Abstract: A method includes: receiving, by a controller of a vehicle, operation data indicative of a duty cycle for the vehicle, wherein the duty cycle is a substantially repeatable set of vehicle or vehicle component operations for a particular event or for a predefined time period; identifying, by the controller, a desired vehicle duty cycle from a population of vehicle duty cycles based on the operation data indicative of the duty cycle for the vehicle and on a desired operating parameter of the vehicle; receiving, by the controller, a set of trim parameters that are electronic operational parameters associated with the desired vehicle duty cycle; and controlling, by the controller, one or more operating points of the vehicle based on the set of trim parameters.

Abstract: A method of facilitating first mile/last mile transfer of a vehicle includes analyzing a first route using a first trained machine learning model and a second route using a second trained machine learning model to determine, respectively, an incentive to a first user and a cost to a second user; causing a first message including the incentive to be displayed to the first user via an electronic device of the first user; and causing a second message including the cost to be displayed to the second user via an electronic device of the second user.

Abstract: This disclosure relates to a system configured to generate and provide timely vehicle event information for a fleet of vehicles including at least a first vehicle. Individual vehicles detect vehicle events and transmit related information to a remote computing server. The remote computing server determines whether the detected vehicles events are relevant to add to a set of vehicle events scenarios. For example, if a particular vehicle event is duplicative of a previous vehicle event, if may not need to be added. The newest vehicles events may be reported at certain intervals, in particular if they are indicative of a trend.

Abstract: Models can be generated of a vehicle's view of its environment and used to maneuver the vehicle. This view need not include what objects or features the vehicle is actually seeing, but rather those areas that the vehicle is able to observe using its sensors if the sensors were completely un-occluded. For example, for each of a plurality of sensors of the object detection component, a computer may generate an individual 3D model of that sensor's field of view. Weather information is received and used to adjust one or more of the models. After this adjusting, the models may be aggregated into a comprehensive 3D model. The comprehensive model may be combined with detailed map information indicating the probability of detecting objects at different locations. The model of the vehicle's environment may be computed based on the combined comprehensive 3D model and detailed map information.

Abstract: An electric aircraft with flight trajectory planning. The electric aircraft includes a sensor. The sensor is coupled to the electric aircraft. The sensor is configured to detect a plurality of weather measurements. The electric aircraft includes a processor. The processor is communicatively connected to the sensor. The processor is configured to receive, from the sensor, a weather measurement of the plurality of weather measurements. The processor is configured to receive, from a user, a destination datum and a desired altitude datum. The processor is configured to determine an optimal trajectory of the electric aircraft as a function of the destination datum, weather datum, and altitude datum.

Abstract: A baggage processing system includes a storage array having a plurality of cells, each cell being configured to contain a single baggage item which is associated with a flight. The baggage processing system further includes a loading conveyor that receives baggage items retrieved from the storage array. A control system prepares a sequenced list of baggage items and controls the retrieval of baggage items from the storage array based on the sequenced list, whereby the retrieved baggage items are placed on the loading conveyor in an order conforming to the sequenced list. The baggage processing system also includes a queue of carts, where each cart is positionable to receive baggage items in sequence from a loading point on the loading conveyor, for transporting the baggage items to an aircraft. The sequenced list of baggage items defines a sequence of loading baggage items from the carts to the aircraft.

Abstract: The disclosure provides an information processing apparatus, an information processing system, and an information processing method capable of allowing a user to approach a destination intuitively. An information processing apparatus according to the present technology includes a position-coordinate acquisition part, a direction acquisition part, a direction calculation part, and a haptic-feedback determining part. The position-coordinate acquisition part acquires a position coordinate of the information processing apparatus. The direction acquisition part acquires an apparatus direction that the information processing apparatus faces. The direction calculation part calculates a target direction being a direction of a target with respect to the information processing apparatus from a position coordinate of the target and the position coordinate of the information processing apparatus.

Abstract: A system for anchoring unmanned aerial vehicles to surfaces includes a landing pad configured to be installed on an agricultural machine, with the landing pad defining a landing surface. Furthermore, the system includes an unmanned aerial vehicle (UAV) configured to land on the landing surface and a top surface of a field across which the agricultural machine is traveling. The UAV, in turn, includes an anchoring device configured to engage soil within the field to anchor the UAV to the field when the UAV has landed on the top surface of the field. Additionally, the anchoring device is further configured to engage the landing pad to anchor the UAV to the landing surface when the UAV has landed on the landing pad.

Abstract: A system for producing a control signal of an electric vertical take-off and landing (eVTOL) aircraft includes a flight controller configured to obtain a requested aircraft force, generate an optimal command mix, wherein the optimal command mix includes a plurality of commands to a plurality of actuators as a function of the requested aircraft force, wherein generating further comprises receiving an ideal actuator model includes at least a performance parameter, producing a model datum as a function of the ideal actuator model, and generating the optimal command mix as a function of the request aircraft force and the model datum, and produce a control signal as a function of the optimal command mix.

Abstract: Aspects of the technology relate to exception handling for a vehicle. For instance, a current trajectory for the vehicle and sensor data corresponding to one or more objects may be received. Based on the received sensor data, projected trajectories of the one or more objects may be determined. Potential collisions with the one or more objects may be determined based on the projected trajectories and the current trajectory. One of the potential collisions that is earliest in time may be identified. Based on the one of the potential collisions, a safety-time-horizon (STH) may be identified. When a runtime exception occurs, before performing a precautionary maneuver to avoid a collision, waiting no longer than the STH for the runtime exception to resolve.

