Abstract: The present disclosure is directed to performing one or more validity checks on potential trajectories for a device, such as an autonomous vehicle, to navigate. In some examples, a potential trajectory may be validated based on whether it is consistent with a current trajectory the vehicle is navigating such that the potential and current trajectories are not too different, whether the vehicle can feasibly or kinematically navigate to the potential trajectory from a current state, whether the potential trajectory was punctual or received within a time period of a prior trajectory, and/or whether the potential trajectory passes a staleness check, such that it was created within a certain time period. In some examples, determining whether a potential trajectory is feasibly may include updating a set of feasibility limits based on one or more operational characteristics of statuses of subsystems of the vehicle.

Abstract: According to one embodiment, a travel planning system for a plurality of mobile objects which travel in a travel network including a plurality of traveling paths includes first processing circuitry and second processing circuitry. The first processing circuitry generates a plurality of traveling timing schedules including timings of traveling on the traveling paths for the plurality of mobile objects under a condition that conflict among the mobile objects does not occur on the traveling paths, based on: position information of the plurality of mobile objects; structure information of the travel network; and a plurality of route plans which designates order of passing through one or more designated areas in the travel network for the plurality of mobile objects. The second processing circuitry transmits movement command data for the plurality of mobile objects on a basis of the plurality of traveling timing schedules.

Abstract: In one embodiment, a method of operating an autonomous driving truck includes receiving location data from a first inertial measurement unit, a first global positioning system, a second inertial measurement unit, and a second global positioning system at a planning module of the autonomous driving truck. The first inertial measurement unit and the first global positioning system are attached to a cabin of the autonomous driving truck and the second inertial measurement unit and the second global positioning system are attached to a body structure of the autonomous driving truck in which the body structure extends away from the cabin. The method further includes receiving location data from the second inertial measurement unit and the second global positioning system at a control module of the autonomous driving truck and controlling the autonomous driving truck based on the received location data at the planning and control modules.

Abstract: The present invention is provided to more reliably keep a work vehicle from coming into contact with an obstacle during automated driving. The work vehicle includes an electronic control system for automated driving that automatically drives the vehicle body. The electronic control system includes an obstacle detection module configured to detect presence or absence of an obstacle, and a contact avoidance control unit configured to perform, upon the obstacle detection module detecting an obstacle, contact avoidance control to keep the vehicle body from coming into contact with the obstacle. The obstacle detection module includes a plurality of obstacle searchers that are distributed on the front end portion and the right and left end portions of the vehicle body such that the front side and the right and left lateral sides of the vehicle body are search-target areas.

Abstract: A method for positioning an autonomous moving device includes steps of: acquiring a current positioning signal of an autonomous moving device during a moving process, and a reference positioning signal of the autonomous moving device before the current positioning signal; resolving the reference positioning signal and the current positioning signal to acquire error data; and processing the error data and position information of the reference positioning signal to acquire current position information of the autonomous moving device.

Abstract: Systems and methods for controlling autonomous vehicles are provided. In one example embodiment, a computer-implemented method includes obtaining, by a computing system that includes one or more computing devices onboard an autonomous vehicle, data indicative of an identifier associated with a user device of a user. The identifier can be assigned to the user device by a cellular network. The method includes determining, by the computing system, location data associated with the user device based at least in part on the identifier associated with the user device. The method includes determining, by the computing system, a vehicle route based at least in part on the location data associated with the user device. The method includes causing, by the computing system, the autonomous vehicle to initiate travel in accordance with the vehicle route.

Abstract: A human-powered vehicle control device includes an electronic controller that controls a motor assisting in propulsion of a human-powered vehicle including a crank. The controller changes an assist force ratio generated by the motor to human drive force input to the crank accordingly to the human drive force and a crank rotational speed. The controller increases the ratio as the human drive force increases while the crank rotational speed is constant and the human drive force is in a first range. The controller controls the motor so that the ratio is larger for a case where the human drive force is a first predetermined value in a first range and the crank rotational speed is in a second range than for a case where the human drive force is the first predetermined value and the crank rotational speed is in a third range higher than the second range.

Abstract: Dynamic customization of an autonomous vehicle experience is presented herein. A dynamic recommendation engine can comprise a subscriber interface component, a data component, and a configuration component. The subscriber interface component can receive, from a subscriber of an autonomous vehicle service, a request specifying a route of transport by an autonomous vehicle; and based on the request, the data component can obtain, via a network slice comprising a virtual network function of the autonomous vehicle service, profile information for the subscriber and route information for the route. Further, the configuration component can determine, via the network slice based on the profile information and the route information, configuration data for the autonomous vehicle, and send, via the network slice, the configuration data directed to the autonomous vehicle to facilitate the transport by the autonomous vehicle.

Abstract: Systems, devices, and methods for drone pairing are disclosed. Drones may be paired by configuring each of a first drone and a second drone in a drone pairing mode, establishing physical contact between the first drone and the second drone while in the drone pairing mode, determining an acceleration parameter for each of the first drone and the second drone related to the physical contact between the first drone and the second drone, comparing the determined acceleration parameter of the first drone and the determined acceleration parameter of the second drone to identify a match, and pairing the first drone and the second drone in response to the identified match between the compared acceleration parameters of the first and second drones.

Abstract: A driving assistance apparatus can execute deceleration assistance of decelerating a host vehicle independently of an operation by a driver. The driving assistance apparatus is provided with: an acquirer configured to obtain surrounding information associated with a surrounding situation of the host vehicle; and a controller programmed to reduce a deceleration assistance amount associated with the deceleration assistance when execution of the deceleration assistance is released. The controller is programmed to quickly reduce the deceleration assistance amount when execution of the deceleration assistance is released, if a surrounding situation indicated by the obtained surrounding information is a first situation in which the host vehicle can be required to accelerate, in comparison with a second situation in which the host vehicle cannot be required to accelerate.

