Abstract: A computer implemented method of path verification in a computer system is described. A user provides input to mark a displayed image of a scenario. A path is generated representing the trajectory of a vehicle. Control points along the path are recorded, each control point associated with a vehicle position and target speed. A vehicle position end target speed of two control points is used to calculate at least one path verification parameter which defines how a vehicle travelling along the path would behave. The at least one verification parameter is compared with a corresponding threshold value; and an alert is generated to the user at the user interface when the at least one path verification parameter exceeds the corresponding threshold value.

Abstract: An automatic landing system for a vertical take-off and landing aircraft includes: a camera mounted on a vertical take-off and landing aircraft; a relative-position acquisition unit configured to perform image processing on an image captured by the camera, the image including a marker group provided at a target landing point, to acquire a relative position between the vertical take-off and landing aircraft and the target landing point; and a control unit configured to control the vertical take-off and landing aircraft such that the relative position becomes zero, in which the marker group includes a plurality of markers that are arranged side by side and that have different center positions from each other, the markers are larger as arranged farther away from the target landing point, and the relative-position acquisition unit acquires the relative position based on a distance between the marker recognized in the image and the target landing point.

Abstract: Systems and methods for unmanned aerial vehicle (UAV) collision prevention are provided. The method includes receiving an indication of a location as a no crash zone (NCZ), calculating a trajectory for flight of a vehicle including a plurality of location points, generating a risk score for each location point of the plurality of location points, generating, based on the generated risk scores for each of the location points, a flight risk value for the trajectory of the flight of the vehicle, determining the flight risk value is below a risk threshold, and loading the trajectory to the vehicle.

Abstract: There is disclosed a control system and a method for a host vehicle operable in an autonomous mode. The control system comprises one or more controllers. The speed and/or path of the vehicle in the autonomous mode is appropriate to a driving context.

Abstract: Provided is a work vehicle capable of excavating an excavation object efficiently and in various excavation patterns with appropriate fuel efficiency, regardless of the operator's skill level. The work vehicle includes a controller. The controller executes control including insertion control, acceleration control, and deceleration control. The insertion control keeps the tilt amount (stroke amount S2) of the bucket and increases the lift amount (stroke amount S1) of the lift arm in the insertion period Ph1 from the timing when the work vehicle meets an entry condition for object, where the acceleration ? of the vehicle becomes negative, to the timing when the acceleration ? first becomes positive.

Abstract: Vehicle data is acquired, and is linked with each vehicle component, first degree of abnormality is determined for each vehicle component. When detecting collision, vehicle data is acquired during self-travelling after the collision. If vehicle is not capable of self-travelling, by referring to post-collision vehicle data etc., second degree of abnormality after the collision is calculated. The first and second degrees of abnormality are compared, if the second degree of abnormality is greater than the first degree of abnormality by a predetermined value or more, vehicle component is identified as vehicle component which is outside an impact area, but has been affected in terms of deterioration etc., and necessary information is displayed. When there is an intentional driving characteristic change after the collision, vehicle component is not identified as vehicle component having been affected in terms of deterioration etc.

Abstract: In one embodiment, one or more suspension systems of a vehicle may be used to mitigate motion sickness by limiting motion in one or more frequency ranges. In another embodiment, an active suspension may be integrated with an autonomous vehicle architecture. In yet another embodiment, the active suspension system of a vehicle may be used to induce motion in a vehicle. The vehicle may be used as a testbed for technical investigations and/or as a platform to enhance the enjoyment of video and/or audio by vehicle occupants. In some embodiments, the active suspensions system may be used to perform gestures as a means of communication with persons inside or outside the vehicle. In some embodiments, the active suspensions system may be used to generate haptic warnings to a vehicle operator or other persons in response to certain road situations.

Abstract: A method of controlling a transition aircraft having actuators and which transitions between a first take-off/landing regime and a second horizontal flight regime, including: controlling a first actuator subset in the first regime and a second actuator subset in the second regime using the flight controller, by: a) providing measurements or estimates of flight parameters; b) depending on a current regime, checking whether a predefined set of conditions for that regime are fulfilled, by comparing flight parameters with threshold values; c) if conditions are fulfilled, signalling a decision-maker and awaiting confirmation regarding a transition to the other regime; d) instructing the flight controller to make the transition if approved; e) after transitioning in step d), commanding the aircraft according to the other regime; and f) returning to step a). Step e) includes gradually blending in a control law for the other regime over time while blending out the current regime.

Abstract: A loading calculation module includes a storage unit, an inertial sensing unit and a calculation unit. The first storage unit is configured to store a relationship between an engine performance and a load, a sprung mass, a centroid distance between a sprung centroid, a rotation center and a moment of inertia. The inertial sensing unit is configured to detect a tilt angle, a tilt angular velocity, a tilt angular acceleration and a lateral acceleration. The calculation unit is configured to obtain a load corresponding to the engine performance according to the relationship between the engine performance and the load; and obtain a load position according to the moment of inertia, the tilt angle, the tilt angular velocity, the tilt angular acceleration, the lateral acceleration, the load and the centroid distance.

