Abstract: A computing device for use in detecting maintenance events and maintenance intervals is provided. The computing device is configured to receive aircraft usage data for at least one carrier, identify at least one potential maintenance event in the usage data, identify at least one actual maintenance event in the usage data at least by comparing the usage data for a first aircraft of the at least one carrier to a second aircraft of the at least one carrier during each potential maintenance event, determine an indicator used by each carrier for scheduling maintenance events, determine a maintenance interval for each carrier for an aircraft model associated with at least the first aircraft.

Abstract: An occupant support includes a seat coupled to a seat base. The seat includes a seat bottom and a seat back. The seat back is coupled to the seat bottom to extend upwardly away from the seat bottom. Motion-sickness mitigation means facilitates relative movement between a support surface of the seat and the seat base.

Abstract: A driving support ECU detects a shallow pressing operation monitoring signal of the turn signal lever is turned off (S14: Yes). When a timer value Tx representing an ON duration time period in which the shallow pressing operation monitoring signal is continued to be turned on reaches an assist request confirmation time period Tref (S19: Yes) and an LCA start condition is established (S20: Yes) after the detection of the shallow pressing operation monitoring signal, the driving support ECU starts LCA. The driving support ECU does not determines, until the LCA is completed, whether or not the shallow pressing operation monitoring signal is turned off. The driving support ECU restarts processes from S11 after the LCA is completed. Therefore, even if the shallow pressing operation is continued to be performed, the LCA is not executed further.

Abstract: Systems and methods for providing autonomous vehicle assistance are disclosed. In one embodiment, a method is disclosed comprising recording an image of a scene surrounding an autonomous vehicle; classifying the image using a machine learning system, the classifying comprising identifying whether the image includes a danger; determining whether the autonomous vehicle is able to respond to the danger in response to identifying that the image includes the danger; and executing one or more security maneuvers, the security maneuvers manipulating the operation of the autonomous vehicle in response to the danger.

Abstract: The aspects of the present disclosure provide an autonomous vehicle interface for a vehicle and a method of enabling and employing an autonomous vehicle interface for a vehicle. The autonomous vehicle interface may be configured to seamlessly transition driving modes or the vehicle's mode of operation from user controlled to an autonomous controlled driving without the user physically activating the autonomous controlled driving. The autonomous vehicle interface may also be configured to consider active components and environmental conditions employed by the user in activating the autonomous control. The autonomous vehicle interface may further be configured to consider the user's operational state and/or the user's attentiveness to activate the autonomous vehicle mode.

Abstract: Aerial vehicles may include propulsion units having motors with drive shafts that may be aligned at a variety of orientations, propellers with variable pitch blades, and common operators for aligning the drive shafts at one or more orientations and for varying the pitch angles of the blades. The common operators may include plate elements to which a propeller hub is rotatably joined, and which may be supported by one or more linear actuators that may extend or retract to vary both the orientations of the drive shafts and the pitch angles of the blades. Operating the motors and propellers at varying speeds, gimbal angles or pitch angles enables the motors to generate forces in any number of directions and at any magnitudes. Attributes of the propulsion units may be selected in order to shape or control the noise generated thereby.

Abstract: In one embodiment, a method includes receiving flight path data regarding the presence of an unmanned aerial vehicle (UAV) at a location at a future time, detecting the presence of the UAV at the location at the future time, determining radio identity data of the UAV using a radio mode of identification, determining optical identity data of the UAV using an optical mode of identification, and certifying the UAV based on a comparison of the radio identity data and the optical identity data to the flight path data.

Abstract: Example implementations may relate to selection between a first mode and a second mode. The first mode may involve (i) directing an aerial vehicle (e.g., in an aerial network including a plurality of aerial vehicles) to navigate to each of a plurality of altitudes and (ii) determining respective wind-related data at each respective altitude. Whereas, the second mode may involve (i) selecting at least one altitude based on the determined wind-related data and (ii) directing the aerial vehicle to reposition to the at least one selected altitude. As such, a control system may determine flight data for the aerial vehicle. Based on the flight data, the control system may make a selection between the first mode and the second mode. And based on the selection, the control system may then operate the aerial vehicle according to the first mode or may operate the aerial vehicle according to the second mode.

Abstract: A smoke detection system for an interior of a vehicle is provided. The smoke detection system includes a detection module and a reporting module. The detection module, while the vehicle is being used as part of a car sharing or ride sharing service: receives a sensor signal from a smoke detector; compares data included in the sensor signal to smoke characteristic or smoke pattern data; based on the comparison, determines whether an occupant of the vehicle is smoking; and generates an alert signal if the occupant is smoking. The reporting module at least one of: based on the alert signal, visually or audibly provides a warning to the occupant to stop smoking; transmits the alert signal to a mobile device of the occupant to indicate that a smoking event has been detected; or transmits the alert signal to a network device of a service provider to report the smoking event.

Abstract: An approach for presenting a comparison of progress information associated with transport modes, routes, or a combination thereof is described. A transport comparison platform determines progress information for at least one device associated with at least one mode of transport, at least one route, or a combination thereof. The transport comparison platform determines other progress information associated with at least another mode of transport, at least another route, or a combination thereof. The transport comparison platform causes, at least in part, a presentation of a comparison of the progress information against the other progress information.

