Abstract: A device for setting a target vehicle that sets a target vehicle to be subjected to driving assistance control of a host vehicle includes: a detection signal acquisition device capable of acquiring a first detection signal representing an object by an image, and a second detection signal representing the object by a reflection point; and setting control unit, which determines whether to set a forward object as a target vehicle, wherein if a movement history is not associated with the forward object, and a combination history is associated with the forward object, then as a selection threshold of a first determination parameter for determining whether to set the forward object as the target vehicle, a selection threshold is used such that the forward object is less likely to be selected as the target vehicle than with the selection threshold which would be used if a movement history is associated with the forward object.

Abstract: Systems, methods, devices and computer-readable storage mediums are disclosed for correcting a compass view using map data. In an implementation, a method comprises: receiving, by one or more sensors of a mobile device, sensor data; determining, by a processor of the mobile device, compass offset data for a compass view based on the sensor data and map data; determining, by the processor, a corrected compass view based on the compass offset data; and presenting, by the processor, the corrected compass view.

Abstract: Methods and associated systems and apparatus for generating a three-dimensional (3D) flight path for a moveable platform such as an unmanned aerial vehicle (UAV) are disclosed herein. The method includes receiving a set of 3D information associated with a virtual reality environment and receiving a plurality of virtual locations in the virtual reality environment. For individual virtual locations, the system receives a corresponding action item. The system then generates a 3D path based on at least one of the set of 3D information, the plurality of virtual locations, and the plurality of action items. The system then generates a set of images associated with the 3D path and then visually presents the same to an operator via a virtual reality device. The system enables the operator to adjust the 3D path via the virtual reality device.

Abstract: A distributed centralized automatic driving method comprises a sensor processing module, a perception positioning module, a perception target detection module, a decision-making module, a planning module, and a vehicle control module. By clearly defining data domains and a control process, a modular design is performed to implement each functional method, and each module can be deployed to a control unit of the corresponding data domain according to the load of a computing platform. The distributed centralized automatic driving method has different computing requirements for different scenarios. By means of a distributed design, centralized computing is distributed to different computing unit modules, so as to greatly improve the stability, efficiency and parallelism of the method, thereby improving the overall performance of the method.

Abstract: A method for determining a risk of instability of a calculation of an angle ? of a steering shaft of a motor vehicle can be employed where a first gear wheel is fixed to the steering shaft and cooperates with a second gear wheel and a third gear wheel, which are smaller than the first gear wheel. The number of teeth of the first gear wheel is n. The number of teeth of the second gear wheel is m. And the number of teeth of the third gear wheel is m+1. The angles ? and ? of the two smaller gear wheels are determined and the angular position ? of the steering shaft is calculated by evaluating the equation ? = m * ? + ( m + 1 ) * ? - ( 2 ? m + 1 ) * k * ? 2 ? n , with ? being an angle of the sensor range and a whole number k given by k = round ? ( ( m + 1 ) * ? - m * ? ? ) , wherein the risk of instability is determined by calculation of a stability margin t according to t = k - ( ( m + 1 ) * ? - m * ? ? ) .

Abstract: Provided are methods for operating a vehicle, which can include receiving, from one or more of at least one sensor placed within a vehicle or an application on a communication device connected to the vehicle, data indicative of at least one of an action or an appearance of a passenger of the vehicle; determining, based on the at least one of the action or the appearance, that a modification of at least one operational parameter of the vehicle is required; and modifying, in response to the determining, the at least one operational parameter of the vehicle. Systems and computer program products are also provided.

Abstract: Modifying settings of autonomous vehicle sensors based on predicted environmental states, including: determining, based on sensor data, that a predicted environmental state of the autonomous vehicle is associated with a sensory input outside an operating range of a sensor; determining a modified operating range of the sensor; and modifying one or more sensors to operate according to the modified operating range.

Abstract: A vehicle control method includes recognizing a vicinity of a vehicle, setting a risk index for a traffic participant, and controlling a vehicle-mounted instrument of the vehicle based on the risk index which is set by the setter, and setting a risk index for a position at which the traffic participant will be present in the future based on ease of entry of the traffic participant from a sidewalk to a roadway adjacent to the sidewalk in a region that the traffic participant traveling on the sidewalk will enter in the future, and increasing a risk index to be set on the roadway side as there is a greater tendency for the traffic participant to enter the roadway.

Abstract: A method for door or tailgate operation in a transportation vehicle, wherein the transportation vehicle is equipped with an access control device with which determines whether the operating person is present with an authentication element within a proximity area around the transportation vehicle. The device is equipped with at least one communication module for wireless communication with the authentication element, wherein access authorization information is transmitted from the authentication element to the device, the information being checked in the device, and wherein access is granted to the device following verification of the access authorization. It is determined whether the operating person is located in the immediate vicinity of the door or tailgate to be operated, and whether the operating person performs an operating movement in the immediate vicinity for the door or tailgate operation.

Abstract: Left turns are known to be one of the most dangerous driving maneuvers. An effective way to mitigate this safety risk is to install a left-turn enforcement—for example, a protected left-turn signal or all-way stop signs—at every turn that preserves a traffic phase exclusively for left turns. Although this protection scheme can significantly increase the driving safety, information on whether or not a road segment (e.g., intersection) has such a setting is not yet available to the public and navigation systems. This disclosure presents a system that exploits mobile crowdsensing and deep learning to classify the protection settings of left turns.

