current vehicle motion, wherein the information is to be used to estimate the operational capability of the autonomous driving vehicle with respect to the current location. Sensor data are obtained, via one or more sensors in one or more media types. A reaction of a passenger present in the vehicle with respect to a current vehicle motion is estimated based on the sensor data. Motion planning is performed based on the information with respect to the current location and the reaction of the passenger to the current vehicle motion.