Abstract: A plurality of prompts, each associated with a road event, are presented on a display upon receiving a first input on an input device. A second input selecting the prompts is received on a second input device. A message is sent with the selected prompts and a location of a vehicle.

Abstract: A method of controlling a mobile machine having a set of ground engaging elements includes receiving an image of terrain proximate the mobile machine, detecting a contour of the terrain, determining a projected path of the set of ground engaging elements based on the detected contour of the terrain, and controlling a display device to display the image with an overlay representing the projected path of the ground engaging elements.

Abstract: A vehicle control system executes automated driving control that controls automated driving of a vehicle based on driving environment information indicating a driving environment for the vehicle. When a part of functions of the vehicle is failed during the automated driving, the vehicle control system executes emergency stop control that stops the vehicle. In the emergency stop control, the vehicle control system: acquires failure status information being information on the failed part of functions; determines, based on the failure status information and the driving environment information, a target stop position at which even the vehicle with the failed part of functions is able to arrive and stop by the automated driving; and executes the automated driving control such that the vehicle travels toward the target stop position to stop at the target stop position.

Abstract: A positioning method comprises acquiring positioning information of a 5G base station from a satellite, obtaining calibration information based on the positioning information, and broadcasting outwards the calibration information; acquiring initial positioning information of a user terminal from the satellite; accessing a nearest 5G base station in real time, monitoring and acquiring calibration information broadcasted by the nearest 5G base station; and calibrating the initial positioning information acquired in the initial positioning step according to the calibration information acquired in the monitoring step to obtain positioning result information. As described above, the positioning of centimeter level precision can be realized by utilizing the 5G base station, and there is no need to additionally establish a CORS base station and a data center, thereby the cost of precise positioning can be reduced.

Abstract: Disclosed is a vehicle control method which comprises the steps of: determining whether or not a squat of a rear end of a vehicle body is equal to or greater than a given level; determining whether or not turning manipulation of a steering device has been made; and, when the turning manipulation of the steering device is determined to have been made, controlling each part of an engine (4) to reduce an output torque of the engine (4), wherein, in response to the determination that the turning manipulation of the steering device has been made, a reduction amount of the output torque of the engine is increased when the squat of the rear end of the vehicle body is equal to or greater than the given level, as compared to when the squat is less than the given level.

Abstract: A simulation environment is disclosed. A simulator generates a simulation model corresponding to a sequence of simulation cycles, each cycle including initial conditions, propagatable states, and a level of simulation fidelity. A fidelity optimizer monitors states and conditions through each cycle, changing the fidelity level for the next cycle based on predetermined factors (e.g., a new flight segment). The fidelity optimizer may dynamically increase or decrease the fidelity level for the next cycle (or for one or more nodes within a group) in response to, or in anticipation of, a state change. The fidelity optimizer may sample several corresponding simulation cycles of varying fidelity levels to compare the effects or results, and determine whether the result is dependent on the fidelity level.

Abstract: A parking assistance device includes a parking direction specification unit specifying a parking direction in a case where a subject vehicle is parked at a parking region, an obstacle detection unit detecting an obstacle, a detection range setting unit setting a detection range for detecting a bearing of the obstacle, a division unit dividing the detection range in a direction associated with the specified parking direction and generating plural divided ranges, a bearing calculation unit calculating a bearing of the detected obstacle, which is a bearing of a side surface of the obstacle which extends in the parking direction, for each of the divided ranges and calculating an average value of the bearings which are respectively calculated for the divided ranges, and a parking position setting unit setting a parking position where the subject vehicle is parked at the parking region based on the calculated average value.

Abstract: A recognition processing apparatus includes a video acquisition unit configured to acquire first captured image data of surroundings of a host vehicle captured by a far-infrared camera, an other vehicle detection unit configured to detect another vehicle parked or stopped in the surroundings of the host vehicle, a heat detection unit configured to detect radiated heat associated with an operation of the other vehicle based on a thermal distribution in a region corresponding to the other vehicle in the first captured image data, and a person detection unit configured to, when the radiated heat has been detected, preferentially execute person recognition in a vicinity of the other vehicle to detect a person. The recognition processing apparatus can ascertain the possibility that a person gets out of a detected vehicle and promptly detect such a person.

Abstract: The present invention provides a new system that allows an easier operation of a moving object. The present invention provides a moving object operation system including: a moving object; and an operation signal transmitter. The moving object includes a signal receipt unit that receives an operation signal. The transmitter includes: an auxiliary tool; a storage unit that contains conversion information; a movement information acquisition unit that acquires auxiliary tool movement information; a conversion unit that converts the acquired movement information into the operation signal based on the conversion information; and a signal transmission unit that transmits the operation signal. The conversion information includes auxiliary tool movement information and operation signal information for instructing the moving object in how to move, and those are associated with each other.

Abstract: Path planning is performed using a multi-layer grid searching algorithm to position an ADV in a target position. A first layer grid including a first set of nodes is defined. A second layer grid is defined. The second layer grid includes a second set of nodes corresponding to at least a portion of the first set of nodes. From a start node until a goal node, following operations are iteratively performed. A set of next node candidates are identified by searching in the first set of nodes and the second set of nodes. For each next node candidate of the set of next node candidates, a cost is determined using a cost function. A next node having a lowest cost is selected from the set of next node candidates based on their respective costs. A path trajectory of the ADV is generated to position the ADV at the target position.

