Abstract: A lane-keeping assistance system of a motor vehicle, which is at least partially operated with assistance, in which an environment of the motor vehicle with a potential lane is detected via an optical detection device of the lane-keeping assistance system and evaluated via an electronic computing device of the lane-keeping assistance system and in which, as a function of the evaluated environment, an at least partially assisted lane-keeping movement is carried out by means of a transverse control device of the lane-keeping assistance system, wherein swarm data provided by an electronic computing device, which is external relative to the vehicle, are taken into account for evaluating the environment, wherein a future drivable route, which is outside of a detection area of the optical detection device, is evaluated on the basis of the swarm data, and a future partially assisted lane-keeping movement for the transverse control device is determined.

Abstract: A convergence determination unit determines whether a state of the bucket has converged to a current target state. A target state update unit is configured to update a target state of the bucket when the convergence determination unit determines that the state of the bucket has converged to the current target state. The convergence determination unit includes a first convergence determination unit and a second convergence determination unit. The first convergence determination unit determines whether a swing angle of each mechanism has converged to the corresponding target swing angle under a first convergence condition. The second convergence determination unit determines whether a swing angle of each mechanism has converged to the corresponding target swing angle under a second convergence condition, which is stricter than the first convergence condition.

Abstract: A flight management apparatus includes a condition information acquisition unit that acquires condition information including a weather condition for flight of a flight apparatus, the weather condition being associated with a position provided on a flight path or in a flight range in which the flight apparatus is scheduled to fly, a weather information acquisition unit that acquires weather information including weather at a current position at which the flight apparatus is positioned, or a scheduled position at which the flight apparatus is scheduled to be positioned, a determination unit that determines whether or not the weather satisfies the weather condition associated with the current position or the scheduled position in the condition information, and an output unit that outputs information corresponding to a determination result of the determination unit.

Abstract: A working machine 1 includes a design data obtainment unit 29, a topography measuring device 30, and a controller 21. The controller 21 extracts peripheral area shape data from the design data in the construction-site coordinate system, maps similar shape portions between the extracted peripheral area shape data and the current topography data in the current topography coordinate system, calculates a coordinate transformation matrix to transform from the current topography coordinate system to the construction-site coordinate system so that a difference in coordinate values of the mapped shape portions is minimized, and transforms the self-position and posture of the working machine 1 and the current topography data from coordinates in the current topography coordinate system to coordinates in the construction-site coordinate system using the calculated coordinate transformation matrix.

Abstract: An autonomous running vehicle transmits a camera image around the vehicle photographed by a camera to a remote monitoring center. An obstacle is detected on the basis of information obtained from autonomous sensors including the camera. When an obstacle is detected, the autonomous running vehicle is automatically stopped. The remote monitoring center determines, when the autonomous running vehicle automatically stops, whether or not the run of the autonomous running vehicle is permitted to restart on the basis of the received camera video. When it is determined that the autonomous running vehicle can be restarted, a departure signal is transmitted to the autonomous running vehicle. When the departure signal is received from the remote monitoring center, the autonomous running vehicle restarts running.

Abstract: A driving operation management system includes: an operator information accumulation unit that accumulates operator information; a mobile object information acquisition unit that acquires mobile object information; a driving operation reception unit that receives a driving operation of the operator; a service information management unit that acquires and associates the operator information and at least one of the mobile object information or operation information indicating the driving operation, and causes the acquired and associated information to be accumulated as service information; a service information accumulation unit that accumulates the service information; a determination logic setting unit that sets a determination logic for determining an operating state on the basis of the service information accumulated; a determination logic accumulation unit that accumulates the determination logic; and a determination unit that determines the operating state using the determination logic accumulated.

Abstract: Sound signals are received by one or more microphones disposed at an ADV. The sound signals are analyzed to extract a feature of a road on which the ADV is driving. A road condition of the road is determined based on the extracted feature. A path planning and speed planning is performed to generate a trajectory based on the road condition. The ADV is controlled to drive autonomously according to the generated trajectory.

Abstract: A robot generates a cell grid (e.g., occupancy grid) representation of a geographic area. The occupancy grid may include a plurality of evenly sized cells, and each cell may be assigned an occupancy status, which can be used to indicate the location of obstacles present in the geographic area. Footprints for the robot corresponding to a plurality of robot orientations and joint states may be generated and stored in a look-up table. The robot may generate a planned path for the robot to navigate within the geographic area by generating a plurality of candidate paths, each candidate path comprising a plurality of candidate robot poses. For each candidate robot pose, the robot may query the look-up table for a corresponding robot footprint to determine if a collision will occur.

Abstract: A system, method, infrastructure, and vehicle for automated valet parking are provided. The method includes initiating an automated valet parking procedure for a vehicle, providing the vehicle with a target position and a first guide route leading to the target position, detecting an unexpected incident based on situation information, and providing the vehicle with a second guide route to deal with the unexpected incident.

Abstract: A method for steering a vehicle along a path in a driveway and around obstacles between a starting position into a target position, comprises the steps of determining the vehicle dimensions, steering and driving capabilities, carrying out a path optimization step to evaluate, based on a predetermined cost function, the least costly path between the starting position and the target position avoiding any collisions with obstacles. The method further comprises the further step of applying a path improver step, smoothening the trajectory obtained by the path optimization method by means of numerical optimization while fulfilling dynamical constraints on acceleration and steering rate of the vehicle through planning lateral and longitudinal movement of the vehicle in a joint optimization problem or by means of separate optimization problems.

