Abstract: An advanced driver assistance system (ADAS) and method for a vehicle include a light intensity detection system configured to detect a set of light density changes proximate to a face of a driver of the vehicle, a vehicle-to-everything (V2X) communication system, a global navigation satellite system (GNSS) system, and a controller configured to detect a current glare condition based on the set of detected light density changes from the light intensity detection system, share, using the V2X communication system, the detected current glare condition and the corresponding GNSS location, based on the sharing and another set of parameters, determine whether the vehicle is likely to experience a future glare condition during a future period, and in response to determining that the vehicle is likely to experience the future glare condition during the future period, at least one remedial action.

Abstract: A work machine includes a sensor that detects a retroreflective material and other objects in a distinguishable manner, a solenoid valve that restricts an operation signal outputted from an operation device, and a controller configured to control the solenoid valve based on the detection result. The controller controls the solenoid valve based on information concerning whether or not the object detected by the sensor is a retroreflective material and information concerning whether a position of the object detected by the sensor is in a first detection region at least partially including an operation range of a machine body or a second detection region located adjacent to and above the first detection region. This makes it possible to restrain contact between the work machine and an obstacle while restraining a reduction in a detection range due to exclusion of a structure of the work machine from an object of detection.

Abstract: Systems and methods are disclosed for detecting and predicting the motion of objects within the surrounding environment of a system such as an autonomous vehicle. For example, an autonomous vehicle can obtain sensor data from a plurality of sensors comprising at least two different sensor modalities (e.g., RADAR, LIDAR, camera) and fused together to create a fused sensor sample. The fused sensor sample can then be provided as input to a machine learning model (e.g., a machine learning model for object detection and/or motion prediction). The machine learning model can have been trained by independently applying sensor dropout to the at least two different sensor modalities. Outputs received from the machine learning model in response to receipt of the fused sensor samples are characterized by improved generalization performance over multiple sensor modalities, thus yielding improved performance in detecting objects and predicting their future locations, as well as improved navigation performance.

Abstract: Data regarding possible flight paths for a drone in relation to a start location and a destination is analyzed using a computer. Air space accessibility over a plurality of properties is determined, as part of a criteria, and the air space accessibility includes property owner permission and authorization for drone flight paths over the properties, respectively. Legal regulations regarding the possible drone flight paths over locations including the plurality of properties is determined as part of the criteria. An approved flight path is generated which includes permissions for the flight path granted by the property owners for flying through respective air space over the respective properties, and meeting legal regulations for flying over the locations including the respective properties on the possible flight paths. The approved flight path is sent to the drone or a drone control system for initiating a flight of the drone along the approved flight path.

Abstract: A system obtains scene context data characterizing the environment. The scene context data includes data that characterizes a trajectory of an agent in a vicinity of a vehicle up to a current time point. The system identifies a plurality of initial target locations, and generates, for each of a plurality of target locations that each corresponds to one of the initial target locations, a respective predicted likelihood score that represents a likelihood that the target location will be an intended final location for a future trajectory of the agent. For each target location in a first subset of the target locations, the system generates a predicted future trajectory for the agent given that the target location is the intended final location for the future trajectory. The system further selects, as likely future trajectories of the agent, one or more of the predicted future trajectories.

Abstract: An information processing apparatus includes a first detection unit which detects an object around a vehicle, a second detection unit of which at least a part of a detection range overlaps a detection range of the first detection unit and which detects an object around the vehicle, and a determination unit which determines whether or not the object has started to move on the basis of detection results of the first detection unit and the second detection unit. The determination unit determines that the object has started to move in a case in which the vehicle and the object are in a halted state when a detection result of the first detection unit indicates that the object has started to move and a detection result of the second detection unit indicates that the object has started to move.

Abstract: A method for controlling an overdetermined system with multiple actuators, for example an aircraft (1) with multiple propulsion units (3). The actuators perform at least one primary task and at least one non-primary task, including: a) determining a pseudo-control command up?p? based on a physical model of the system, which command represents the torques (L, M, N) and a total thrust force (F) acting on the system, b) determining a control matrix D, D?p?×k according to up=Du, where u1=D?1upu1?k represents a control command for the actuators to perform the primary task, c) projecting the non-primary task into the null space N(D) of the primary task, so that Du2=0 if u2u2?k represents a control command for the actuators to perform the non-primary task, and d) providing the control commands from b) and c) to the actuators. In this way, the solution of the primary task is not adversely affected by the non-primary task or its solution.

Abstract: The invention relates to an automated driving control system, including: a data exchange unit configured to obtain video data streams and distribute the video data streams to at least one computing unit; the at least one computing unit configured to compute perception result data based on the video data streams; a sensor fusion unit configured to fuse the perception result data and sensor data, to obtain fusion result data; and a planning control unit configured to generate a driving control instruction based on the fusion result data, where the planning control unit or the sensor fusion unit is configured to provide a bypass of the data exchange unit. When anomalies occur in any of the units, the automated driving control system may provide a corresponding bypass to keep an automated driving function going.

Abstract: A braking method for a vehicle is provided. The method includes the following steps: obtaining a first state information of the vehicle, where the first state information includes a vehicle mass and a deceleration required by braking; calculating a braking torque required by the vehicle according to the first state information, and controlling an output of an electric braking torque according to the braking torque required by the vehicle; obtaining a current vehicle speed of the vehicle and a maximum electric braking exit speed; and; controlling, if the deceleration required by braking of the vehicle changes to zero, the vehicle to unload the electric braking torque when the current vehicle speed is less than the maximum electric braking exit speed. A braking device for a vehicle and a vehicle are further provided.

