A method for operating a higher-level automated vehicle (HAV), in particular a highly automated vehicle, is provided, including: S1 for providing a digital map, which may be a highly accurate digital map, in a driver assistance system of the HAV; S2 for determining an instantaneous vehicle position and localizing the vehicle position in the digital map; S3 for providing an expected setpoint traffic density at the vehicle position; S4 for ascertaining an instantaneous actual traffic density in the surroundings of the HAV; S5 for comparing the actual traffic density to the setpoint traffic density and ascertaining a difference value as the result of the comparison; S6 for checking the vehicle position of the HAV for plausibility at least partially based on the difference value and/or S7 for updating the digital map at least partially based on the difference value. Also described are a corresponding driver assistance system and a computer program.

An automatic traveling vehicle includes a vehicle structure including a first top plate, and an electronic control unit. The electronic control unit is configured to execute a storage mode when a storage execution condition is satisfied. The storage mode includes a storage posture formation process of causing the vehicle to automatically travel so as to take a predetermined storage posture together with a counterpart automatic traveling vehicle. In the storage posture, the vehicle is in a superposition state in which the vehicle overlaps with the counterpart vehicle in a plan view, or a parallel state in which the vehicle is lined up with the counterpart vehicle while the first top plate and a second top plate of the counterpart vehicle are standing and facing each other so as to be parallel to or substantially parallel to a vertical direction.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

Methods, apparatus, and articles of manufacture to generate acquisition paths are disclosed. An example apparatus includes input interface circuitry to obtain input data associated with a vehicle, threshold calculation circuitry to calculate, based on the input data, a threshold curvature and a threshold curvature rate of the vehicle, and acquisition path generation circuitry to select a point on a target path of the vehicle, generate an acquisition path from a current position of the vehicle to the point, the acquisition path including at least two curves, and cause storage of the acquisition path in response to the at least two curves satisfying the threshold curvature and the threshold curvature rate.

A method using a system and a system having at least one autonomous vehicle, with the autonomous vehicle having at least one drive, at least one brake, and at least one steering, with the vehicle having a navigation system, with the navigation system having a first radio receiver for a global navigation satellite system and a second radio receiver for a global navigation satellite system, with the first radio receiver and the second radio receiver being arranged at a predefined spacing on the vehicle, with the navigation system having a control and evaluation unit to which the first radio receiver and the second radio receiver are connected, with the control and evaluation unit having two independent processor units, with the control and evaluation unit being configured to evaluate the position data of the first radio receiver and the position data of the second radio receiver using both processor units and to compare them with one another, and with the control and evaluation unit being configured to generate checked position data on a valid agreement of the position data.

A self-moving device, including: a moving module, a task execution module, a control module. The control module is electrically connected to the moving module and the task execution module, controls the moving module to actuate the self-moving device to move, controls the task execution module to execute a working task. The self-moving device further includes a satellite navigation apparatus, electrically connected to the control module and configured to receive a satellite signal and output current location information of the self-moving device. The control module determines whether quality of location information output by the satellite navigation apparatus at a current location satisfies a preset condition, controls, if the quality does not satisfy the preset condition, the moving module to actuate the self-moving device to change a moving manner, to enable quality of location information output by the satellite navigation apparatus at a location after the movement to satisfy the preset condition.

An in-vehicle system for generating precise, lane-level road map data includes a GPS receiver operative to acquire positional information associated with a track along a road path. An inertial sensor provides time local measurement of acceleration and turn rate along the track, and a camera acquires image data of the road path along the track. A processor is operative to receive the local measurement from the inertial sensor and image data from the camera over time in conjunction with multiple tracks along the road path, and improve the accuracy of the GPS receiver through curve fitting. One or all of the GPS receiver, inertial sensor and camera are disposed in a smartphone. The road map data may be uploaded to a central data repository for post processing when the vehicle passes through a WiFi cloud to generate the precise road map data, which may include data collected from multiple drivers.

The present invention provides specific systems, methods and algorithms based on artificial intelligence expert system technology for determination of preferred routes of travel for electric vehicles (EVs). The systems, methods and algorithms provide such route guidance for battery-operated EVs in-route to a desired destination, but lacking sufficient battery energy to reach the destination from the current location of the EV. The systems and methods of the present invention disclose use of one or more specifically programmed computer machines with artificial intelligence expert system battery energy management and navigation route control. Such specifically programmed computer machines may be located in the EV and/or cloud-based or remote computer/data processing systems for the determination of preferred routes of travel, including intermediate stops at designated battery charging or replenishing stations. Expert system algorithms operating on combinations of expert defined parameter subsets for route selection are disclosed. Specific fuzzy logic methods are also disclosed based on defined potential route parameters with fuzzy logic determination of crisp numerical values for multiple potential routes and comparison of those crisp numerical values for selection of a particular route. Application of the present invention systems and methods to autonomous or driver-less EVs is also disclosed.

A vehicle control system includes: a vehicle including an operation device; a first communication device; and a second communication device. In a case in which the first communication device is positioned in a first area containing a position of the vehicle, the vehicle operates in an operation waiting state in which the operation device is allowed to receive an operation. In a case in which the second communication device is positioned in a second area contained in the first area and smaller than the first area, the vehicle operates in the operation waiting state. In a case in which the first communication device is positioned in the first area and the second communication device is positioned in the second area, the second communication device generates a notification indicating that the vehicle is in the operation waiting state.

A method of creating a virtual boundary for a robotic garden tool includes receiving location coordinates of a location in which the robotic garden tool is intended to be operated. The method also includes retrieving, from a first server and based on the location coordinates, a preexisting visual media file of the location in which the robotic garden tool is intended to be operated. The preexisting visual media file includes metadata that includes coordinate information of the location shown in the preexisting visual media file. The method includes generating virtual boundary coordinates of the virtual boundary based at least partially on the preexisting visual media file and the coordinate information. The method includes controlling, with a first electronic processor of the robotic garden tool, the robotic garden tool to be confined by the virtual boundary to remain in an operating area during operation of the robotic garden tool.