Abstract: Provided are a trajectory prediction method and device, a storage medium, and a computer program to avoid low accuracy and low reliability of a prediction result in conventional trajectory prediction methods. A trajectory prediction neural network acquires input current trajectory data and current map data of current environment when a moving subject moves in the current environment. The current trajectory data and the current map data are expressed as a current trajectory point set and a current map point set in a high-dimensional space. A global scene feature is extracted according to the current trajectory point set and the current map point set. The global scene feature has a trajectory feature and a map feature of the current environment. Multiple prediction trajectory point sets of the moving subject and a probability corresponding to each prediction trajectory point set are predicted and output according to the global scene feature.

Abstract: Aspects an autonomous driving system with air support are described herein. The aspects may include an unmanned aerial vehicle (UAV) in the air and a land vehicle on the ground communicatively connected to the UAV. The UAV may include at least one UAV camera configured to collect first ground traffic information and a UAV communication module configured to transmit the collected first ground traffic information. The land vehicle may include one or more vehicle sensors configured to collect second ground traffic information surrounding the land vehicle, a land communication module configured to receive the first ground traffic information from the UAV, and a processor configured to combine the first ground traffic information and the second ground traffic information to generate a world model.

Abstract: A control device for a human-powered vehicle comprises an electronic controller configured to obtain driving-environment information relating to driving environment of the human-powered vehicle. The driving-environment information includes at least one of traffic information relating to traffic and road object information relating to road objects. The electronic controller is configured to control an electric component based on the driving-environment information.

Abstract: Methods and systems for operating a hybrid vehicle having a first power source that uses a rechargeable battery and a second power source that uses a fuel. Preview information relating to upcoming road and traffic is used to generate a speed reference. A transmission torque reference is calculated using the speed reference and upcoming road information. A predictive power split plan is then determined by optimizing use of the first and second power sources to satisfy the transmission torque reference. At least a first sample of the predictive power split plan is then implemented.

Abstract: Implementations relate to using deep reinforcement learning to train a model that can be utilized, at each of a plurality of time steps, to determine a corresponding robotic action for completing a robotic task. Implementations additionally or alternatively relate to utilization of such a model in controlling a robot. The robotic action determined at a given time step utilizing such a model can be based on: current sensor data associated with the robot for the given time step, and free-form natural language input provided by a user. The free-form natural language input can direct the robot to accomplish a particular task, optionally with reference to one or more intermediary steps for accomplishing the particular task. For example, the free-form natural language input can direct the robot to navigate to a particular landmark, with reference to one or more intermediary landmarks to be encountered in navigating to the particular landmark.

Abstract: 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.

Abstract: A vehicle can connect to multiple networks and multiple frequency bands and can determine network parameters (e.g., available bandwidth, throughput, latency, signal strength, etc.) associated with the multiple networks. Additionally, the vehicle can access network map data associated with the multiple networks. As the vehicle traverses an environment, the vehicle can collect sensor data of the environment and/or vehicle data (e.g., vehicle pose, diagnostic data, etc.). Based on the vehicle location and the network map data, the vehicle can optimize the use of networks and frequency bands to determine portions of the sensor data and/or vehicle data to transmit via the one or more of the multiple networks and multiple frequency bands.

Abstract: Presented herein are systems and methods for operating a flight plan based distributed ledger system implemented on an aviation communications network. According to an aspect, data associated with communication transmissions occurring between communications elements of the aviation communications network may be recorded on the distributed ledger system. The communications elements involved in the distributed ledger system may be determined using a received flight plan. The flight plan information may be used to initialize the ledger information at each communications element involved in the distributed ledger system. The distributed ledger system may be updated to add or remove communications elements if the flight deviates from the original flight plan. After the flight plan is executed, the distributed ledger system may inactivate the ledger and store the ledger information in a centralized repository.

Abstract: A control target controller generates control targets in accordance with a route, the control targets being for controlling the location and orientation of a ship. The route has a plurality of via points. Each of the via points has information about a target location and a target orientation for the ship. The route is made up of a plurality of partial routes that sequentially connect the target locations of the via points. The control target controller comprises a transit target point generation part and an arrival determination part. The transit target point generation part can generate, as control targets, transit target points that are in the middle of the partial routes and have information about a target location and a target orientation for the ship. On the basis of the current location and the current orientation of the ship, the arrival determination part determines whether the ship has arrived at the transit target points.

Abstract: The server (electrified vehicle management device) includes a communication unit (second communication unit) that communicates with a mobile terminal (first communication unit) of a user of the electrified vehicle. The server includes a processor (control unit) that controls the communication unit. Then, the processor controls the communication unit so that a permission signal permitted to receive a privilege in the amusement park is transmitted to the mobile terminal of the user when a predetermined condition is satisfied with respect to power control in a EVSE (power station) provided in the amusement park (entertainment facility).

Abstract: An HEV-CU determines whether a traveling state requires giving priority to a front and rear driving force control (e.g., whether a vehicle is cornering) on the basis of a traveling state of the vehicle. If the traveling state requires giving priority to the front and rear driving force control (e.g., the vehicle is cornering), the HEV-CU-preferentially controls of an engine and a motor generator as well as engagement force of a differential limiting clutch in accordance with friction force between front and rear wheels and a road surface. If the traveling state does not require giving priority to the front and rear driving force control (e.g., the vehicle is traveling straight), the HEV-CU preferentially controls the driving of the motor generator to cause a charged state (SOC) of a high-voltage battery that supplies electric power to the motor generator to fall within a predetermined range.