Abstract: The disclosure relates to a steering system and a method for controlling the same. According to an embodiment, a steering system comprises an electric power steering (EPS) steering motor connected to a first inverter and a second inverter, an additional motor connected to the second inverter and providing a steering-related additional function, a main electric control unit (ECU) including the first inverter and controlling the EPS steering motor through the first inverter, and a sub ECU including the second inverter and controlling at least one of the EPS steering motor or the additional motor based on at least one of main ECU state information or vehicle driving state information.

Abstract: In a driving control device that controls a driving system for a vehicle, a voltage detection unit acquires a voltage value for each of cells of the battery as a cell voltage value, an abnormality determination unit determines an abnormality in voltage detection system for each of the cells based on the cell voltage value, and a rank setting unit sets ranks of the plurality of cells based on a parameter involved in failure in the battery. A fail-safe running unit determines a mode of fail-safe running of the vehicle based on the rank of the cell to be detected by the voltage detection system determined to have an abnormality, and a rotating electric machine control unit controls the rotating electric machine based on the mode of fail-safe running of the vehicle determined by the fail-safe running unit.

Abstract: A system for detecting material accumulation relative to rotating ground-engaging tools includes an agricultural implement having a frame and first and second ground-engaging tools supported relative to the frame, with the first ground-engaging tool corresponding to a different tool type than the second ground-engaging tool. The system also includes first and second speed sensor configured to provide data indicative of the rotational speeds of the first and second ground-engaging tools, respectively. In addition, the system includes a computing system communicatively coupled to the first and second speed sensors.

Abstract: A method for detecting a rotating stall includes: determining a level of variation of a static pressure in a combustion chamber of the turbojet engine around an average value of this static pressure; comparing the level of variation of the static pressure relative to a first threshold; comparing a temperature measured at the outlet of a turbine of the turbojet engine relative to a second threshold; and if the level of variation of the static pressure is greater than the first threshold and the temperature at the outlet of the turbine is greater than the second threshold, detecting a presence of a rotating stall.

Abstract: Systems and methods for evaluating and deploying fleets of autonomous in operational domains are described. A computing system may obtain data indicative of one or more capabilities of at least one autonomous vehicle, data indicative of vehicle service dynamics in an operational domain over a period of time, and determining a plurality of resource performance parameters respectively for a plurality of autonomous vehicle fleets associated with potential deployment in the operational domain. Each autonomous vehicle fleet can be associated with a different number of autonomous vehicles The resource performance parameter for each autonomous vehicle fleet can be based at least in part on the one or more capabilities of the at least one autonomous vehicle and the vehicle service dynamics in the operational domain. The computing system can initiate an action associated with the operational domain based at least in part on the plurality of resource performance parameters.

Abstract: Provided is a hydraulic excavator including a controller that can control a work device by utilizing an excavation work control for causing a claw tip of a bucket to move along a predetermined target surface and a leveling work control for causing the bucket to move along the target surface while maintaining the posture of the bucket with respect to the target surface, in which: the controller, based on posture data and size data on a work device and position data on the target surface, calculates an arm tip difference Dva that is the distance from the tip of an arm to the target surface; and the controller executes the leveling work control in a case of the calculated arm tip difference being equal to or less than a predetermined threshold dv1, there being no input of a bucket operation to an operation lever, and there being an input of an arm operation to the operation lever, and otherwise executes the excavation work control.

Abstract: An intelligent system for controlling driving of an aircraft tow tractor by means of combination of voice and vision includes an audio transmission line, a voice recognition system, a visual recognition system, and a vehicle-mounted motion controller. According to the intelligent system, visual recognition is performed based on a belly-mounted anti-collision light on an aircraft, a taxi light, and the visual recognition system on an aircraft tow tractor, and the aircraft tow tractor is intelligently controlled by means of combination of voice recognition and the visual recognition; furthermore, the aircraft tow tractor is intelligently controlled by voices of flight crew via the audio transmission line, safety in a towing process is guaranteed by the visual recognition, and each step in the towing process is performed by means of a cross validation based on the voice recognition and the visual recognition.

Abstract: A driving assistance system includes a front camera module (FCM). The system, responsive to processing captured image data from the FCM, generates FCM control signals. The system includes a plurality of vehicle sensors capturing sensor data and an advanced driving-assistance system (ADAS) controller. The ADAS controller, responsive to processing the sensor data, generates ADAS control signals. The ADAS controller generates an ADAS status signal indicating a reliability of the generated ADAS control signals. With the ADAS status signal indicating the reliability of the generated ADAS control signals is at or above a threshold ADAS reliability level, the system controls the vehicle using the ADAS control signal and, responsive to determining that the ADAS status signal indicates that the reliability of the generated ADAS control signals is below the threshold, switches from controlling the vehicle based on the ADAS control signals to controlling the vehicle based on the FCM control signals.

Abstract: A method for sensor diagnostics in a seat suspension system includes: generating, by a rotational position sensor, based on a rotational position of an output shaft coupled to a suspension mechanism to move a vehicle seat relative to a vehicle body, an output signal including a sine output and a cosine output; determining, based on the sine output and the cosine output, a diagnostic indicator value; and determining, based on the diagnostic indicator value, an accuracy of the output signal to represent the rotational position of the output shaft. A second method determines accuracy of an output signal to represent a rotational position of the output shaft in a seat suspension system using the output signal and a motor position signal representing a rotational position of a motor shaft coupled to the output shaft such that rotation of the motor shaft causes rotation of the output shaft.

