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.

Abstract: A plurality of fault conditions are detected on a communication network onboard a vehicle. The detected fault conditions, a fault condition importance, environment conditions, and a vehicle operation mode are input to a neural network that outputs rankings for respective detected fault conditions. The neural network is trained by determining a loss function based on a maximum likelihood principle that determines a probability distribution that ranks the detected fault conditions. The vehicle is operated based on the rankings of the fault conditions.

Abstract: Systems and methods described in this disclosure provide methods and systems for automatic deployment of a vehicle covering apparatus to protect the vehicle from environmental conditions such as severe weather.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a simulation of an environment that is being interacted with by a plurality of agents over a plurality of time steps, wherein the simulation comprises a respective simulation state for each time step that specifies a respective state of each agent at the time step. In one aspect, a method comprises, for each time step: obtaining a current simulation state for the current time step; generating a plurality of candidate next simulation states for a next time step; determining, for each candidate next simulation state, a discriminative score characterizing a likelihood that the candidate next simulation state is a realistic simulation state; and selecting a candidate next simulation state as the simulation state for the next time step based on the discriminative scores for the candidate next simulation states.

Abstract: A method for behavior cloned vehicle trajectory planning is described. The method includes perceiving vehicles proximate an ego vehicle in a driving environment, including a scalar confidence value of each perceived vehicle. The method also includes generating a bird's-eye-view (BEV) grid showing the ego vehicle and each perceived vehicle based on each of the scalar confidence values. The method further includes ignoring at least one of the perceived vehicles when the scalar confidence value of the at least one of the perceived vehicles is less than a predetermined value. The method also includes selecting an ego vehicle trajectory based on a cloned expert vehicle behavior policy according to remaining perceived vehicles.

Abstract: A vehicle control device comprises a unit to detect a distance to an obstacle; a unit to detect a speed of the vehicle; and a reduction support unit to, based on the speed and the distance, perform support for reduction of a speed of the vehicle. The reduction support unit changes the distance at which the reduction support is to be performed between a case where driving during parking and a case where not driving during parking. The distance at which the reduction support is to be performed is, for a first speed range, longer in a case where driving during parking than in a case where not driving during parking, and, for a second speed range, longer in a case where not driving during parking than in a case where driving during parking.

Abstract: A method including generating a curvilinear coordinate system from a current position of the vehicle. The method further includes generating a probability distribution from the curvilinear coordinate system and predicting a future vehicle behavior of the vehicle based on the probability distribution.

Abstract: A system for identifying data includes an interface and a processor. The interface is configured to receive training data samples associated with interesting events of an interesting event type. The processor is configured to train a model to recognize the interesting events; determine embedded vectors associated with the interesting events; and determine a representative embedded vector associated with the interesting event type.

Abstract: When a required download time is equal to or shorter than a communication-enabled time on a running route, an update program is received from an external device via wireless communication, so a vehicular program is appropriately updated. Besides, when the required download time is longer than the communication-enabled time on the running route, a driving method ensuring the communication-enabled time that is equal to or longer than the required download time is suggested to a driver, so the update program is easy to receive via wireless communication. In consequence, the opportunities to update the vehicular program can be ensured. That is, the vehicular program can be restrained or prevented from being updated with a delay.

Abstract: An apparatus for controlling a vehicle capable of performing autonomous driving is provided. The apparatus includes an autonomous driving device that executes the autonomous driving and generates a transition demand when it is impossible to execute the autonomous driving. A driving controller performs a minimum risk maneuver (MRM) of applying a deceleration pattern differently depending on a driving environment of the vehicle, when the transition demand is generated, but when driving manipulation by a driver does not occur. A subsequent safety ensuring function is performed according to the MRM for the driver to recognize the MRM, and a drive mode of the vehicle is changed to a drive mode with a rapid response speed to acceleration or steering.

Abstract: According to an aspect of an embodiment, operations may comprise receiving a plurality of frame sets generated while navigating a local environment, receiving an occupancy map (OMap) representation of the local environment, for each of the plurality of frame sets, generating, using the OMap representation, one or more instances each comprising a spatial cluster of neighborhood 3D points generated from a 3D sensor scan of the local environment, and classifying each of the instances as dynamic or static, tracking instances classified as dynamic across the plurality of frame sets using a tracking algorithm, assigning a single instance ID to tracked instances classified as dynamic across the plurality of frame sets, estimating a bounding box for each of the instances in each of the plurality of frame sets, and employing the instances as ground truth data in a training of one or more deep learning classifiers.