Abstract: A system comprising a computer programmed to identify a connected location of a vehicle at which a user device is connected to a first network and a disconnected location of the vehicle at which the user device is disconnected from the first network. Upon further determining that the user device has not connected to a second network within a first predetermined time, the computer is further programmed to activate an aerial drone container to an open position.

Abstract: [Problem] To implement a variety of realistic staging under various venue environments. [Solution] An event staging system according to the present invention comprises a first device attached to a first moving body and a second device attached to a second moving body. The first device comprises a control means which generates a control command including operation control information for controlling the operation of the device, and a communication means which outputs radio waves of a predetermined intensity and wirelessly transmits the control command within a distance range reachable by the radio waves of the predetermined intensity. The second device includes a communication means which wirelessly receives the control command and an operation execution means which executes operation according to the operation control information included in the wirelessly received control command.

Abstract: Provided herein are platforms for determining a non-navigational quality of at least one infrastructure by a plurality of autonomous or semi-autonomous land vehicles through infrastructure recognition and assessment.

Abstract: An unmanned aerial vehicle (UAV) having at least one sensor for detecting the presence of a survivor in a search and rescue area. The at least one sensor is preferably an ultra-wide band (UWB) transceiver sensor. The UAV includes a UAV data link transceiver for wirelessly communicating information concerning the survivor to a command center.

Abstract: An apparatus (1) for calibrating an ADAS sensor of an advanced driver assistance system of a vehicle (9) positioned in a service area (8), includes: a support structure (3); a vehicle calibration assistance structure (4), mounted on the support structure (3) and including a calibration device (41, 42) configured to facilitate aligning or calibrating the ADAS sensor of the vehicle (9); a positioning system; a computer (102), having access to a database (101) and configured to: receive one or more information items as input; query the database (101) to retrieve a reference parameter (111) and a geometric parameter (112) as a function of the input information; process the reference parameter (111) and the geometric parameter (112) to generate derived data (114) relating to a reference position of the vehicle calibration assistance structure (4).

Abstract: A vehicle includes a lane generator that is configured to receive information that describes a first lane portion and a second lane portion and determine that a discontinuity is present. The lane generator obtains a sensor output and detects presence of a nearby vehicle in the first lane portion. A classification for the nearby vehicle is identified by analyzing the sensor output, and is used to select a vehicle kinematics model. The lane generator determines paths for a simulated vehicle from the first lane portion to the second lane portion using the vehicle kinematics model. A third lane portion is determined based on the paths such that the third lane portion defines a traversable route from the first lane portion to the second lane portion in accordance with the vehicle kinematics model. An automated vehicle control system generates control outputs based in part on the third lane portion.

Abstract: Devices, systems, and methods are provided for enhanced sensor cleaning validation. A device may determine a baseline performance measurement associated with a clean performance baseline of a sensor. The device may actuate a cleaning mechanism to remove at least a portion of an obstruction deposited on the sensor. The device may determine a first post-clean performance measurement associated with the sensor. The device may determine a degradation measurement between the baseline performance measurement and the first post-clean performance measurement, wherein the degradation measurement indicates an effectiveness of the cleaning mechanism.

Abstract: An automatic parking system park autonomous driving vehicles in a target parking space in a parking lot by instructing the autonomous driving vehicle in the parking lot. The system includes: a failure type determination unit configured to determine a failure type from among a plurality of preset failure type candidates, when a vehicle-induced failure occurs in an automated vehicle under autonomous driving in accordance with the instruction, an evacuation space determination unit configured to determine an evacuation space based on the failure type determined by the failure type determination unit, the position information of the autonomous driving vehicle, and the parking lot map information, and a vehicle instruction unit configured to execute an evacuation instruction to evacuate the autonomous driving vehicle to the evacuation space.

Abstract: Systems and methods are described for performing one or more validity checks on potential trajectories for a device, such as an autonomous vehicle, to navigate. In some examples, a potential trajectory may be validated based on whether it is consistent with a current trajectory the vehicle is navigating such that the potential and current trajectories are not too different, whether the vehicle can feasibly or kinematically navigate to the potential trajectory from a current state, whether the potential trajectory was punctual or received within a time period of a prior trajectory, and/or whether the potential trajectory passes a staleness check, such that it was created within a certain time period. In some examples, determining whether a potential trajectory is feasibly may include updating a set of feasibility limits based on one or more operational characteristics of statuses of subsystems of the vehicle.

Abstract: A driving load estimation apparatus can estimate the driving load of individual drivers in accordance with the driving environment. The driving load estimation apparatus can include a first VACP calculator configured to calculate a first VACP value based on information related to a driving environment of a vehicle and a correction value calculator configured to calculate a VACP correction value of each driver based on a steering operation in the driving environment. The driving load estimation apparatus estimates a driving load of the driver by correcting the first VACP value based on the VACP correction value.