Abstract: An automated driving vehicle includes: a communication device which receives a traveling plan from an operation management device provided outside an vehicle; and an automated driving controller which allows an vehicle the controller is associated with to travel autonomously along a traveling route on which a plurality of stations are set so as to fulfill the traveling plan, in which the automated driving controller has a standard plan which prescribes a standard operation schedule of the vehicle the controller is associated with, and the automated driving controller, in a case where the traveling plan has not arrived or is irregular, generates an interim plan on the basis of the standard plan, and allows the vehicle the controller is associated with to travel autonomously so as to fulfill the interim plan.

Abstract: Techniques relating to performance-based metrics for evaluating system quality are described. In an example, sensor data associated with an environment within which a vehicle is positioned is received. A performance metric associated with a trajectory, indicative of a performed behavior of the vehicle, can be determined and a correctness metric can be determined based at least in part on the performance metric. The correctness metric can represent a correctness of the performed behavior. Modification(s) to component(s) and/or system(s), or portions thereof, of the vehicle can be affected based at least in part on the correctness metric.

Abstract: Provided is a method of controlling driving of a vehicle using advance information, the method including acquiring preset local information including a road name, a road section, a road attribute, a location of a building, a lane, a traffic signal, and obstacle information for a predetermined region, acquiring a driving experience value resulting from a previous drive using the local information, and setting a target speed corresponding to the road attribute using the driving experience value, determining a driving state and a driving speed of the vehicle on the basis of the local information, and the target speed, of a current position of the vehicle, and generating a driving control command corresponding to the driving state and the driving speed.

Abstract: A driver assistance system (DAS) comprises camera installed on a vehicle, having a field of view in front of the vehicle, and configured to acquire image data; and a controller including a processor configured to process the image data. The controller may be configured to identify at least one object obstructing a driving of the vehicle based on the image data, identify a stopped vehicle among the at least one object based on the image data, and set a driving route of the vehicle based on the position of the at least one object and the position of the stopped vehicle, and controls at least one of a braking device and a steering device of the vehicle so that the vehicle travels along the driving route.

Abstract: In a vehicle control device for an autonomous driving vehicle that autonomously travels based on an operation command, a gesture image of a person around the autonomous driving vehicle is acquired, and a stored reference gesture image is collated with the acquired gesture image. At this time, when it is discriminated that the gesture of the person around the autonomous driving vehicle is a gesture requesting the autonomous driving vehicle to stop, it is determined whether a disaster has occurred. When it is determined that the disaster has occurred, the autonomous driving vehicle is caused to stop around the person requesting the autonomous driving vehicle to stop.

Abstract: Systems, methods, and computer-readable media are disclosed for controlling one or more vehicles with the use of navigation markers positioned or integrated into a ground surface. A vehicle, such as an autonomous vehicle, may include a light detection assembly, which may include a light emitter, an optical filter, an optical sensor, and an analog-to-digital converter, and optionally may include a lens. The light emitter may emit light towards the ground surface which may illuminate the navigation marker and cause the navigation marker to emit light passes through the optical filter and is ultimately sensed by the optical sensor. The vehicle may determine the light was emitted by the navigation marker and cause the vehicle to perform the predetermined action.

Abstract: As a farming machine travels through a field of plants, the farming machine operates in a normal operational state to perform one or more farming operations. The farming machine detects an operational failure of a component of the farming machine using measurements obtained from one or more sensors coupled to and monitoring the farming machine. The operational failure of the component impacts performance of a first farming operation of the farming operations. The farming machine configures the farming machine to operate in a remedial operational state. In the remedial operational state, the farming machine diagnoses the operational failure of the component using the obtained measurements. In the remedial operational state, the farming machine selects a solution operation to address the operational failure of the component based on the diagnosis. The farming machine performs the determined solution operation.

Abstract: In a vehicle including a shift-by-wire (SBW) transmission which may be parked in the neutral gear position of the transmission, method for controlling parking thereof includes determining whether the vehicle is in a situation in which neutral parking is required according to sensor information, when the vehicle is stopped, outputting first information configured to get a confirmation on whether a driver intends to perform the neutral parking from the driver, when the controller concludes that the vehicle is in the situation in which the neutral parking is required and when a park (P) gear position is input or an ignition of the vehicle is turned off, and controlling the SBW transmission to shift to a neutral (N) gear position, when there is an agreement input as a response to the first information.

Abstract: Disclosed herein an autonomous driving system includes a first sensor installed in a vehicle, having a field of view facing in front of the vehicle, and configured to acquire front image data; a second sensor selected from the group consisting of a radar and a light detection and ranging, installed in the vehicle, having a detection field of view facing in front of the vehicle, and configured to acquire forward detection data; a communicator configured to receive a high definition map at a current location of the vehicle from an external server; and a controller including a processor configured to process the high definition map, the front image data, and the forward detection data.

Abstract: A cleaning route determination system includes an analyzer that analyzes behavior of airflow and particles inside a facility, a map generator that generates a dust accumulation map indicating one or more dust accumulation areas inside the facility and one or more dust amounts corresponding to the one or more dust accumulation areas, and a route calculator that determines a first route from second routes. Each of the second routes is a route for a cleaner to pass through, within a certain period of time, at least one of the one or more dust accumulation areas. A total amount indicating a sum of dust amounts corresponding to dust accumulation areas included the first route is largest among total amounts corresponding to the second routes, each of the total amounts indicating a sum of dust amounts corresponding to dust accumulation areas included in each of the second routes.

Abstract: A vehicle control system is configured to group objects detected by a plurality of sensors. The vehicle control system includes an integration device that groups detection information from the plurality of sensors and outputs integrated detection information, and a vehicle control device that controls a vehicle on the basis of the integrated detection information.