Abstract: A vehicular self-diagnosis device includes first to third sensors that detect parameters to be used in steering control of a vehicle, first to third turn estimators that respectively estimate turn statuses of the vehicle based on a steering angle detected by the first sensor, vehicle behavior detected by the second sensor, and a lane curvature and a vehicle-versus-lane yaw angle of the vehicle relative to the lane curvature detected by the third sensor, an offset extractor that extracts first to third offset components respectively from signals indicating the estimated turn statuses, an offset-divergence-amount calculator that calculates a maximum divergence amount based on maximum and minimum values of the first to third offset components, and a comparison unit that compares the maximum divergence amount with a predetermined threshold value and determines that inconsistency exists among the first to third sensors if the maximum divergence amount exceeds the threshold value.

Abstract: In various examples, sensor data may be collected using one or more sensors of an ego-vehicle to generate a representation of an environment surrounding the ego-vehicle. The representation may include lanes of the roadway and object locations within the lanes. The representation of the environment may be provided as input to a longitudinal speed profile identifier, which may project a plurality of longitudinal speed profile candidates onto a target lane. Each of the plurality of longitudinal speed profiles candidates may be evaluated one or more times based on one or more sets of criteria. Using scores from the evaluation, a target gap and a particular longitudinal speed profile from the longitudinal speed profile candidates may be selected. Once the longitudinal speed profile for a target gap has been determined, the system may execute a lane change maneuver according to the longitudinal speed profile.

Abstract: The present application provides a method and apparatus for planning an autonomous vehicle, an electronic device and a storage medium, which relates to the field of autonomous driving. According to the technical solutions of the present application, time points of entering a vehicle-converging area can be accurately predicted according to traveling conditions of two parties, so that a driving behavior of the autonomous vehicle is controlled more accurately.

Abstract: A work vehicle includes a driving wheel provided in a machine body, a motor for inputting a rotational force to the driving wheel, a traveling control device for acquiring an output instruction for the motor according to an operation of a maneuvering lever, a traveling control unit for controlling driving of the motor in accordance with the output instruction, a battery for reserving energy source for driving the motor, a remaining amount detection section for detecting a remaining amount of the energy source in the battery, and a restriction section for restricting a maximum speed of the machine body to a preset speed irrespectively of the output instruction if the remaining amount of the energy source is equal to or smaller than a preset first threshold value.

Abstract: An exemplary robotic system includes a plurality of controllable joints and a controller. An exemplary control method provides for controlling the controllable joints by the controller. The control method provides for determining a configuration space for the robotic system and determining a reference movement path within the configuration space. The control method then provides for assigning a plurality of streamlines in the configuration space to yield a flow field based on the reference movement path. The control method then provides for measuring actual velocity vectors of the robotic system in the configuration space. The control method then provides for determining an error velocity vector based on a difference between the actual velocity vector and the desired velocity vector given by the flow field corresponding to the current robot configuration.

Abstract: The technology relates to route planning and performing driving operations in autonomous vehicles, such as cargo trucks, articulating buses, as well as other vehicles. A detailed kinematic model of the vehicle in evaluated in conjunction with roadgraph and other information to determine whether a route or driving operation is feasible for the vehicle. This can include evaluating a hierarchical set of driving rules and whether current driving conditions impact any of the rules. Driving trajectories and cost can be evaluated when pre-planning a route for the vehicle to follow. This can include determining an ideal trajectory for the vehicle to take a particular driving action. Pre-planned routes may be shared with a fleet of vehicles, and can be modified based on information obtained by different vehicles of the fleet.

Abstract: A system and method for detecting behavioral anomalies among a fleet including a plurality of connected vehicles. The method includes generating at least one fleet behavioral profile for the fleet using a first set of data, wherein creating each fleet behavioral profile includes training a machine learning model using at least a portion of the first set of data, wherein the at least a portion of the first set of data relates to communications with and among the plurality of connected vehicles; applying the at least one fleet behavioral profile to detect at least one anomaly in a second set of data for the fleet wherein the second set of data includes data related to communications with and among the plurality of connected vehicles; and performing at least one mitigation action when the at least one anomaly is detected.

