Abstract: Systems and methods are disclosed for determining that an adverse driving event is likely to occur and utilizing accident calculus algorithms to determine and cause vehicle driving actions necessary to mitigate consequences of the adverse driving event. After determining that an adverse driving event is likely to occur, a computing device my forecast consequences of the driving event. The computing device may determine potential evasive maneuvers that may be taken responsive to the adverse driving event. Additionally, the computing device may determine consequences associated with the potential evasive maneuvers and assign a weight relative to the consequence. The computing device may compare the potential driving maneuvers based on the weighted consequences to determine a driving maneuver to take.

Abstract: A platooning control apparatus for preventing a vehicle from rollover and a method thereof are provided. A communication device provided in a vehicle which is platooning transmits and receives platooning information and information about a risk of rollover of the vehicle due to crosswind with at least one of other vehicles in a string of the vehicle or an external server. A processor performs formation control for preventing at least one of the vehicle or the other vehicles in the string from rollover. An autonomous vehicle in which a driver does not ride is prevented from rollover to ensure stability of autonomous driving.

Abstract: Embodiments of this application disclose a vehicle-based data processing method performed by a computer device. The method includes: determining at least two predicted offsets of a first vehicle, a first traveling state of the first vehicle, and a second traveling state of a second vehicle; determining, according to the first traveling state and the second traveling state, first lane change payoffs of the predicted offsets when the second vehicle is in a yielding prediction state, and determining second lane change payoffs when the second vehicle is in a non-yielding prediction state; and determining a predicted yielding probability of the second vehicle, generating target lane change payoffs of the predicted offsets according to the predicted yielding probability and the first lane change payoffs and the second lane change payoffs of the predicted offsets, and determining a predicted offset having a maximum target lane change payoff as a target predicted offset.

Abstract: A method includes: repeatedly performing following steps according to a preset scheduling period: receiving travelling information acquired by a target vehicle; searching, according to a global path of the target vehicle, a topological map for a target directed edge matching the travelling information; determining a right-of-way node sequence of the target vehicle according to the target directed edge and a coverage range of the target vehicle, where the right-of-way node sequence includes multiple right-of-way nodes, and the right-of-way nodes are nodes on the topological map; and determining right-of-way nodes matching the global path in the right-of-way node sequence as target right-of-way nodes in a case that each of the right-of-way nodes in the right-of-way node sequence is in a vacant, and sending the target right-of-way nodes to the target vehicle.

Abstract: A method for controlling a plurality of drones to survey a location, the method comprising, at a computing system: automatically generating preliminary flight plans for a plurality of drones to survey the location based on a 3D model; receiving survey data from the plurality of drones as the plurality of drones are surveying the location based on the preliminary flight plans; updating the 3D model based on the survey data received from the plurality of drones; and automatically updating at least a portion of the flight plans based on the updated 3D model

Abstract: Disclosed are a device for controlling a hybrid vehicle and a method thereof. The device includes a communication device that receives a plurality of data sets including a driving pattern and a control coefficient, and a controller that extracts speeds from the driving pattern, learns a control coefficient prediction model by using an average and a standard deviation of the speeds, and determines a control coefficient of the hybrid vehicle based on the control coefficient prediction model for which the learning is completed.

Abstract: A method of controlling a power supply system for an electric vehicle includes acquiring a first power setpoint value corresponding to the electrical power to be supplied by the battery, determining the electrical power required by the drivetrain and the electrical power required by the at least one auxiliary apparatus, determining the state of the battery, calculating at least one electrical power value to be delivered by the fuel cell, and calculating a second setpoint value for the electrical power to be delivered by the fuel cell. The second setpoint value is optimized so that the fuel cell operates at or near its maximum efficiency point.

Abstract: A pedal fault diagnosis method and apparatus for a vehicle are provided, including: detecting whether a driver seat is in an unmanned state; collecting an actual zero position voltage of a pedal when the driver seat is in the unmanned state; and then determining, based on the actual zero position voltage, whether a zero position fault exists on the pedal. The apparatus may update a set value of a zero position voltage in a vehicle controller based on the actual zero position voltage that is collected when the driver seat is in the unmanned state, and may be applied to the fields of assisted driving and automatic driving. Vehicle control safety can be improved by using the actual zero position voltage that is collected when the driver seat is in the unmanned state.

Abstract: Aspects of the present invention relate to a method of controlling one or more active vanes (2-n) on a host vehicle (VH1) having an energy recovery system (10). The one or more active vanes (2-n) is selectively configurable in a first position and a second position. The method comprises, in respect of one or more current operating parameters of the host vehicle (VH1), determining a first energy expended value (EEV1) and a first energy recovery value (ERV1) associated with the one or more active vanes (2-n) in the first position. A second energy expended value (EEV2) and a second energy recovery value (ERV2) associated with the one or more active vanes (2-n) are determined in respect of the second position. A first difference (D1) is determined between the first energy expended value (EEV1) and the first energy recovery value (ERV1). A second difference (D2) between the second energy expended value (EEV2) is determined and the second energy recovery value (ERV2).

Abstract: A vehicle and a control method thereof may increase a shooting angle of a camera mounted on the vehicle to photograph without limitation of the shooting angle. The method of controlling a vehicle including at least one camera, the control method including: adjusting a direction of a vehicle body to adjust a shooting direction of the at least one camera to a target direction thereof; and controlling the at least one camera to photograph in the adjusted shooting direction.