Abstract: A system for providing a flight planning tool is disclosed. The system may include at least one memory device for storing flight information and one or more hardware processors. The one or more hardware processors may be configured to provide an Application Program Interface (API) for facilitating communication between the system and at least one of a client device and one or more third-party devices, receive, via the API, a request including first information related to a flight, collect, via the API and based on the first information, second information from one or more third-party devices, generate flight trip data based on the first and second information, wherein the flight trip data includes information and graphics associated with the flight, and provide, via the API, one or more user interfaces to the client device for communicating the flight trip data.

Abstract: The present disclosure provides a left and right wheel determination method, a wheel pressure monitoring chip and system, and related apparatuses. The left and right wheel determination method includes: obtaining a time duration for a wheel to rotate for a predetermined number of revolutions after the wheel being detected as rotating; sampling centrifugal acceleration and tangential acceleration of the wheel within the time duration; determining an overrun-lag relationship between the centrifugal acceleration and the tangential acceleration of the wheel based on a serial number of a sampling time-point corresponding to the centrifugal acceleration and a serial number of a sampling time-point corresponding to the tangential acceleration; and determining the wheel to be of a left wheel or a right wheel based on the overrun-lag relationship between the centrifugal acceleration and the tangential acceleration of the wheel.

Abstract: A parking brake fail safety control system and method for a vehicle having an electric-axle, may enable safe parking braking on a level ground, a slope, etc. By controlling the torque from a first motor configured for a rear wheel-first electric-axle and the torque from a second motor configured for a rear wheel-second electric-axle to have the same magnitude in opposite directions and by increasing/decreasing the torque from the first motor and the torque from the second motor, depending on a change of wheel speed when a parking brake fails.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive radar data from a radar, the radar data including radar pixels having respective measured depths; receive camera data from a camera, the camera data including an image frame including camera pixels; map the radar pixels to the image frame; generate respective regions of the image frame surrounding the respective radar pixels; for each region, determine confidence scores for the respective camera pixels in that region; output a depth map of projected depths for the respective camera pixels based on the confidence scores; and operate a vehicle including the radar and the camera based on the depth map. The confidence scores indicate confidence in applying the measured depth of the radar pixel for that region to the respective camera pixels.

Abstract: A lighting device for a motor vehicle includes a housing having a front lighting surface, and a substantially planar plate and at least one lighting module mounted on the plate. The plate has a general plane of extension that is horizontal when the housing is mounted in the vehicle, and has a surface referred to as a lower surface and a surface referred to as an upper surface. The plate includes a first control system which includes a first male element and is arranged to cause translation of the first male element in an axis parallel to the plate, the plate being provided with a first recess receiving the first male element. A second control system that includes a second male element and is arranged to cause translation of the second male element in an axis perpendicular to the plate, the plate being provided with a second recess on its upper or lower surface that receives the second male element. The housing thus takes up less space above the modules, which can easily be raised.

Abstract: Discussed herein are devices, systems, and methods for improved trajectory planning. A method can include providing two of (i) a first value indicating a change in velocity to alter an orbit of a first object to a transfer orbit; (ii) a second value indicating a range between the first object and a second object; or (iii) a third value indicating an altitude of the first object relative to a celestial body around which the first and second objects are orbiting as input to a machine learning (ML) model, receiving, from the ML model, a holdout value, the holdout value a prediction of the value, of the first value, the second value, and the third value, that was not provided to the ML model, and providing the holdout value to an orbital planner.

Abstract: The method can include optionally training a transportation modality classification model; determining a transportation modality of a trip; and optionally triggering an action based on the transportation modality. However, the method can additionally or alternatively include any other suitable elements. The method functions to facilitate a classification of a transportation modality for trips based on location data (e.g., collected at a mobile device). Additionally or alternatively, the method can function to facilitate content provisions based on a trip classification.

Abstract: A mobile object monitoring system including a terminal unit installed in a vehicle and a monitoring unit configured to monitor an unknown mobile object around the vehicle. The terminal unit includes: an information acquisition component that acquires unknown mobile object information including information on presence or absence of an unknown mobile object; a determination component that determines presence or absence of an unknown mobile object regarding a blind spot; a time-of-absence information generation component that generates a time-of-absence information set concerning an unknown mobile object that includes absence information of an unknown mobile object in the blind spot and time information on a time of determination; and a communication component that transmits the time-of-absence information set.

Abstract: Pallet detection device that acquires point cloud data indicating a point cloud measured by a two-dimensional distance measurement device on a depth map; detects a straight line corresponding to a front surface of a pallet based on the point cloud in a region presumed to include the front surface of the pallet in the point cloud data; detects a line segment indicating the front surface of the pallet based on the straight line; acquires position and orientation of the pallet based on the line segment. Acquires one or more straight line candidates and assigns for each of the one or more straight line candidates a score to the point cloud and selects the straight line from the one or more straight line candidates based on a score accumulated value obtained by accumulating the score for the point cloud in the region presumed to include the front surface of the pallet.

Abstract: A computer implemented method for determining weights for an attention based trajectory prediction comprises the following steps carried out by computer hardware components: receiving a sequence of a plurality of captures taken by a sensor; determining an unnormalized weight for a first capture of the sequence based on the first capture of the sequence; and determining a normalized weight for the first capture of the sequence based on the unnormalized weight for the first capture of the sequence and a normalized weight for a second capture of the sequence.

Abstract: Systems and methods for a vehicle are provided. In one embodiment, a method includes: receiving image data defining a plurality of images associated with an environment of the vehicle; receiving vehicle data indicating a velocity of the vehicle, wherein the vehicle data is associated with the image data; determining, by a processor, feature points within at least one image based on the vehicle data and a three dimensional projection method; selecting, by the processor, a subset of the feature points as ground points; determining, by the processor, a ground plane based on the subset of feature points; determining, by the processor, a ground normal vector from the ground plane; determining, by the processor, a camera to ground alignment value based on the ground normal vector; and generating, by the processor, second image data based on the camera to ground alignment value.