Abstract: An exemplary method to determine an airspeed and an angle of attack of a propeller powered vehicle includes determining the power delivered to the propeller, the air density, a propeller power coefficient, an advance ratio for the propeller, and the airspeed using the advance ratio and determining the angle of attack using the airspeed.

Abstract: An aerial vehicle including a body, a first ranging device, a second ranging device and a controller is provided. The first ranging device is disposed on the body and is configured to detect a first distance between the first ranging device and the reflector. The second ranging device is disposed on the body and is configured to detect a second distance between the second ranging device and the reflector. The controller is configured to obtain an included angle between a direction of the body and the reflector according to the first distance and the second distance.

Abstract: An approach is provided for determining tunnel speed for a vehicle travelling through a tunnel. A tunnel processing platform aggregates probe data associated with at least one vehicle into at least one tunnel path based, at least in part, on a network geometry topology for at least one tunnel. The tunnel processing platform also designates at least one probe point collected upstream of the at least one tunnel as at least one starting point of the at least one tunnel path and at least one temporary probe point as at least one endpoint of the at least one tunnel path, wherein the at least one temporary probe point is downstream of the at least one tunnel. It then determines at least one temporary tunnel speed for the at least one tunnel path based, at least in part, on the timestamp for the at least one probe point and the current time associated with the at least one temporary probe point.

Abstract: Provided is a parking assist apparatus for a vehicle, the parking assist apparatus including a first module configured to set, as a movement path, a path along which the vehicle is movable to a target position, and determine movement assist information for moving the vehicle along the movement path; and a second module configured to execute parking assist control such that the vehicle moves in accordance with the determined movement assist information, the second module being further configured to, when an occupant performs a first operation before the vehicle has reached the target position, stop the vehicle, and execute pause processing for maintaining the movement assist information.

Abstract: A parking assistance device performs parking assistance control including steering angle control for changing a steering angle of a vehicle, driving force control for controlling a driving force of the vehicle, and braking force control for controlling a braking force of the vehicle. The parking assistance device notifies an occupant of a driving operation to be performed by the occupant, including a moving operation on a shift lever and an operation on a brake pedal when the vehicle reaches a switching position where a traveling direction of the vehicle is to be switched during performing the parking assistance control. When the driving operation is performed by the occupant, the parking assistance device restarts the parking assistance control at a timing when the occupant stops the operation on the brake pedal.

Abstract: A vehicle control device includes a scene determination unit determining whether or not a current traveling scene is a traveling-restricted scene, an order setting unit setting priorities corresponding to a restriction with respect to driving behaviors previously classified for different purposes in a case where it is determined that the traveling scene is the traveling-restricted scene and setting priorities with respect to the plurality of driving behaviors in a case where it is not determined that the traveling scene is the traveling-restricted scene, a traveling plan generating unit generating traveling plans corresponding to the plurality of priority-set driving behaviors, an executability determination unit determining executability of each of the plurality of generated driving behaviors, a traveling plan selection unit selecting the traveling plan corresponding to the driving behavior with the highest priority, and a traveling control unit controlling the traveling of the host vehicle based on the trav

Abstract: An unmanned aerial vehicle (UAV) is disclosed that includes a retractable payload delivery system. The payload delivery system can lower a payload to the ground using a delivery device that secures the payload during descent and releases the payload upon reaching the ground. The location of the delivery device can be determined as it is lowered to the ground using image tracking. The UAV can include an imaging system that captures image data of the suspended delivery device and identifies image coordinates of the delivery device, and the image coordinates can then be mapped to a location. The UAV may also be configured to account for any deviations from a planned path of descent in real time to effect accurate delivery locations of released payloads.

Abstract: Described is a system for analyzing time series data. A sequence of symbols is generated from a set of time series input data related to a moving vehicle using automatic segmentation. A grammar is extracted from the sequence of symbols, and the grammar is a subset of a probabilistic context-free grammar (PCFG). Using the grammar, time series input data can be analyzed, and a prediction of the vehicle's movement can be made. Vehicle operations for an autonomous vehicle are determined using the prediction.

Abstract: Disclosed is a networked array of radar enclosures that can be arranged to cover a desired geographical location. The array can detect moving objects in the coverage area. When warranted, elements of the array can also control the movement of associated objects, for example, friendly drones. The present invention also combines attributes that facilitate the less conspicuous detection and monitoring of moving objects, with the capability of distinguishing types of moving objects.

Abstract: The present teaching relates to a method, system, medium, and implementation of processing image data in an autonomous driving vehicle. Sensor data acquired by one or more types of sensors deployed on the vehicle are continuously received. The sensor data provide different information about surrounding of the vehicle. Based on a first data set acquired by a first sensor of a first type of the one or more types of sensors at a specific time, an object is detected, where the first data set provides a first type of information about the surrounding of the vehicle. Depth information of the object is then estimated via object centric stereo at object level based on the object detected as well as a second data set acquired by a second sensor of the first type of the one or more types of sensors at the specific time. The second data set provides the first type of information about the surrounding of the vehicle with a different perspective as compared with the first data set.

Abstract: A motion constraint-aided underwater integrated navigation method employing improved Sage-Husa adaptive filtering includes establishing a Doppler log error model; constructing a state equation for an underwater integrated navigation system employing Kalman filtering; according to a relationship between a centripetal acceleration and a forward velocity of an underwater vehicle, establishing a constraint condition, and constructing a complete motion constraint model; establishing two measurement equations; and establishing a filter equation, conducting calculation by using a standard Kalman filtering algorithm when an underwater glider normally runs, and conducting time updating, measurement updating and filtering updating by using an improved Sage-Husa adaptive filtering algorithm when a measurement noise varies.