Abstract: A robot in a robot system including a plurality of robots each having a function of identifying a monitoring target and transmitting information related to the monitoring target to a remote site. The robot includes an acquiring unit that acquires sensing data related to the monitoring target, a communication unit that communicates with another nearby robot, and a control unit that controls the communication unit such that an alert mode transition request signal is transmitted to the other nearby robot if it is determined that a first monitoring target is in an abnormal state on a basis of the sensing data. The robot transitions to an alert mode in which a process according to the received alert mode transition request signal is performed if the alert mode transition request signal related to a second monitoring target is received.

Abstract: Provided is a setting change assist apparatus for a vehicle configured to: determine whether a setting change request for changing a setting state of driving support control is issued; when determining that the setting change request is issued, notify a driver of confirmation information including information on a content of the setting change request and information on a predetermined approval operation with respect to the setting change request; and change the setting state of the driving support control in accordance with the setting change request when the driver performs the approval operation.

Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to capture, from a camera, one or more images, wherein the one or more images include at least a portion of a vehicle, receive a plurality of keypoints corresponding to markers on the vehicle and instantiate a virtual vehicle corresponding to the vehicle. The instructions include further instructions to determine rotational and translation parameters of the vehicle by matching a plurality of virtual keypoints to the plurality of keypoints and determine a multi-degree of freedom (MDF) pose of the vehicle based on the rotational and translation parameters.

Abstract: Systems and methods for controlling an autonomous vehicle are described. A trajectory planner module provides a first trajectory to a trajectory control module. The trajectory control module determines parameters of the first trajectory. The trajectory control module compares the parameters to a respective threshold value. The trajectory control module obtains one or more alternative trajectories, determines parameters of each alternative trajectory, and compares the parameters of the alternative trajectory to a respective threshold value. The trajectory control module selects a trajectory for controlling the autonomous vehicle that has parameters which are within a range defined by the threshold values and controls the autonomous vehicle based on the selected trajectory. Thus, before handing back control to a driver, the trajectory control module selects from alternate trajectories for controlling the autonomous vehicle.

Abstract: A vehicle travel control device includes a travel information collector and a travel control unit. The travel information collector is configured to collect travel environment information of a first vehicle. The travel environment information at least includes travel information of the first vehicle, ambient environment information of the first vehicle including external appearance information of a second vehicle, and first-vehicle lane information for recognizing a traveling lane of the first vehicle. The travel control unit is configured to perform travel control of the first vehicle based on the travel environment information. When the traveling lane of the first vehicle is a nonpriority lane and the first vehicle traveling on a nonpriority lane is to merge into a priority lane, the travel control unit is configured to perform control for causing the first vehicle to travel along a lane boundary line of the traveling lane, based on the travel environment information.

Abstract: A method of operating an autonomous cleaning robot includes receiving, at a handheld computing device, a first input representing a first set of cleaning schedule parameters for a first cleaning schedule for the autonomous cleaning robot, the first cleaning schedule corresponding to a first area. The method includes presenting, on a display of the handheld computing device, the first cleaning schedule. The method includes receiving, at the handheld computing device, a second input representing a second set of cleaning schedule parameters for a second cleaning schedule for the autonomous cleaning robot, the second cleaning schedule corresponding to a second area different from the first area. The method includes presenting, on the display, the first and second cleaning schedules, and initiating a transmission to the autonomous cleaning robot, based on the first or second cleaning schedules, the transmission including data for causing the robot to initiate a cleaning mission.

