Abstract: Computer-implemented methods for validating a real-time condition of a landing field using aircraft data. One method comprises identifying a plurality of segments of the runway based on a configurable parameter; receiving input data of at least one of a reported runway condition code and a reported braking action of a recently landed aircraft; receiving actual data of an actual runway deceleration profile from the recently landed aircraft for each identified segment of the runway; creating expected data of an expected runway deceleration profile based on the received input data and the received actual data; comparing the received actual data with the created expected data to validate and/or reassess the input data; and transmitting the validated and/or reassessed data to at least one of other approaching aircraft and an airport controller.

Abstract: It is estimated whether or not each of landmarks is an object to be noted for travel assist control by using an estimation line EL set in the reference frame. The estimation line EL is set to be substantially parallel to a borderline BL. The borderline BL is a line a line which separates a drivable area and an undrivable area of a vehicle. It is estimated that the landmark located on a center line CL side is the object to be noted for travel assist control. It is estimated that the landmark located on a borderline BL side is not the object to be noted for travel assist control.

Abstract: According to an embodiment, an information processing device includes a memory; and one or more processors coupled to the memory. The one or more processors are configured to: arrange a node in a first region not interfering with an object on a scheduled traveling route; arrange a node in a second region around an interference region interfering with the object; and search for a route going through a plurality of nodes and having a moving cost from a first point to a second point on the scheduled traveling route equal to or smaller than a threshold.

Abstract: Techniques are disclosed for filtering point cloud data associated with particulate matter (e.g., gas, exhaust, fog, etc.) which do not impact driving from data used to plan a trajectory and/or a route of a robotic platform. The filtering may be based on determining that a set of points associated with a point cloud represents a navigable space for the robotic platform. The point cloud data may be filtered based on a determination that one or more safety conditions are satisfied. Semantic segmentation may be performed on an image to determine pixel classification probability distributions associated with pixels of the image. Data associated with the set of points may be projected onto the image to identify corresponding pixels. Confidence scores associated with pixel classification probability distributions for the identified pixels may be queried. A classification probability distribution for the set of points may be determined based at least in part on the queried confidence scores.

Abstract: A precision landing system including an unmanned aerial vehicle (UAV) and a beacon is provided. A processor of the UAV controls a flight system of the UAV to fly the UAV. The processor detects, via a sensor of the UAV, a signal emitted by a beacon. The processor controls the flight system of the UAV to land on or near the beacon. The processor also energizes one or more electromagnets on a cradle of the UAV to retrieve the beacon.

Abstract: A method for wrong-way driver detection, including a step of reading map data mapping road segments of a road network negotiable by a vehicle, a step of determining a plurality of instantaneous particles using a measured instantaneous position of the vehicle, one particle representing an assumed position of the vehicle and a weighting assigned to the assumed position, a step of reading in a plurality of previously filtered particles representing particles filtered in a preceding step of filtering using a particle filter, a step of determining a set of plausible road segments, using the plurality of instantaneous particles and the plurality of previously filtered particles, and a step of filtering the plurality of instantaneous particles based on the set of plausible road segments, using the particle filter, to determine a plurality of filtered particles.

Abstract: Methods and systems are provided for reducing release of undesired evaporative emissions to atmosphere for a hybrid vehicle. In one example, a method comprises locking a transmission of the vehicle in park until a request to override the locking is received at a controller of the vehicle, and conducting one or more routines related to reducing release of undesired evaporative emissions to atmosphere, where the one or more diagnostic routines rely on a vacuum derived from an engine of the vehicle combusting air and fuel while the transmission is locked in park. In this way, completion rates for conducting the one or more routines may be improved, and issues related to the release of undesired evaporative emissions to atmosphere may be reduced or avoided.

Abstract: A method includes determining a first speed value based on a first signal from a first data source. The method also includes determining a second speed value based on a second signal from a second data source. The method further includes determining a first likelihood of icing value based on a third signal from a third data source. The method also includes determining a second likelihood of icing value based on a fourth signal from a fourth data source. The method further includes performing a first comparison between the first speed value and the second speed value and performing a second comparison between the first likelihood of icing value and the second likelihood of icing value. The method also includes generating sensor reliability data based on the first comparison and the second comparison and displaying situational awareness data based on the sensor reliability data.

Abstract: A motor controller of an unmanned aerial vehicle (UAV) is optimized to improve operation of the UAV. The motor control optimizations include controlling a motor of a UAV to reduce an operating temperature of the UAV, reducing an amount of latency or jitter resulting from motor operation, and applying a smoothing filter for motor operation. For example, controlling a motor of a UAV to reduce an operating temperature of the UAV can include using a temperature model for the unmanned aerial vehicle or an operating temperature measurement to determine a current operating temperature and comparing that current operating temperature to a threshold. If the threshold is exceeded, settings of the motor are adjusted to cause the motor to operate in a manner that reduces the current operating temperature.

Abstract: Disclosed herein is a lane change assistance device, including: a change time setting unit configured to set a change time required for the lane change; a yaw angle acquisition unit configured to acquire a yaw angle of an own vehicle before starting the lane change; and a steering control unit configured to control a steering unit of the own vehicle to perform the lane change in the change time set by the change time setting unit, wherein when the yaw angle acquired by the yaw angle acquisition unit is a yaw angle in a state where the own vehicle approaches a target lane designated during the lane change, the change time setting unit sets the change time shorter than in other states, and when the yaw angle acquired by the yaw angle acquisition unit is a yaw angle in a state where the own vehicle stays away from the target lane, the change time setting unit sets the change time longer than in the other states.

