Abstract: A radar controller for a vehicle and a method therefore are provided. The radar controller includes a radar that detects a passenger located inside the vehicle and an obstacle located outside the vehicle and a controller that determines sensitivity and a detection speed corresponding to an operation mode of the radar and controls the radar to operate at the determined sensitivity and the determined detection speed.

Abstract: A predicting device includes: a recognizer configured to recognize a state of a moving body; a predictor configured to predict a position of the moving body in the future on the basis of the recognition result of the recognizer; and a processor configured to determine whether to set a first risk region or a second risk region larger than the first risk region for the moving body on the deviation between a position of the moving body which has been recognized by the recognizer and a position of the moving body in the future which has been predicted previously by the predictor.

Abstract: A method for enhancing movement or autonomy, including movement or flight of vehicles or flight vehicles in communication and or GPS degraded and or denied and or non-optimal environments is presented, where 3D area maps and or area maps may be employed, and 3D area maps and or area maps employed may include embedded position, location or GPS date, where the location or GPS data may be used in the present invention to determine vehicle location through image recognition, and using the GPS coordinates or location from the 3D area map of the image recognized, or measuring distance to other know aspects of a 3D area map in the real world, and context or system level information may also be used to estimate obstacle shapes and optimal routes in a potential route of travel or for understanding an area.

Abstract: A takeoff and landing facility management apparatus 4 transmits an information request for an unmanned aerial vehicle 1 to an unmanned aerial vehicle traffic management apparatus 3 in response to receiving a landing request from the unmanned aerial vehicle 1 that asks for an emergency landing. And then, the unmanned aerial vehicle traffic management apparatus 3 transmits at least position information of the unmanned aerial vehicle 1 to the takeoff and landing facility management apparatus 4 in response to the information request in a case where the unmanned aerial vehicle 1 that asks for the emergency landing is in an emergency state.

Abstract: A device and a method for controlling flight of an unmanned aerial vehicle are provided. To efficiently acquire environment information required to generate a navigation route of a vehicle, the device include a receiver that receives departure point information and destination information of a vehicle. A controller that generates a flight route corresponding to a travel route from a departure point to a destination of the vehicle based on at least one of a sensing range of a sensor mounted on the unmanned aerial vehicle, a flight available distance based on a fuel amount, and a communication available distance of a communication device mounted on the unmanned aerial vehicle, and operates the unmanned aerial vehicle to follow the generated flight route.

Abstract: A vehicle control method and system, including: receiving road friction information indicating road friction estimates for a plurality of regions surrounding the vehicle; detecting and determining a predicted trajectory for an object within the plurality of regions surrounding the vehicle; wherein the predicted trajectory for the object is determined based in part on the road friction estimates for the plurality of regions surrounding the vehicle; and modifying operation of the vehicle based on the predicted trajectory for the object. The predicted trajectory for the object is determined based in part on a risk map for the plurality of regions surrounding the vehicle that is generated from a road friction map for the plurality of regions surrounding the vehicle.

Abstract: In some embodiments, apparatuses and methods are provided herein useful to delivering merchandise using autonomous ground vehicles (AGVs) in cooperation with unmanned aerial vehicles (UAVs). In some embodiments, the system includes: an AGV having a motorized locomotion system, a storage area to hold merchandise, a sensor to detect obstacles, a transceiver, and a control circuit to operate the AGV; a UAV having a motorized flight system, a gripper mechanism to grab merchandise, a transceiver, an optical sensor to capture images; and a control circuit to operate the UAV. In some forms, the system may include a control circuit that instructs movement of the AGV along a delivery route; determines if the AGV has stopped due to an obstacle; and in certain circumstances, instructs the UAV to retrieve merchandise from the AGV, calculates a delivery route for the UAV to the delivery location, and instructs the UAV to deliver the merchandise.

Abstract: The present disclosure relates to a method for estimating a wheel base length (D) of at least one trailer (10) of a vehicle combination (100) comprising a towing vehicle (1), the at least one trailer and more than one articulation joint (A1, A2), wherein the towing vehicle comprises at least one wheel identification sensor (2) for identifying wheels (11, 12, 13) of the at least one trailer, the method comprising the following steps: —(S1) performing a plurality of wheel identification measurements on at least one side of the at least one trailer, by means of the at least one sensor during use of the vehicle combination, —(S2) determining a number of identifiable active wheels on the at least one side of the at least one trailer in each one of the plurality of wheel identification measurements, —(S3) determining a total number of active wheels on the at least one side of the at least one trailer, wherein the total number of active wheels is determined based on at least one of the plurality of wheel identificat

Abstract: Embodiments of the present systems and methods may provide techniques that provide dynamic groups and attribute-based access control (ABAC) model (referred as CV-ABACG) to secure communication, data exchange and resource access in smart vehicles ecosystems. In embodiments, the model not only considers system wide attributes-based security policies, but also takes into account individual user privacy preferences for allowing or denying service notifications, alerts, and operations to on-board resources. Embodiments of the present systems and methods may provide groups in vehicular IoT, which may be dynamically assigned to moving entities like connected cars, based on their current GPS coordinates, speed or other attributes, to ensure relevance of location and time sensitive notification services, to provide administrative benefits to manage large numbers of entities, and to enable attributes inheritance for fine-grained authorization policies.

Abstract: A non-transitory computer-readable medium and apparatus for restoring navigational performance for a navigational system. The apparatus including a receiver for receiving by a first navigational system and a second navigational system a collection of data points to establish a real-time navigational route for the aircraft, and a computer for comparing navigational performance values or drift ranges. The computer capable of establishing a new navigational route based on the collection of data points.