Abstract: A processor is operably coupled to a time of flight (TOF) camera, a light detection and ranging (LIDAR) sensor, and an optical camera. The processor can receive a TOF signal representative of a first coordinate associated with a stick-up height of a tool joint of a pipe of a drill string during a tripping operation on a rig drill floor, and a pitch and a roll of the tool joint. The processor can receive a LIDAR signal representative of a second coordinate associated with the stick-up height, and the pitch of the tool joint. The processor can receive an optical camera signal representative of a third coordinate associated with the stick-up height of the tool joint and the roll of the tool joint. The processor can generate a pose estimate and an orientation estimate based on the signals.

Abstract: A system and method for determining a predicted trajectory of a human-driven host vehicle as the human-driven host vehicle approaches a traffic signal. The method includes: obtaining a host vehicle-traffic light distance dx and a longitudinal host vehicle speed vx that are each taken when the human-driven host vehicle approaches the traffic signal; obtaining a traffic light signal phase Pt and an traffic light signal timing Tt; obtaining a time of day TOD; providing the host vehicle-traffic light distance dx, the longitudinal host vehicle speed vx, the traffic light signal phase Pt, the traffic light signal timing Tt, and the time of day TOD as input into an artificial intelligence (AI) vehicle trajectory prediction application, wherein the AI vehicle trajectory prediction application implements an AI vehicle trajectory prediction model; and determining the predicted trajectory of the human-driven host vehicle using the AI vehicle trajectory prediction application.

Abstract: An artificial intelligence device mounted on a vehicle is provided. A sensing unit acquires a gyroscope sensor value, an acceleration sensor value, a GPS sensor value, and a proximity sensor value. If the acquired data satisfies a predetermined reference value, a processor inputs the acquired sensor values to an artificial intelligence model, acquires whether an impact requiring self-diagnosis occurs and impact direction information as a result value, selects an ECU module to perform self-diagnosis according to the acquired result value, and performs self-diagnosis.

Abstract: A vehicle includes a controller, programmed to responsive to receiving a credential for connecting to a wireless network from a mobile device, connect to the wireless network using the credential; and establish a link with the mobile device via the wireless network, wherein the credential is received through a cloud server via a wireless connection other than the wireless network.

Abstract: A technique for validating a balcony to receive delivery of a parcel via a UAV includes obtaining a first identification of a general location of the balcony; generating a first image representing a building including the balcony where the first image is selected based upon the location identified; obtaining a second identification or a confirmation of a precise location of the balcony in the building where the second identification or the confirmation are received in response to an end-user interaction with the first image; determining a deliverability score based at least in part on the precise location of the balcony; and indicating an enrollment status to the end-user where the enrollment status is generated based upon the deliverability score.

Abstract: A method and a system for avoiding collision of an object with a work tool coupled to a work machine. The method comprising generating an object signal by an object detector, monitoring the object signal in real-time by a processor, processing the object signal to detect an object at least partially buried in the ground surface, determining a distance between the object and a distance threshold, and sending by a controller a control signal to one or more of a machine control system and a work tool control system to modify one or more of a movement of the work tool or the work machine based on the object reaching the distance threshold.

Abstract: A vehicle includes one or more sensors arranged on at least one of a dashboard, a roof, and a center console of the vehicle, or one or more image capturing devices for capturing one or more images from a left side and a right side of the vehicle, an electronic control unit (ECU) configured to communicate with the one or more sensors or the one or more image capturing devices, and at least one of a morphing surface, a windshield display, and one or more displays configured to be controlled by the ECU, where the one or more sensors are arranged under a black panel surface.

Abstract: The present invention discloses an unmanned aerial vehicle control system and an implementation method therefor, a ground control device and a relay station, where the unmanned aerial vehicle control system includes an unmanned aerial vehicle and a ground control device, and further includes one or more relay stations in communication connection with the ground control device through a local area network or the Internet, the ground control device being configured to send a control instruction to control the unmanned aerial vehicle, and the relay station being configured to: when satisfying a preset condition, receive the control instruction sent by the ground control device, and send the control instruction to the unmanned aerial vehicle.