Abstract: Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle visual line of sight flight operations. A UAV computer system may be configured to ensure the UAV is operating in visual line of sight of one or more ground operators. The UAV may confirm that it has a visual line of sight with the one or more user devices, such as a ground control station, or the UAV may ensure that the UAV does not fly behind or below a structure such that the ground operator would not be able to visually spot the UAV. The UAV computer system may be configured in such a way that UAV operation will maintain the UAV in visual line of sight of a base location.

Abstract: A system for controlling vehicles using distributed cloud computing is provided. The system includes a first layer cloud server for collecting vehicle status data generated in a vehicle from the vehicle in real time and processing the collected data in real time. A second layer cloud server receives the vehicle status data generated in the vehicle, data collected by the first layer cloud server or data processed in the first layer cloud server, processes the received data, stores the processed data, and provides the stored data to the vehicle directly or via the first layer cloud server.

Abstract: An apparatus including an interface and a processor. The interface may be configured to receive pixel data of an area external to a vehicle. The processor may be configured to generate video frames from the pixel data, perform computer vision operations on the video frames to detect objects in the video frames and determine characteristics of the objects, analyze the characteristics of the objects to determine a visually observable status of the objects, perform a comparison of the visually observable status to a remote command and send the remote command if the comparison determines that the visually observable status does not match the remote command. The remote command may be configured to control the visually observable status of the objects.

Abstract: A vehicle control system for automated driver-assistance includes a model-based controller that generates a first control signal to alter an operation of a plurality of actuators of a vehicle based on a reference trajectory for the vehicle, and a present state of the vehicle and actuators. The vehicle control system further includes a neural network controller that generates a second control signal to alter the operation of the actuators of the vehicle based on a reference trajectory for the vehicle, and the present state of the vehicle and actuators. The vehicle control system further includes a combination module that combines the first control signal and the second control signal to operate the actuators based on a combined signal.

Abstract: A device performs operations including determining a probability that a vulnerable road user (VRU) will continue on a current path (e.g., in connection with controlling an autonomous vehicle). The device receives an image depicting a vulnerable road user (VRU). The device inputs at least a portion of the image into a model, and receives, as output from the model, a plurality of probabilities describing the VRU, each of the probabilities corresponding to a probability that the VRU is in a given state. The device determines, based on at least some of the plurality of probabilities, a probability that the VRU will exhibit a behavior, and outputs the probability that the VRU will exhibit the behavior to a control system.

Abstract: Techniques for procedurally generating scenarios that verify and validate predictions from or operation of a vehicle safety system are discussed herein. Sensors of a vehicle may detect one or more objects in the environment. A model may determine intersection values indicative of probabilities that the object will intersect with a trajectory of the vehicle. A vehicle may receive one or more intersection values from a model usable by a computing device to validate a prediction from a vehicle safety system.

Abstract: A method and arrangement for storing and recalling of setting values of a vehicle (10) and/or implement (14) that can be used for agricultural purposes comprising the following steps: inputting of at least one setting value for an actuator (49) of the vehicle (10) and/or implement (14) by a user interface; transmitting of a command based on the setting value to a control unit (32, 34, 38, 48) standing in operational connection with the actuator (49); and storing of setting data based on the setting value in a memory (72) in order to recall the setting value on the user interface or another user interface as required, wherein the setting value is converted into setting data using meta data regarding technical properties of the vehicle (10) and/or implement (14), the setting data representing a physical measure of the adjustment of the vehicle (10) and/or implement (14) achieved by the actuator (49) based on the setting value, the measure calculated based on the meta data and the setting value, and the setting

Abstract: An obstacle recognition device, a vehicle system including the same, and a method thereof are provided. The obstacle recognition device includes a storage storing data and an algorithm for calculating a risk probability and a processor configured to execute the algorithm to generate an occupancy grid map based on a sensing value of at least one ultrasonic sensor, calculate the risk probability of each cell on the occupancy grid map, and determine a shape and location of an obstacle based on the risk probability of each cell.

Abstract: Systems and methods for autonomous vehicle state management are provided. An offboard state service can obtain a vehicle command associated with changing an onboard-defined state of an autonomous vehicle. Data indicative of the command can be provided to a computing system onboard the autonomous vehicle. The onboard computing system can initiate a vehicle action in accordance with the command and provide a command response indicative of an updated vehicle status for the onboard-defined state to the state service. In response, the state service can update a current status for the onboard-defined state as represented by a vehicle profile corresponding to the autonomous vehicle. The state service can generate an update event indicative of the vehicle state and the updated current status and publish the update event to a distributed event stream such that a number of devices subscribed to the event stream can receive data indicative of the update event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for an unmanned aerial vehicle control point selection system. A first unmanned aerial vehicle can navigate about a geographic area while a second unmanned aerial vehicle can capture images of the first unmanned aerial vehicle. Location information of the first unmanned aerial vehicle can be recorded, and a system can identify the first unmanned aerial vehicle in the captured images. Utilizing the recorded location information, the system can identify landmarks proximate to the first unmanned aerial vehicle identified in the images, and determine location information of the landmarks. The landmarks can be assigned as ground control points for subsequent flight plans.