Abstract: Systems and methods are provided for providing recommendations of safe driving routes that are tailored to the driving habits of particular drivers. A machine learning model (e.g., an artificial neural network) may be trained using data indicative of insurance claim severity, road conditions, and/or vehicle telematics data associated with vehicle-related incidents, such as vehicle collisions. The machine learning model may be trained to identify road types and conditions that are predictive of claim frequency and severity. Any given driving route(s) may be provided to the trained machine learning model, and a risk value may be computed for the route(s). By further applying a personalized driver profile to the calculations of risk, personalized risk values may be computed for the route(s), and a safest route may be recommended to a driver.

Abstract: The present invention provides a computerized system for mapping an orchard, and a method for producing precise map and database with high resolution and accuracy of all trees in an orchard.

Abstract: The present disclosure relates to a method and a control unit for controlling pre-warming process of an engine of a Hybrid Electric Vehicle (HEV). The method comprises determining start-up time of the engine. The method also comprises determining engine heating time for the engine. The pre-warming process of the engine is initiated prior to start up time of the engine. The process of pre-warming is discontinued when the determined start-up time of the engine is greater than the engine heating time and the process is restarted when the determined start-up time of the engine is less than the engine heating time and when the pre-warming process of the engine is discontinued. The above-mentioned process is reiterated at plurality of time intervals for controlling the pre-warming process of the engine which results in energy efficiency and sufficient heat for warm-up of the engine.

Abstract: A computer is programmed to identify first and second virtual boundaries of a roadway lane based on a predicted boundary between the roadway lane and an adjacent roadway lane, determine a first constraint value based on a first virtual boundary approach acceleration, determine a second constraint value based on a second virtual boundary approach acceleration, output a prescribed steering angle, brake input, and propulsion input when one of the constraint values violates a respective threshold, and actuate components to attain the prescribed steering angle, brake input, and propulsion input. The first virtual boundary approach acceleration is based on a steering wheel angle of a vehicle and input to one of a brake or a propulsion of the vehicle. The second virtual boundary approach acceleration is based on a steering wheel angle of the vehicle and input to one of a brake or a propulsion of the vehicle.

Abstract: A vehicle information DB holds information on whether or not a vehicle falls under a welfare vehicle provided with an assistance apparatus for a driver who has a lower limb impairment. A power feed facility DB holds position information of a power feed facility and information indicating whether the power feed facility falls under a contact type power feed facility or a wireless power feed facility. A processing apparatus creates a travel route such that a larger number of wireless power feed facilities are included along the travel route when the vehicle falls under the welfare vehicle than when the vehicle does not fall under the welfare vehicle.

Abstract: An unmanned aerial vehicle, UAV is controlled based on communication via at least two mobile communication networks. Before takeoff, the UAV receives position data describing starting and destination points. A flight plan is set up from the starting point to the destination point by obtaining information about service coverage provided by the two mobile communication networks in a volume between the starting and destination points. A path to be followed by the UAV is calculated at least based on the obtained information. The path defines a restriction volume within which the UAV is allowed to fly from the starting point to the destination point. The path is calculated on the further basis of at least one switching criterion for changing from a communicative connection between the UAV and the first mobile communication network to a communicative connection between the UAV and the second mobile communication network.

Abstract: Systems and methods are provided for operating a vehicle using dynamic speed limits. A vehicle can monitor current road conditions by capturing real-time data that is indicative of a driving environment associated with a roadway being traversed by the vehicle. Using the captured real-time data, the vehicle can predict a dynamic speed limit, wherein the dynamic speed limit is a driving speed for the vehicle that is adapted for the monitored current road conditions. Additionally, the vehicle can automatically perform a driving operation for the vehicle in accordance with the dynamic speed limit, wherein the driving operation causes the vehicle to move at a driving speed that is approximately equal to the predicted dynamic speed limit.

Abstract: A flight management system is configured to manage the flight of a flight vehicle in communication with a user terminal operated by a user. The flight management system includes a receiver configured to receive from the user terminal the flight application information including the identification information of the flight vehicle, a flight path preferred by the user, and a flight time preferred by the user; a determination unit configured to determine whether or not to permit utilization of predetermined radio waves with the flight vehicle to fly along the flight path at the flight time based on the flight application information; and a transmitter configured to transmit the flight information instructing the flight vehicle to fly along the flight path to the flight vehicle identified by the identification information on the condition that the determination unit determines to permit utilization of predetermined radio waves.

Abstract: A method for calculating running resistance of a vehicle includes: calculating, by a controller, an integrated value obtained by integrating a torque of a driving source of the vehicle before the vehicle reaches a reference speed after the vehicle starts; and calculating, by the controller, the running resistance of the vehicle including rolling resistance based on the integrated value of the torque of the driving source.

Abstract: A method for generating an occlusion map using crowdsourcing includes receiving occlusion data from a host vehicle. The occlusion data includes a plurality of virtual detection lines each extending from the sensor and intersecting an off-road area. The method further includes marking all non-occluded points that are located inside the off-road area and that are located within a predetermined distance from each plurality of virtual detection lines. The method further includes determining a non-occluded region inside the off-road area using the non-occluded points that have been previously marked inside the off-road area, wherein the non-occluded region is part of non-occlusion data. The method further includes generating an occlusion map using the non-occlusion data. The method further includes transmitting the occlusion map to the host vehicle. The method can also determine an occlusion caused by an elevation peak.