Abstract: The present invention provides a recognition device that is mounted on a moving object and recognizes a lighting situation of a traffic signal, the recognition device comprising: an imaging unit that periodically images an external environment of the moving object; at least one processor with a memory comprising instructions cause the at least one processor to at least: sequentially detect, for each image periodically obtained by the imaging unit, a lighting mode of the traffic signal included in the image; and determine, in a case where a same lighting mode of the traffic signal is continuously detected for a predetermined time, the lighting mode as a lighting situation of the traffic signal, wherein the predetermined time is twice or more as long as an imaging cycle of the imaging unit.

Abstract: A lift device includes multiple electrical components and a battery monitoring system. The battery monitoring system includes multiple batteries and a controller. The multiple batteries are configured to power the multiple electrical components. The controller is configured to obtain sensor data from the batteries. The controller is also configured to determine a state of charge of the batteries for open circuit conditions based on the sensor data. The controller is configured to determine a state of charge of the batteries for load conditions based on the sensor data. The controller is configured to determine a state of charge of the batteries for charging conditions based on the sensor data. The controller determines an overall state of charge of the batteries based on the state of charge for open circuit conditions, the state of charge of the batteries for load conditions, and the state of charge for charging conditions.

Abstract: A vehicle includes a controller programed to: collect a set of data related to a driver of the vehicle; predict a driving setting for the driver using the set of data and an initial student-T process (STP) machine learning (ML) model; generate an updated STP ML model based on the prediction of the driving setting as to the set of vehicle data; transmit incremental learning related to the updated STP ML model to a server; and receive, from the server, a personalized driving setting for the driver output from a cloud STP ML model trained by the incremental learning.

Abstract: A control unit for a vehicle is configured to determine, during an approaching manoeuvre of a distance controller and/or cruise controller of the vehicle towards a vehicle in front, whether or not the vehicle will overtake or can overtake the vehicle in front during the approaching manoeuvre. Furthermore, during the approaching manoeuvre, the control unit is configured to adjust a behaviour of the cruise controller and/or adaptive cruise controller of the vehicle on the basis of the above determination.

Abstract: A work machine control device includes a lift force detection unit, a control amount determination unit, and a command output unit. The lift force detection unit detects a lift force of the work machine. The control amount determination unit determines a control amount for the work machine based on a change amount of the detected lift force. The command output unit outputs, to an actuator driving the work machine, a control command according to the determined control amount. The control amount determination unit determines the control amount such that the control amount monotonically increases with respect to the lift force until a lift amount of the work machine reaches a predetermined threshold. A work vehicle includes the work machine control device, a vehicle body, a work machine supported by the vehicle body, and an actuator that drives the work machine.

Abstract: The technology relates to generating simulations in order to evaluate software used to control vehicles in an autonomous driving mode. In one example, an initial situation involving a certain kind of interaction between a vehicle operating in the autonomous driving mode and an object may be identified. A search of log data may be conducted in order to identify one or more similar situations based on characteristics of the initial situation. A new simulation may be generated using the identified one or more similar situations by inserting the object into the one or more similar situations. The new simulation may be run in order to evaluate the software.

Abstract: Described are systems and methods relating to the causal detection and diagnosing of faults and anomalous operation of autonomous vehicles, such as unmanned aerial vehicles (UAVs), using machine learning. Embodiments of the present disclosure can provide systems and methods for detecting and diagnosing faults based on comparisons between the measured operation and/or behavior of a vehicle to the vehicle's expected nominal operation and/or behavior. Accordingly, the systems and methods according to embodiments of the present disclosure do not require prior knowledge of faults or modeling of the vehicle, the vehicle's operation, and/or environmental uncertainties. Further, embodiments of the present disclosure can facilitate sequencing of a vehicle's faults and/or anomalous operation and/or behavior, identify dependencies between a vehicle's faults and/or anomalous operation and/or behavior, and can detect and diagnose faults and/or anomalous operation and/or behavior in a contextual manner.

Abstract: Provided is an apparatus for assisting driving of a vehicle, the apparatus comprising: a front camera mounted on a vehicle and having a field of view in front of the vehicle, the front camera configured to acquire front image data; a dynamics sensor mounted on the vehicle and configured to acquire dynamics data that is a motion state of the vehicle; and a controller including a processor configured to process the front image data and the dynamics data, wherein the controller is configured to generate a front virtual lane on the basis of the field of view in front of the vehicle based on the front image data, and generate a rear virtual lane on the basis of the field of view in rear of the vehicle based on the front virtual lane and the dynamics data.

Abstract: A method and system for teaching a transfer device including a substrate holder and a first detector disposed at the substrate holder is disclosed. The method comprises detecting a vertical position of an object by the first detector while moving the substrate holder in a vertical direction, and setting a teaching position of the substrate holder in the vertical direction based on the detected vertical position of the object; and setting a teaching position of the substrate holder in a horizontal direction based on a horizontal position of the substrate holder at which the substrate holder is detected by a second detector while moving the substrate holder in the horizontal direction, the second detector being disposed at a position different from a position of the transfer device.

Abstract: A measurement of the rotation speed of an object is made using a time-of-flight sensor configured to detect a passing of one or more of elements of the object through a given position. The time-of-flight sensor is further mounted on a one-person vehicle configured to protect the one-person vehicle against collisions through the making a time-of-flight measurement of a relative speed between the one-person vehicle and an obstacle.