Abstract: A method includes, during a delivery process of an unmanned aerial vehicle (UAV), receiving, by an image processing system, a depth image captured by a downward-facing stereo camera on the UAV. One or more pixels are within a sample area of the depth image and are associated with corresponding depth values indicative of distances of one or more objects to the downward-facing stereo camera. The method also includes determining, by the image processing system an estimated depth value representative of depth values within the sample area. The method further includes determining that the estimated depth value is below a trigger depth. The method further includes, based at least on determining that the estimated depth value is below the trigger depth, aborting the delivery process of the UAV.

Abstract: In various examples, a 3D surface structure such as the 3D surface structure of a road (3D road surface) may be observed and estimated to generate a 3D point cloud or other representation of the 3D surface structure. Since the estimated representation may be sparse, a deep neural network (DNN) may be used to predict values for a dense representation of the 3D surface structure from the sparse representation. For example, a sparse 3D point cloud may be projected to form a sparse projection image (e.g., a sparse 2D height map), which may be fed into the DNN to predict a dense projection image (e.g., a dense 2D height map). The predicted dense representation of the 3D surface structure may be provided to an autonomous vehicle drive stack to enable safe and comfortable planning and control of the autonomous vehicle.

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 computer hardware system includes a full self-driving (FSD) assistive system for assisting a user with a trip using a FSD autonomous vehicle and hardware processing configured to initiate the following executable operations. Based upon a first user input to a computing device associated with the user, a proposed route of the trip is received. A previously-stored user profile of the user and a context of the trip is retrieved. The vehicle is searched for based upon the user profile, the proposed route, and the context. The vehicle is configured using the user profile. External sensors are polled for road conditions along the route, and the road conditions are forwarded to the vehicle. An onboard analytics device of the vehicle uses the road conditions to change a driving mode of the vehicle.

Abstract: A method for operating a driver information system in an ego vehicle is provided, wherein an operating state of a lighting apparatus of the ego vehicle is detected, and a driver information display is generated and output. The driver information display comprises a graphic ego object which represents the ego vehicle. In this context, the ego object comprises a rear depiction of the ego vehicle, wherein the ego object is generated depending on the detected operating state.

Abstract: The following relates generally to determining effectiveness of an update to a vehicle feature. In some embodiments, information indicating an update to a vehicle feature, and accident record information may be received. A first dataset from before the update was implemented in the vehicle, and a second dataset from after the update was implemented in the vehicle may then be constructed. An effectiveness score may then be calculated based upon the first and second datasets.

Abstract: Example data processing methods and apparatus are provided. One example method includes obtaining an image captured by an in-vehicle camera. A to-be-detected target in the image is determined. A feature region corresponding to the to-be-detected target in the image is further determined based on a location of the to-be-detected target in the image. A first parking state is determined based on the image and wheel speedometer information. A first homography matrix corresponding to the first parking state is determined from a prestored homography matrix set, where different parking states correspond to different homography matrices. Image information of the feature region is processed based on the first homography matrix to obtain a detection result.

Abstract: A use management device includes: a traveling information acquisition part which acquires subsequent prospective traveling information about an electrically driven cart; a remaining amount information acquisition part which acquires remaining amount information about a battery; a determination section which determines, based on the prospective traveling information and the remaining amount information, whether charging of the battery is necessary; and a control section which executes a permission control of permitting a traveling motor to drive when the determination section determines that the charging of the battery is unnecessary, and executes a forbidding control of forbidding the traveling motor from driving when the determination section determines that the charging of the battery is necessary.

Abstract: A method for controlling a vehicle (1) assembled from a set of modules (20). The vehicle (1) includes: at least one drive module (30); and at least one functional module (40). The at least one drive module (30) has a pair of wheels (32) and is configured to autonomously operate and drive the assembled vehicle (1) wherein the modules (30, 40, 70, 80) of the vehicle (1) are configured to communicate with the control device (100). The method includes: receiving (s101) data from the modules (30, 40, 70, 80) of the vehicle (1), wherein the data includes a value of at least one parameter associated with a current condition of the modules (30, 40, 70, 80); evaluating (s102) the received data by comparing the value of the at least one parameter with a predetermined value or value interval for the at least one parameter; and controlling (s103) the vehicle (1) based on the evaluation.

Abstract: A working machine includes a machine body capable of traveling, a position detector to detect a position of the machine body, and a controller to control the machine body based on the position of the machine body detected by the position detector and a planned travel route. The planned travel route includes a straight section on which the machine body travels straight, and the controller includes a threshold setter to set a threshold according to work, and causes the machine body to perform a recovery movement to make a deviation between the position of the machine body detected by the position detector and the planned travel route less than the threshold when the machine body is at a start point of the straight section or is about to enter the start point of the straight section.

Abstract: In case a vehicle speed control is performed in response to a failure in a steer-by-wire steering system, the vehicle is prevented from accelerating following a speed reduction caused by a braking operation of the vehicle operator. The speed limit control limits a traveling speed of the vehicle below an upper limit speed upon detecting a fault in the steering system, and is configured to set a target deceleration of the vehicle according to the limited traveling speed, perform a deceleration control to bring an actual deceleration of the vehicle to become near the target deceleration, and restrict the actual deceleration from changing to an acceleration side in the deceleration control.