Abstract: A vehicle having an imaging sensor that is arranged to monitor a field-of-view (FOV) that includes a travel surface proximal to the vehicle is described. Detecting the travel lane includes capturing a FOV image of a viewable region of the travel surface. The FOV image is converted, via an artificial neural network, to a plurality of feature maps. The feature maps are projected, via an inverse perspective mapping algorithm, onto a BEV orthographic grid. The feature maps include travel lane segments and feature embeddings, and the travel lane segments are represented as line segments. The line segments are concatenated for the plurality of grid sections based upon the feature embeddings to form a predicted lane. The concatenation, or clustering is accomplished via the feature embeddings.

Abstract: Vision-aided inertial navigation techniques are described. In one example, a vision-aided inertial navigation system (VINS) comprises an image source to produce image data at a first set of time instances along a trajectory within a three-dimensional (3D) environment, wherein the image data captures features within the 3D environment at each of the first time instances. An inertial measurement unit (IMU) to produce IMU data for the VINS along the trajectory at a second set of time instances that is misaligned with the first set of time instances, wherein the IMU data indicates a motion of the VINS along the trajectory. A processing unit comprising an estimator that processes the IMU data and the image data to compute state estimates for 3D poses of the IMU at each of the first set of time instances and 3D poses of the image source at each of the second set of time instances along the trajectory.

Abstract: The present application discloses a method and an apparatus for acquiring sample deviation data and an electric device, which relate to the fields of artificial intelligence technology, automatic driving technology, intelligent transportation technology and deep learning technology. The specific implementation solution is: in case of acquiring the sample deviation data, a first driving behavior parameter of a vehicle and a second driving behavior parameter of the vehicle in a simulated automatic driving mode are respectively acquired in the manual driving mode; and it is determined whether there is a deviation between the first driving behavior parameter and the second driving behavior parameter, and if there is a deviation, the vehicle is controlled to acquire the sample deviation data within a preset time period.

Abstract: A system and method for securing delivery of an autonomous vehicle. The method includes determining visual features of a captured image of a current location of the autonomous vehicle, the captured image generated by an image sensor communicatively coupled with the autonomous vehicle; retrieving location coordinates of the current location of the autonomous vehicle from a positioning sensor communicatively coupled with the autonomous vehicle; matching the visual features of the captured image to reference data associated with the location coordinates; and determining if the current location is the final destination. In some embodiments, the method further includes matching a verification code present within the captured image to a reference verification code, where the verification code is a two-dimensional visual code previously associated with the final destination.

Abstract: Provided is a navigation system for a leader vehicle leading follower vehicles, including: the leader vehicle, configured to transmit, real-time movement data to follower vehicles; and, the follower vehicles, each comprising: a signal receiver for receiving the data from the leader vehicle; sensors configured to detect at least one maneuverability condition; a memory; a vehicle maneuver controller; a distance sensor; and a processor configured to: determine a route for navigating the local follower vehicle from an initial location; determine a preferred range of distances from the vehicle in front of the respective follower vehicle that the respective follower vehicle should stay within; determine a set of active maneuvering instructions for the respective follower vehicle based on at least a portion of the data received from the guiding vehicle; determine a lag in control commands; and, execute the set of active maneuvering instructions in the respective follower vehicle.

Abstract: Aspects of the present invention are directed to system and methods for optimizing identification of locations within a search area using hash values. A hash value represents location information in a single dimension format. Computing points around some location includes calculating an identification boundary that surrounds the location of interest based on the location's hash value. The identification boundary is expanded until it exceeds a search area defined by the location and a distance. Points around the location can be identified based on having associated hash values that fall within the identification boundary. Hashing operations let a system reduce the geometric work (i.e. searching inside boundaries) and processing required, by computing straightforward operations on hash quantities (e.g. searching a linear range of geohashes), instead of, for example, point to point comparisons.

Abstract: An automatic brake subsystem (24) includes second accumulators (25F, 25R), a front second line (28) and a rear second line (29), second brake valves (30F, 30R), a first solenoid switching valve (32), first shuttle valves (33F, 33R), and a controller 37. A second solenoid switching valve (34F) and a pressure sensor (35F) are provided in the front second line (28), and a second solenoid switching valve (34R) and a pressure sensor (35R) are provided in the rear second line (29). In a case where it is determined that each of the second brake valve (30F, 30R) is not performing normally based upon a pressure of a hydraulic fluid detected by each of the pressure sensors (35F, 35R) and an operating signal supplied to the first solenoid switching valve (32) or each of the second brake valves (30F, 30R), a controller 37 performs control to switch each of the second solenoid switching valves (34F, 34R).

Abstract: A method for detecting icing conditions for an aircraft including a measurement of the parameters of embedded systems, with the exception of probes dedicated to the detection of ice, a transformation of the measurements of the symptomatic parameters to obtain P-tuples of values of explanatory variables which explain icing conditions, a classification of the measurements by classifiers on the basis of the P-tuples of values thus obtained, the classifiers having been previously trained in a supervised manner, each classifier providing a prediction of membership in a class of icing conditions, the predictions of the various classifiers being consolidated to provide a consolidated prediction of icing conditions.

Abstract: A method and apparatus for displaying road names and a storage medium, the method comprises: performing collision detecting on and loading planned road names according to planned road name data and priority levels of the planned road names included in a navigation route; and performing collision detecting on and loading annotations of other map contents except the navigation route in a navigation map. The method and apparatus for displaying road names and the storage medium are used to enable a user to view the planned road names of the navigation route on an overview page of the navigational route, thereby improving guidance of map display for navigation.