Abstract: A vehicle includes an inertial measurement unit (IMU); and a controller electrically connected to the IMU. The controller is configured to receive an output signal including at least one of an angular velocity and an acceleration from the IMU, to identify a driving state of the vehicle according to at least one of the output signal, a steering angle of the vehicle, a steering angular velocity of the vehicle, a number of gear stages of the vehicle, a wheel speed of the vehicle, and a braking pressure of the vehicle, to identify an offset and an offset reliability of the output signal according to the driving state of the vehicle, and to transmit a signal from which the offset is removed from the output signal according to the offset and the offset reliability.

Abstract: A vehicle is capable of compensating for steering control based on vehicle's intrinsic factors and environmental influence factors, thereby performing steering compensation control accurately. The vehicle includes: a storage unit; a driving unit to drive a steering device; a sensor to acquire detection signals including a steering angle and a steering torque; and a controller to determine whether the vehicle is in a predetermined stable running state based on the detection signals, wherein, when the vehicle is in the predetermined stable running state, the controller extracts reference information including a relationship between the steering angle and the steering torque at one or more past time points, stores the reference information in the storage unit, and controls the driving unit based on a difference between the reference information and the steering angle and the steering torque.

Abstract: An automatic parking assistance system, an in-vehicle device and an automatic parking assistance method. The in-vehicle device comprises a communication interface for receiving a parking navigation path and traffic information; and a parking controller coupled with the communication interface, the parking controller being configured to: acquire the traffic information and the parking navigation path; control vehicle parking maneuvers based on the parking navigation path; judge whether there is a potential collision object with respect to the vehicle based on the traffic information; in the case that the judgment indicates there is no potential collision object, control the vehicle to travel along the parking navigation path; in the case that the judgment indicates there is a potential collision object, determine a danger level of the potential collision object based on the traffic information and determine safety measures corresponding to the danger level.

Abstract: In one aspect, the present disclosure is directed at a computer implemented method for determining a drivable area in front of a host vehicle. According to the method, a region of interest is monitored in front of the host vehicle by at least two sensors of a detection system of the host vehicle. The region of interest is divided into a plurality of areas via a computer system of the host vehicle, and each area of the plurality of areas is classified as drivable area, non-drivable area or unknown area via the computer system based on fused data received by the at least two sensors.

Abstract: A device for controlling travel of a vehicle includes: a sensor that acquires information on a surrounding region of the vehicle, and a controller that generates a speed profile based on the information on the surrounding region of the vehicle, calculates an average acceleration in the speed profile based on a current vehicle speed and a vehicle speed at a predetermined time point, and calculates a required acceleration at a time point at which a difference between the speed profile and the average acceleration is greatest, and performs travel control based on at least one of the average acceleration or the required acceleration. The device allows a longitudinal control to be performed based on the speed profile generated by the vehicle, thereby improving an accuracy of autonomous driving.

Abstract: A vehicle control device executes a cruise control to let a vehicle travel in such a manner that an acceleration is equal to a predetermined acceleration, when an execution condition becomes satisfied, and starts a vehicle speed upper limit control to let the vehicle travel in such a manner that the vehicle speed does not exceed an upper limit value determined based on a shape of a curve section, when a start condition becomes satisfied. The vehicle control device starts displaying a display element in a first display mode, when the vehicle speed upper limit control is started. At a time point at which the vehicle speed upper limit control is ended, the vehicle control device starts displaying the display element in a second display mode different from the first display mode if the execution condition is not satisfied.

Abstract: The techniques of this disclosure relate to a vehicle lateral-control system with adjustable parameters. The system includes a controller circuit that receives identity data from a driver-monitoring sensor indicating an identity of a driver of a vehicle. The controller circuit receives vehicle lateral-response data from vehicle sensors based on steering maneuvers performed as the vehicle operates under control of the driver. The controller circuit determines lateral-steering parameters of the vehicle based on the vehicle lateral-response data. The controller circuit adjusts lateral-control parameters of the vehicle based on the lateral-steering parameters. The controller circuit associates the adjusted lateral-control parameters of the vehicle with the identity of the driver. The controller circuit operates the vehicle according to the lateral-control parameters associated with the identity of the driver.