Abstract: A lifting gantry device for containers, in particular of the straddle carrier or sprinter carrier type, having four gantry supports spaced apart from one another and which by wheels of the lifting gantry device is floor-based and freely movable. A vehicle controller is provided such that the lifting gantry device can be controlled automatically. A sensor system is also provided and configured to determine sensor data on the surroundings of the lifting gantry device for automatically controlling the lifting gantry device. The sensor system comprises at least two, preferably four, sensor units for contactless object measurement and in particular object recognition, of which one sensor unit each is arranged on one of the four gantry supports and is configured to determine sensor data on the surroundings of the lifting gantry device for object measurement and in particular object recognition.

Abstract: Braking systems and methods for an electrical vertical takeoff and landing aircraft are provided. A braking system may contain a pilot control device, brakes, wheels, sensors, and a controller. Pilot controls the pilot control device to transmit information to the controller such that the aircraft will slow down.

Abstract: An aircraft engine nacelle comprising an icing protection system and an icing protection method for such an aircraft engine nacelle. The aircraft engine nacelle comprises an air inlet comprising a lip, a tubular air inlet piece and an icing protection system. The icing protection system comprises an icing prevention means powered continuously by a first electrical energy source and wholly or partly covering the lip, a de-icing means powered by a second electrical energy source covering the tubular air inlet piece and a controller configured to acquire a current total air temperature value, and control the second electrical energy source as a function of the current total air temperature value.

Abstract: An unmanned flight equipment according to an embodiment of the present invention includes: an aerial vehicle capable of flying in an unmanned manner; an abnormality recognition part-configured to recognize an abnormal situation in which a determination is made that it is difficult for the aerial vehicle to continue flight; and an alarm device held on the aerial vehicle and configured to be detached from the aerial vehicle and to warn neighborhood of abnormality when the abnormality recognition part recognizes the abnormal situation.

Abstract: Power steering device has steering mechanism 2, power cylinder 29 having a pair of hydraulic chambers 29a, 29b divided by piston 31 and providing steering force to steering mechanism, torque sensor 11 detecting steering torque Tr of steering mechanism, rotary valve 30 selectively supplying working fluid supplied from pump 9 to the pair of hydraulic chambers according to relative rotation between input and output shafts, hollow shaft motor 10 providing steering force to input shaft, control unit 13 in which microcomputer is mounted, and torque command signal operating section 61 provided in control unit and configured to calculate torque command signal Tm* for driving and controlling electric motor 10 on the basis of the steering torque Tr and vehicle speed Vs and when vehicle speed is a predetermined vehicle speed or greater, set torque command signal to 0. With this, physical size of power steering device can be decreased.

Abstract: In an aspect of the present disclosure is a computing device for predicting battery temperature in an electric aircraft, the computing device including a controller communicatively connected to the electric aircraft, the controller comprising: a battery model, the battery model configured to: receive a flight plan; instantiate a machine-learning model, wherein the machine-learning model is trained as a function of a training set correlating flight plan data to battery temperature labels.

Abstract: A simulating method for an electric vehicle (EV) includes: receiving a request from a driver of the EV for performing a simulation of a target vehicle on the EV; obtaining a plurality of configuration parameters for simulating behavior of the target vehicle on the EV, at least including information of the target vehicle and settings of the target vehicle for the driver; obtaining a plurality of vehicle parameters of the EV, at least including run-time parameters of the EV and driving conditions of the EV; and performing a simulating process to obtain one or more control parameters to control the EV to realize behaviors, actions, and/or characteristics of the target vehicle on the EV based on the plurality of vehicle parameters and the plurality of configuration parameters using a vehicle simulator model. The vehicle simulator model is a neural network.

Abstract: A driving support apparatus comprises a controller for performing collision avoidance braking control and lane deviation suppressing control. When a performing condition of the lane deviation suppressing control is satisfied at a timing of the collision avoidance braking control is about to be performed, the controller makes direction determination processing for determining whether or not the own vehicle travels to a direction toward which it will collide with a target object or to a direction toward which it will avoid colliding with the target object. In the direction determination processing, when it is determined the own vehicle travels to a collision direction, the controller stops the lane deviation suppressing control to perform the collision avoidance braking control, and when it is determined the own vehicle travels to a collision avoidance direction, the controller performs cooperative control for making the lane deviation suppressing control cooperate with the collision avoidance braking control.

Abstract: A computing system establishes a geofence associated with a particular service area, where the geofence corresponds to a set of rules for matching drivers with requesting users of the transport service. The system monitors a location of a computing device of a driver and detects when the driver enters the geofence. In response to the driver entering the geofence, the system places the driver into a queue for the particular service area. The system receives a transport request from a computing device of a requesting user, where the transport request is associated with the particular service area. The system arranges the transport service for the requesting user in accordance with the set of rules by (i) selecting a driver from the queue to service the transport request for the requesting user, and (ii) communicating a pickup location for the transport request to a computing device of the selected driver.

Abstract: A method for autonomous mower navigation includes receiving a return-to-zero encoded signal including a pseudo-random sequence, transforming the received signal to a non-return-to-zero representation, digitally sampling the non-return-to-zero signal representation in a time domain, filtering the sampled signal utilizing a reference data array based on the return-to-zero encoded signal to produce a filter output, and determining a location of the autonomous mower relative to a defined work area based on an evaluation of the filter output.