Abstract: A method for identifying the contour of a vehicle based on measurement data from an environment sensor system is disclosed. The measurement data includes a set of spatial points of an object detected by the environment sensor system. The method includes: producing an envelope in the form of a polygonal chain around the object based on the set of spatial points; reducing the set of spatial points; removing spatial points from the polygonal chain that are irrelevant to identifying the contour of the vehicle and determining spatial points of the polygonal chain that are relevant to identifying the contour of the vehicle; classifying one or more edges as belonging to a front and a side of the vehicle on the basis of the reduced set of spatial points.

Abstract: A vehicle health monitoring system monitors the health of components for ground vehicles and accounts for the impact of changing engine RPM, a multi ratio gearbox, and the variable ratio encountered in vehicles having a differential. The vehicle health monitoring system may incorporate regime recognition that determines the vehicle state, e.g., the engine RPM, transmission gear ratio, whether its accelerating (or turning), so that a decision can be made whether the vehicle is in an appropriate regime for data acquisition for a monitored vehicle of the component, and if so, what type of configuration to use for analyzing the component for determining a condition indicator for that component. The configuration describes the ratio from a given tachometer to a shaft under analysis, and which, if any, gears/bearings are associated with the shaft.

Abstract: Systems and methods for multiple inertial measurement unit sensor fusion using machine learning are provided herein. In certain embodiments, a system includes inertial sensors that produce inertial measurements, a memory unit that stores a fusion model produced by at least one machine learning algorithm, and a processor that receives inertial measurements, where the processor applies the fusion model to the inertial measurements. The fusion model directs the processor to extract features from the inertial measurements, and to select inertial measurements based on a sensor in the plurality of inertial sensors that produced the inertial measurements. Also, the fusion model directs the processor to apply weights to the selected inertial measurements based on the extracted features, to apply compensation coefficients to the selected inertial measurements, and to fuse the selected inertial measurements into an inertial navigation solution.

Abstract: A vehicle comprises an autonomous driving system and a vehicle platform that controls the vehicle in response to a command received from the autonomous driving system. In the present vehicle, when the autonomous driving system issues a first command to request the vehicle platform to provide deceleration to stop the vehicle and a first signal indicates 0 km/h or a prescribed velocity or less, the autonomous driving system issues a second command to request the vehicle platform to maintain stationary. And after brake hold control is finished, a second signal indicates standstill. Until the second signal indicates standstill, the first command continues to request the vehicle platform to provide deceleration.

Abstract: A vehicle control device of the embodiment includes a recognizer configured to recognize a surrounding situation of a vehicle and a driving controller configured to control one or both of steering and a speed of the vehicle on the basis of the surrounding situation recognized by the recognizer, in which the driving controller causes the vehicle to travel by executing any one of a plurality of driving modes including at least a first driving mode and a second driving mode in which a task imposed on an occupant of the vehicle is heavier than in the first driving mode, and switches from the first driving mode to the second driving mode when a first section in which the number of lanes of a road on which the vehicle travels is different from the current number of lanes and a second section in which a road having at least three lanes branches are present within a predetermined distance in a traveling direction of the vehicle while the first driving mode is executed.

Abstract: A method of controlling availability of autonomy functions of a vehicle includes determining one or more uncertainty levels, each corresponding to a driving data stream including driving data, wherein the uncertainty levels correspond to a probability of a collision or driving off the roadway. The method further includes generating a total uncertainty level based on the one or more uncertainty levels and disabling a first autonomy function based on availability criteria of the first autonomy function. The availability criteria define a first threshold of the total uncertainty level. The method further includes providing a second autonomy function based on the second autonomy function's availability criteria that include a total uncertainty threshold higher than the first threshold.

Abstract: A landing zone landing assistance system for a rotary wing aircraft, the system includes a computer, an HMI for interacting with the pilot of the aircraft, an optical assembly provided with at least one optical sensor, a radar assembly provided with at least one radar detector and an inertial unit, wherein the computer is configured to implement the following steps: a first step (Step1) consisting in determining an optical image of the possible landing zone; a second step (Step2) consisting in determining the relative position of the landing zone with respect to said system in the terrestrial reference frame; a third step (Step3) consisting in determining a landing zone approach path; and a fourth step (Step4) consisting in supplying to the HMI a deviation between the position of the system and the approach path.

Abstract: A vehicle control apparatus includes a storage and a processor. The storage holds a first resonance map. The processor calculates a first torque command value that indicates a value of torque to be outputted by a first driving source. The first resonance map includes, as one or more first resonance points, one or more operating points at which resonance occurs in an operating region of the first driving source under a square wave control. The processor decreases or increases the first torque command value to avoid the one or more first resonance points on the condition that a predicted route of transition of an operating point of the first driving source meets the one or more first resonance points.

Abstract: Embodiments for wirelessly programming a control system of a machine, such as a vehicle, are provided. As machines typically include an intricate collection of electronic devices that communicate to one another via a complex network, the ability to reliably program such devices over a wireless connection is extremely unreliable due to network limitations or requirements, such as defined communication protocols or standards. Embodiments relate to a machine interfacing device that can wirelessly communicate with a client device that serves as both a diagnostics and programming interface. The machine interfacing device, physically coupled to the control system, can independently convert and intelligently manage communications to and from electronic devices of the machine control system.

Abstract: Systems and methods for determining accuracy of a smoothed navigation solution using filtered resets are provided. In certain embodiments, a navigation system includes one or more inertial devices configured to detect motion of the system and generate inertial data; and one or more aiding devices configured to generate aiding device measurement data. Further, the navigation system includes one or more processors configured to generate an un-smoothed navigation solution based on the inertial data and the aiding device measurement data, wherein the un-smoothed navigation solution includes an un-smoothed navigation error estimates for a state variable. Further, the one or more processors are configured to calculate a smoothed navigation error estimate for the state variable based on the un-smoothed navigation error estimate.