Abstract: According to an aspect, a system in an aircraft includes a vehicle management system (VMS) and a load control system (LCS). The LCS includes an LCS processor operable to receive and transmit a plurality of data and load management commands to one or more of: the VMS and a load control interface. The LCS processor is further operable to interact with one or more of: the VMS, one or more LCS sensors, and a load capturing interface of the aircraft to execute the load management commands as a sequence of one or more load management subcommands. The load capturing interface is operable to capture and release an external load relative to the aircraft using a load capture device. The LCS processor is also operable to report a status of execution of the load management commands to the VMS and the load control interface.

Abstract: Provided are a vehicle body behavior control device which can reduce unstable behavior of a vehicle body and a method of controlling behavior of a vehicle body which can reduce unstable behavior of the vehicle body. A vehicle body behavior control device incorporated into a vehicle body having a plurality of wheels includes: a behavior control mechanism which controls behavior of the vehicle body; and a control part which controls an operation of the behavior control mechanism based on an axle load applied to the wheel calculated using a gradient value ? of a road surface.

Abstract: Methods and apparatus are described for drone collision avoidance that includes extracting first feature information from an image. The image is captured from a first camera oriented in a direction. Second feature information is received from an external source. The second feature information is extracted from a second image of the environment captured by a second camera oriented in the direction. The first feature information and the second feature information are matched. A second local frame of reference of the second feature information is transformed to a first local frame of reference of the first feature information to determine a location of the external source. If a collision with the external source will occur is determined based on the location of the external source and a current flight trajectory.

Abstract: A method of operation of a navigation system comprising: determining a geographic limitation with a control unit based on the geographic limitation associated with a traveler information included in a traveler restriction information; generating a provisional route based on a path between a start point and a destination point; determining a provisional POI based on a POI of the provisional route; determining a POI restriction based on the POI restriction associated with the provisional POI included in a rule information; determining a navigation restriction based on matching the geographic limitation and the POI restriction for presenting on a device.

Abstract: A vehicle mounted apparatus includes a first acquisition portion, a second acquisition portion, a comparison portion, and a control portion. The first acquisition portion acquires first vehicle information of different vehicles. The second acquisition portion acquires second vehicle information of different vehicles. The comparison portion compares a position of a closest different vehicle recognized based on the first vehicle information with a position of a closest different vehicle recognized based on the second vehicle information. The control portion employs both of the vehicle information acquired based on detection signals from the vehicle detection sensor and the vehicle information acquired based on the detection signals from the vehicle-to-vehicle communication in a combined manner when the position of the closest different vehicle recognized based on the first vehicle information matches with the position of the closest different vehicle recognized based on the second vehicle information.

Abstract: A method for identifying missing map features in an electronic map, involving receiving telemetry probes indicating a geographic location of a mobile computing device, and identifying a subset of telemetry probes corresponding to an existing map feature. The identified subset is then removed from an aggregation of telemetry probes, and the remaining telemetry probes used to generate a density map and identify missing clusters of telemetry probes. A geometry of the missing clusters is determined, and a missing map feature defined from the geometry of the missing cluster. An electronic map may be updated with the missing map feature.

Abstract: A system including a processor and memory may provide for automatically activating or deactivating a feature of a fleet vehicle. For example, one or more fleet vehicles may include one or more of a global-positioning system, a speed governor, electronically-controlled brakes, an electronically-controlled accelerator, a speed limiter, or an on-board computer with a processor and memory. One or more features may be activated by a local or remote computing device or system. For example, a system may determine one or more recommended routes between two or more locations. The system may track a fleet vehicle's progress along a route, and activate a feature of the fleet vehicle based on the fleet vehicle following or not following the recommended route. For example, the system may cause activation of a speed limiter on the fleet vehicle, disable the fleet vehicle, and/or activate or deactivate autonomous features of the fleet vehicle.

Abstract: A method for ascertaining data of a traffic situation with a first vehicle and at least one second vehicle trailing the first vehicle, the method including a) ascertaining at least one defined parameter of the first vehicle, b) ascertaining a traffic situation in front of the first vehicle by the first vehicle and/or by the second vehicle, c) evaluating the information ascertained in steps a) and b) in a defined manner, and providing the information evaluated in step c) to the second vehicle at least at the start of a passing maneuver of the first vehicle conducted by the second vehicle.

Abstract: A charging system by autonomous guide of drone includes a drone for being autonomously guided to a charging station on the basis of location and altitude coordinates for charging and for transmitting a charged information to a control station when the charging is completed; a charging station for recognizing the approach of the drone within a chargeable range and for controlling the guide flight of the drone and transmitting a charged information to the control station when the charging is completed; and a control station for detecting the state of charge of the drone in real time and for transmitting a location coordinate and altitude coordinate of the charging station to the drone for guiding flight to the charging station.

Abstract: The present disclosure provides a vehicle interface for an autonomous vehicle. In particular, the systems and methods of the present disclosure can, responsive to receiving, from an autonomy computing system of an autonomous vehicle, a time-based trajectory for the autonomous vehicle, verify that execution of the time-based trajectory is within parameters of the autonomous vehicle. Responsive to verifying that execution of the time-based trajectory is within the parameters of the autonomous vehicle, the time-based trajectory can be converted into a spatial path for the autonomous vehicle, and one or more controls of the autonomous vehicle can be interfaced with such that the autonomous vehicle tracks the spatial path.