Abstract: System, methods, and computer-readable media for an object path prediction model, and an associated training technique, to output a path that is considered an object collision path. The object path prediction model outputs a set of predicted paths for the object that are outputted to a trained planning algorithm, which includes paths that are most likely to occur and a path that is considered an object collision path. The predicted paths are sent to the trained planning algorithm and used for planning a trajectory for the autonomous vehicle that is associated with a low probability of colliding with or taking a sudden evasive action to avoid the object.

Abstract: A remote operation terminal of a crane provided with a GNSS receiver for calculating the current position of the tip of a boom: acquires attitude information of the crane and the current position of the tip of the boom from a control device of the crane; generates a three-dimensional image of the crane at the current time and planimetric features on the basis of the information acquired from the control device and three-dimensional information acquired by a three-dimensional information acquisition unit; displays, on a display device, the generated three-dimensional image at the position of and in the direction of a viewpoint input to a viewpoint changing operation tool; and generates a control signal for the crane so that the tip of the boom of the three-dimensional image moves in a moving direction input to a suspended load moving operation tool in the three-dimensional image of the crane displayed on the display device.

Abstract: A method of performing autonomous driving based on platooning by a moving object includes setting a moving path, determining whether platooning is allowed, transmitting moving path information to a first intelligent transportation system infrastructure when the moving object of a plurality of moving objects approaches a preset range of the first intelligent transportation system infrastructure, receiving platooning information from the first intelligent transportation system infrastructure, and performing platooning based on the platooning information, wherein the first intelligent transportation system infrastructure groups ones of the moving objects capable of platooning from among the plurality of moving objects based on the moving path information received from each of the plurality of moving objects.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to receive radar data including a radar pixel having a radial velocity from a radar; receive camera data including an image frame including camera pixels from a camera; map the radar pixel to the image frame; generate a region of the image frame surrounding the radar pixel; determine association scores for the respective camera pixels in the region; select a first camera pixel of the camera pixels from the region, the first camera pixel having a greatest association score of the association scores; and calculate a full velocity of the radar pixel using the radial velocity of the radar pixel and a first optical flow at the first camera pixel. The association scores indicate a likelihood that the respective camera pixels correspond to a same point in an environment as the radar pixel.

Abstract: An electric vehicle computing sharing system (100) is adapted to receive a signal indicating the electric vehicle (110, 120, 130) is connected to a charging station (115, 125, 135). The computing sharing system (100) may be further adapted to receive information about the electric vehicle (110, 120, 130). The computing sharing system (100) may be further adapted to determine a predicted charging duration (535) for the electric vehicle (110, 120, 130). The computing sharing system (100) may be further adapted to identify a task for execution by a computing resource of the electric vehicle (110, 120, 130) based on the predicted charging duration (535). The computing sharing system (100) may be further adapted to transmit the task to the electric vehicle (110, 120, 130). The computing sharing system (100) may be further adapted to receive a result for the task from the electric vehicle (110, 120, 130).

Abstract: The invention relates to a self-moving device, including: a housing, a movement module configured to drive the housing to move, a drive module configured to drive the movement module to move, and a control module configured to control the self-moving device. A non-contact obstacle recognition sensor assembly is disposed on the housing. After the obstacle recognition sensor assembly detects that an obstacle exists in a movement direction, the control module controls the self-moving device to continue moving and steer until the obstacle is avoided. The movement direction is a forward driving direction of the self-moving device.

Abstract: An interference margin between a stator and a rotor is measured after a rotary electric machine is manufactured, and the measured value is stored in a memory of a life predicting device as an allowable limit value. The life predicting device calculates a wear amount of a bearing portion of the rotary electric machine from an operation state amount of the rotary electric machine, and determines whether or not the rotary electric machine reaches an end of a life and maintenance is needed based on the calculated value and the allowable limit value stored in the memory.

Abstract: A method for determining a movement vector of a motor vehicle includes: determining, via a radar system of the vehicle, at two successive instants, positions, relative to the vehicle, of elements of an environment of the vehicle that are static relative to the environment, associating the positions determined at these two successive instants with each other in such a way as to form different pairs of positions each grouping together the preceding position and the subsequent position of a given element of the environment, and determining the movement vector of the vehicle by linear regression, based on the pairs of positions thus formed.

Abstract: An information processing apparatus includes a communication interface configured to communicate with a first unmanned aircraft having a first camera to be used for detecting an obstacle and a second unmanned aircraft having a second camera to be used for detecting an obstacle with higher detection accuracy than the first camera, and a controller configured to, in a case in which a predetermined event relating to the first unmanned aircraft has occurred, detect, using the second unmanned aircraft, an obstacle at a target point on a flight path along which the first unmanned aircraft travels to a destination, and control the first unmanned aircraft to navigate around the detected obstacle using information regarding the detected obstacle.

Abstract: In a system for controlling a watercraft, when a first mode is selected, a controller determines a route on which a single or a plurality of specified spots including a destination are located, and controls a marine propulsion device such that the watercraft moves along the route with a bow thereof being kept oriented in a predetermined cardinal direction. When a second mode is selected, the controller controls the marine propulsion device such that the bow of the watercraft is kept oriented in the predetermined cardinal direction without determining the route. The controller obtains a position of the watercraft. In the first mode, the controller determines whether or not the watercraft has passed through the destination. When the watercraft has passed through the destination in the first mode, the controller performs a mode switching from the first mode to the second mode and controls the marine propulsion device in the second mode.