Abstract: Methods and systems that allow neural network systems to maintain or increase operational accuracy while being able to operate in various settings. A set of training data is collected over each of at least two different settings. Each setting has a set of characteristics. Examples of setting characteristic types can be time, geographical location, and/or weather condition. Each set of training data is used to train a neural network resulting in a set of coefficients. For each setting, the setting characteristics are associated with the corresponding neural network having the resulting coefficients and neural network structure. A neural network, having the coefficients and neural network structure resulted after training using the training data collected over a setting, would yield optimal results when operated in/under the setting. A database management system can store information relating to, for example, the setting characteristics, neural network coefficients, and/or neural network structures.

Abstract: A driving guidance system that provides a driving guidance to a driver when the driver makes operations to remotely control a vehicle in a driving route. The driving guidance system includes at least one driving guidance equipment, an analytic engine, a control platform. The driving guidance equipment is distributed along the driving route for recording data of the vehicle. The analytic engine receives and analyzes the data of the vehicle to generate a plurality of features of the vehicle. The control platform further includes a real virtuality objects generator and a display. The real virtuality objects generator generates a plurality of real virtuality objects based on the features of the vehicle and the display shows the real virtuality objects to the driver of the vehicle for providing the driving guidance.

Abstract: An autonomous system including a plurality of autonomous bodies, each of the autonomous bodies includes a situation grasping unit that grasps situation, an operation determining unit that determines an operation based on the grasped situation, and an operation executing unit that executes the determined operation, the plurality of autonomous bodies included in the autonomous body system includes one or more first autonomous bodies and two or more second autonomous bodies, situation grasped by the situation grasping unit of the first autonomous body includes situation of the second autonomous body, the situation grasped by the situation grasping unit of the second autonomous body includes a result of an operation executed by the operation executing unit of the first autonomous body, and the operation determining unit of the second autonomous body determines an operation based on the result of the operation executed by the operation executing unit of the first autonomous body.

Abstract: An asset management mapping system including a microphone recording the audio of the asset inspector and a condition signal generator generating an audio condition signal based on asset inspector input from a keypad including condition selectors recorded into a global positioning system audio and video recorder that associates the audio and video with a gps location to create a pavement condition database. The database is interpreted to generate a condition output map of the areas inspected.

Abstract: A control device includes a processor which: obtains first region information indicating a first region; obtains first position information indicating the position of an unmanned aerial vehicle tethered to a tethering device using a tether; and controls the tethering device using the first region information and the first position information to cause the tether to have tension corresponding to a specified distance which is at least one of the shortest distance between a boundary of the first region and the position of the unmanned aerial vehicle and a distance included in a predetermined range from the shortest distance.

Abstract: An agricultural harvester includes a cutting head configured to harvest an agricultural material, a transfer mechanism configured to transfer the harvested agricultural material from the agricultural harvester, and a fill management system. The fill management system is configured to provide open-loop control of an automated transfer of the agricultural material from the agricultural harvester. The fill management system includes a controller, a user interface module coupled to the controller and configured to receive user input indicative of a selected nudge direction, and a wireless communication module coupled to the fill management system and configured to communicate wirelessly with a receiving vehicle. The wireless communication module is configured to obtain storage dimensions relative to the receiving vehicle from the receiving vehicle.

Abstract: In response to perceiving a moving object, one or more possible object paths of the moving object are determined based on the prior movement predictions of the moving object, for example, using a machine-learning model, which may be created based on a large amount of driving statistics of different vehicles. For each of the possible object paths, a set of trajectory candidates is generated based on a set of predetermined accelerations. Each of the trajectory candidates corresponds to one of the predetermined accelerations. A trajectory cost is calculated for each of the trajectory candidates using a predetermined cost function. One of the trajectory candidates having the lowest trajectory cost amongst the trajectory candidates is selected. An ADV path is planned to navigate the ADV to avoid collision with the moving object based on the lowest costs of the possible object paths of the moving object.

Abstract: A system includes a flight plan database and a flight plan engine. The flight plan database is configured to store a local flight plan. The local flight plan includes one or more flight actions associated with a plan event condition including at least one of a time, a waypoint, or a position. The flight plan engine is configured to, while a platform is in an operational state, compare the plan event condition of at least one flight action to a current event condition to determine an action state of the at least one flight action, generate a group flight plan including the at least one action based on the action state, and transmit the group flight plan to one or more remote platforms.

Abstract: An electronic device comprises a wireless transmitter and an operation device. The operation device comprises a base, a brake lever, operation portions and an electronic controller. The base is to be removably attached to a handlebar. The operation portions includes first, second and third operation portions. The first operation portion is arranged on the base. The second and third operation portions are arranged adjacent to the brake lever and are disposed between the brake lever and the handlebar. At least one of the operation portions includes a lever. At least one of the operation portions includes a button. The electronic controller is configured to transmit an operation signal to the wireless transmitter upon operation of any of the operation portions to control at least one bicycle component that is any one of a shifting device, a brake device, an adjustable seatpost, a suspension and a drive unit.

Abstract: Aspects of the present disclosure include systems, methods, and devices to provide estimations of vehicular pick-up/drop-off zone (PDZ) availability. A request for vehicular PDZ availability at a location is received from a vehicular autonomy system of a vehicle. The request specifies an estimated time of arrival at the location. The PDZ availability at the location at the estimated time of arrival is estimated using a probabilistic model. A response to the request is generated based on the estimated PDZ availability. The response indicates the estimated PDZ availability. The response is transmitted to the vehicular autonomy system responsive to the request.