Abstract: A navigation system includes an IMU, a navigation estimator configured to estimate a current navigation solution based on (i) a last navigation solution, and (ii) a specific force vector and an angular rate vector measured by the IMU, an RI sensor, an RI data preprocessor configured to: perform a priori transformations of last RI data and current RI data to obtain transformed last RI data and transformed current RI data based on the last navigation solution and the current navigation solution, respectively, an RI filter manager (RFM) configured to construct a delta pose registration cost gradient (DPRCG) measurement based on (i) the transformed last RI data, (ii) the transformed current RI data, (iii) the current navigation solution, and (iv) the last navigation solution. The navigation estimator is further configured to determine an absolute navigation solution based on at least (i) the current navigation solution, and (ii) the DPRCG measurement.

Abstract: Systems and methods for facilitating storage of an autonomous vehicle (“AV”) in a storage facility are disclosed. A server receives a storage request from an electronic device and retrieves a set of available storage facilities stored in a storage facilities database. The server obtains a current location of the AV and determines a preferred storage facility of the set of available storage facilities based in part on the current location of the AV and a set of storage preferences stored in a storage preference database. The server generates a set of vehicle control instructions based on a location of the preferred storage facility and the location of the AV, and transmits the set of vehicle control instructions to the AV causing the AV to navigate to the preferred storage facility from the current location of the AV.

Abstract: An unmanned aerial vehicle includes: a sensor including at least a microphone that generates sound data; and a processor. The processor determines a quality of a target sound by using the sound data generated by the microphone, acquires a positional relationship between the unmanned aerial vehicle and a sound source of the target sound by using data generated by the sensor, determines a destination to which the sound source is to move based on the quality of the target sound and the positional relationship, and presents target movement information that prompts the sound source to move toward the destination.

Abstract: Methods and apparatus, including computer program products, are provided In one aspect there is provided a method. The method may include detecting, at a first node, an event; generating, at the first node, a message in response to the detected event; and sending, at the first node, the message to at least a second node to enable the second node to determine at least one of a reliability or an importance of the message. Related apparatus, systems, methods, and articles are also described.

Abstract: A method comprising: operating a swarm of autonomous vehicles to maximize a number of intercepted targets, wherein, for each of said autonomous vehicles, the method comprises: identifying a plurality of objects in an operational area as targets or obstacles; determining a location parameter for each of said plurality of objects; calculating a trajectory of motion for said autonomous vehicle based at least in part on said location parameters of each of said plurality of objects, wherein said calculating maximizes: (i) a probability of intercepting each of said targets, and (ii) a probability of avoiding collisions with each of said obstacles; and moving said autonomous vehicle along said trajectory of motion.

Abstract: A vehicle driving assistance system performs traveling assistance control under which an own vehicle automatically travels with. The traveling assistance control includes first constant-speed control for automatically controlling the acceleration of the own vehicle, based on a first vehicle-speed range including a set vehicle speed, such that the vehicle speed of the own vehicle is kept equal to the set vehicle speed, and second constant-speed control for automatically controlling the acceleration of the own vehicle, based on a second vehicle-speed range including the set vehicle speed, such that the vehicle speed of the own vehicle is kept equal to the set vehicle speed. The second vehicle-speed range is set to a wider range than the first vehicle-speed range. The vehicle driving assistance system switches the traveling assistance control between the first constant-speed control and the second constant-speed control, according to the traveling state of the own vehicle.

Abstract: Disclosed are methods, systems, and non-transitory computer-readable media for transmitting obstacle information to one or more operator displays associated with an aircraft. For instance, the method may include obtaining aircraft flight information including a current position and altitude; retrieving obstacle information for a flight area; scanning the flight area with environment sensors to identify observed obstacles and generate observed obstacle information.

Abstract: Provided is an anomaly detection device that acquires a degree of anomaly required for anomaly detection when a feature pattern of time series data changes over time. The anomaly detection device is a device that detects the degree of anomaly in the time series data. The anomaly detection device includes a first acquisition unit, a prediction unit, and an anomaly degree acquisition unit. The first acquisition unit acquires, from a first section that is a partial section of the time series data, a dynamic feature pattern of the first section. The prediction unit predicts data of a second section that is a partial section of the time series data later than the first section by using the feature pattern. The anomaly degree acquisition unit acquires the degree of anomaly based on a difference between the predicted second section data and actual data of the second section.

Abstract: Presented are intelligent vehicle systems for thermal event mitigation during vehicle towing, methods for making/using such systems, and vehicles equipped with such intelligent control systems. A method of operating a host vehicle includes a resident or remote vehicle controller verifying the host vehicle is an incapacitated state. Responsive to the incapacitation of the host vehicle, the controller detects the host vehicle being towed by a tow vehicle and identifies a wireless-enabled portable computing device (PCD) within a predefined range of the host vehicle. Responsive to the host vehicle being towed, the controller determines if the wireless-enabled PCD is on the tow vehicle while towing the host vehicle. Upon detection of a thermal event in at least one battery cell in the host vehicle's battery system while the host vehicle is being towed, the controller responsively commands a resident vehicle subsystem to execute a control operation to mitigate the thermal event.