Abstract: A flying vehicle navigation system includes a flying vehicle (2) and a control system (4) that controls the flight of the flying vehicle. The flying vehicle is configured to be switchable to autonomous driving when the flying vehicle is located in a first takeoff and landing section (22) set on the ground. After the flying vehicle is switched to autonomous driving, the control system guides the flying vehicle such that the flying vehicle takes off from a first takeoff and landing section, flies in a three-dimensional road as an exclusive track set in the specific region of the air, and lands on a second takeoff and landing section set on the ground. After the flying vehicle is switched to autonomous driving, operations from takeoff from the first takeoff and landing section to landing on the second takeoff and landing section are automatically carried out under control by the control system.

Abstract: A control method of a rear wheel steering system prevents a sudden change in a rear wheel steering control amount when an error occurs in a wheel speed sensor. The control method detects an error in wheel speed sensors based on output values of the wheel speed sensors. A vehicle speed is estimated by using output values of remaining normal wheel speed sensors except for an output value of an abnormal wheel speed sensor where an error is detected, when an error in the wheel speed sensor is detected. Rear wheels are steered and controlled based on the estimated vehicle speed.

Abstract: Herein is disclosed an unmanned aerial vehicle light flash comprising a support structure; a camera coupled to the support structure and configured to take a photograph; one or more processors coupled to the support structure and configured to control a predetermined flight plan of the unmanned aerial vehicle, control the camera, generate or process a synchronization signal to synchronize a light flash to be generated by a further unmanned aerial vehicle with a taking of the photograph by the camera; a transceiver coupled to the support structure and configured to transmit or receive the synchronization signal to or from the further unmanned aerial vehicle.

Abstract: Devices, systems, and methodologies for providing a comfort system of a transportation vehicle include capturing and assessing movement data of a user. The movement data can include movement data captured upon the user's approach to the transportation vehicle.

Abstract: In an information transfer device (5) installed in a vehicle (3), the vehicle carrying the information transfer device (5) is referred to as a subject vehicle, and an information acquisition unit (9) acquires through communications with another vehicle (a) information indicating whether the other vehicle is being automatically driven, (b) information indicating functions of the other vehicle related to automatic driving, and (c) information indicating a schedule of the other vehicle related to automatic driving. An information processing unit (11) provides the information acquired by the information acquisition unit to the driver of the subject vehicle (3) or outputs the same to a driving control device (7) of the subject vehicle (3).

Abstract: A method and device for determining a coefficient of friction of a passable supporting surface with the aid of an ego vehicle, including a step of acquiring first data values, which represent a moisture level in the surrounding area of the ego vehicle, a step of checking the plausibility of the acquired, first data values by comparison with at least one second data value, and a step of determining third data values, which represent the coefficient of friction of the passable supporting surface; the determination taking place as a function of the plausibility check of the first data values, using the at least one second data value.

Abstract: A vehicle travel control system installed on a vehicle includes: a recognition sensor configured to recognize a situation around the vehicle; a sensor cleaning device configured to clean the recognition sensor; and a control device configured to execute vehicle travel control based on result of recognition by the recognition sensor, and to actuate the sensor cleaning device to execute sensor cleaning processing that cleans the recognition sensor. The control device permits execution of the sensor cleaning processing in a situation where decrease in recognition performance has a small influence on the vehicle travel control. For example, when a surrounding vehicle recognized by a first recognition sensor is also recognized by a second recognition sensor, the control device permits execution of the sensor cleaning processing that cleans the first recognition sensor.

Abstract: Embodiments of the present disclosure disclose an aerial vehicle landing method, a ground control system, and a flight control system. The aerial vehicle landing method includes: selecting, when an aerial vehicle needs to make a diversion, an available alternative landing area according to at least a flight parameter of the aerial vehicle; determining the available alternative landing area as a target waypoint, and planning a new airway according to the target waypoint; and controlling, according to the new airway, the aerial vehicle to fly to the target waypoint. According to the foregoing manners, the embodiments of the present disclosure can resolve problems of unpredictable casualties and property losses that may be caused because the aerial vehicle has an emergency and is landed in a non-predetermined area.

Abstract: Systems and methods for autonomous vehicle localization are provided. In one example embodiment, a computer-implemented method includes obtaining, by a computing system that includes one or more computing devices onboard an autonomous vehicle, sensor data indicative of one or more geographic cues within the surrounding environment of the autonomous vehicle. The method includes obtaining, by the computing system, sparse geographic data associated with the surrounding environment of the autonomous vehicle. The sparse geographic data is indicative of the one or more geographic cues. The method includes determining, by the computing system, a location of the autonomous vehicle within the surrounding environment based at least in part on the sensor data indicative of the one or more geographic cues and the sparse geographic data. The method includes outputting, by the computing system, data indicative of the location of the autonomous vehicle within the surrounding environment.

Abstract: The lane change intention discrimination portion executes intention discrimination processing when it receives from the vehicle control ECU an instruction for controlling the blinker. The intention discrimination processing is processing to discriminate what type of pattern for the lane change operation was demanded in the instruction for controlling the blinker. The start and exit timing setting portion executes timing setting processing based on a discrimination result of the intention discrimination processing. The timing setting processing is processing to set a start timing and an exit timing of the lighting operation of the blinker.