Abstract: The present invention relates to an apparatus and method of controlling a vehicle. The present disclosure relates to a vehicle control apparatus and a control method therefor. Particularly, the vehicle control apparatus according to the present disclosure comprises: an operation performance unit for recognizing a first moving target on the basis of detection information detected by a sensor and performing a collision avoidance control operation; an identity determination unit for, when the first moving target is not recognized, recognizing a second moving target on the basis of the detection information after the first moving target is not recognized and determining whether or not the first moving target and the second moving target are identical to each other; and a control unit for, when the identity between the first moving target and the second moving target is recognized, controlling the vehicle on the basis of the collision avoidance control operation.

Abstract: A driving controller for a vehicle includes a detector that obtains driving information of a preceding vehicle and information about the road and a controller that determines a risk level of the preceding vehicle based on the driving information of the preceding vehicle and determines whether to perform avoidance control depending on the risk level. When it is determined that a breakdown or risk occurs in the preceding vehicle, the driving controller provides corresponding logic capable of avoiding the preceding vehicle.

Abstract: The present disclosure is directed to a device and method for detection of motion events including towing of the vehicle, jacking of the vehicle, and the vehicle being hit by another object. Processing is split between an MCU and a sensor unit. After the vehicle is turned off and before the MCU enters a sleep mode, the MCU calculates a gravity vector of the vehicle using accelerometer data, calculates threshold values based on the gravity vector, and saves the threshold values. After the MCU enters the sleep mode, the sensor unit subsequently monitors and detects motion events with the saved threshold values.

Abstract: A travel control device includes a travel environment recognizer recognizing travel environment information around a vehicle, an obstacle recognizer recognizing an obstacle possibly colliding with the vehicle, and a travel controller performing emergency braking when a first parameter becomes a first threshold value or smaller and causing the vehicle to start moving again when a second parameter reaches a second threshold value or larger. The obstacle recognizer recognizes a group of moving objects expressing similar behaviors based on the travel environment information, and recognizes the moving-object group as an obstacle if located closer to the vehicle than other objects. The travel controller calculates an expectation value based on each moving-object's behavior when the vehicle makes an emergency stop, and allows the vehicle to start moving again when the expectation value reaches a threshold value or larger even if the second parameter is smaller than the second threshold value.

Abstract: An apparatus and method for controlling material transfer from a harvesting machine. More specifically, an apparatus and method for transfer of an agricultural crop from a harvesting machine having a crop discharging device to a transport vehicle comprising a crop loading container while the harvesting machine and the transport vehicle travel on a field.

Abstract: A method includes an initial trailer health assessment and real-time trailer health monitoring. The initial trailer health assessment includes autonomous pre-trip maneuvers of the autonomous vehicle during a first time period, and detecting a pre-trip vehicle health condition. A vehicle health score is calculated based on the pre-trip vehicle health condition. If the vehicle health score is at least a threshold value, real-time trailer health monitoring is performed during a trip of the autonomous vehicle during a second time period, by actively monitoring vehicle dynamics data and/or image data associated with the autonomous vehicle, to determine a fault condition of the autonomous vehicle. If the fault condition meets a first criteria, a control parameter and/or a travel plan of the autonomous vehicle is adjusted. If the fault condition meets a second criteria different from the first criteria, a signal is sent to cause the autonomous vehicle to cease movement.

Abstract: A computing system for a vehicle may include processors to execute instructions to receive, by a middleware software layer of the computing system, messages published by one or more of a plurality of autonomous processing modules, and determine, by the middleware software layer, and based on the published messages, whether a similarity comparison of a first vehicle parameter and a second vehicle parameter satisfy a similarity threshold value. The first vehicle parameter and the second vehicle parameter relate to the messages published by the one or more autonomous processing modules. In response to determining that the similarity comparison of the first vehicle parameter and the second vehicle parameter does not satisfy the similarity threshold value, provide, by the middleware software layer, an instruction to a control system to cause the vehicle to perform an action, and cause, by the control system, the vehicle to perform the action.

Abstract: A system for predicting a collision risk in lane change decision based on a radar sensor, includes radar sensors disposed at a front portion and a rear portion of a host vehicle to recognize a forward vehicle positioned at a front-side portion of the host vehicle and a rearward vehicle positioned at a rear-side portion of the host vehicle, respectively, and a moving controller configured to determine that the host vehicle is able to change a lane, when a position of a counterpart vehicle, which is measured through the radar sensor, is not included in a section of the local map, and when a relative acceleration of the counterpart vehicle is maintained in an allowance range for a specific time.

Abstract: Anticipatory vehicle seat actuation, including: determining, based on sensor data capturing an environment around a vehicle, a predicted environmental state corresponding to a future time and comprising the vehicle entering a turn; determining, based on the predicted environmental state, an actuation state for one or more ECUs controlling a seat state the vehicle; and configuring the seat state of the vehicle according to the actuation state before the future time.

Abstract: A travel control device includes a first recognizer recognizing first travel environment information based on information acquired by an autonomous sensor, a second recognizer recognizing second travel environment information acquired by external communication, a main deceleration controller performing main deceleration control against an obstacle when it is determined, based on the first information, that the vehicle is traveling on a branch road merging with a main road and an obstacle may interfere with the vehicle at a merging point with the main road at a predicted time, and a preliminary deceleration controller performing preliminary deceleration control against the obstacle before the main deceleration control when it is determined, based on the second information, that the vehicle is traveling on the branch road, and the obstacle is to exist at the merging point at the predicted time and the obstacle is not recognized yet based on the first information.