A vehicle control device is mountable on a vehicle. The vehicle control device includes: a processor; and a memory storing instructions that, when executed by the processor, cause the vehicle control device to perform operations including: acquiring detection information obtained by detecting an obstacle around the vehicle; performing collision determination of evaluating a possibility of collision with the obstacle; generating, based on the detection information, information on an approaching object that is an obstacle approaching the vehicle and information on a detection point indicating an obstacle that does not move; estimating a position of a shielding object based on the information on the detection point; evaluating, based on the position of the shielding object and the information on the approaching object, a ghost likelihood indicating a possibility that the approaching object is a ghost; and excluding, based on the ghost likelihood, the approaching object from the collision determination.

An agricultural vehicle monitoring system includes one or more noncontact sensors configured to sense multiple objects along a scanline. A comparative vehicle monitor is in communication with the one or more noncontact sensors. The comparative vehicle monitor is configured to provide a specified row width and to identify one or more crop rows from the scan line and determine one or more lengths of scan line segments between identified crop rows. The comparative vehicle monitor is further configured to determine a vehicle position including one or more of a vehicle angle or a vehicle location according to the specified row width and the one or more determined lengths of scan line segments between the identified crop rows.

The present invention provides a sensor recognition integration device capable of preventing a rapid change in coordinates of an integrated object and preventing, for example, an erroneous determination in an autonomous driving plan determination device, even when the combination of sensors that perform detection changes. In the present invention, since an object position is estimated in a state where information of a position detected by a sensor that recognizes an object in an external field is corrected or changed, the rapid change of coordinates of an integrated object is prevented even when the combination of sensors that perform detection changes.

Provided is a vehicle tracking device capable of appropriately tracking a vehicle. The vehicle tracking device is a vehicle tracking device that tracks a target vehicle that travels at the periphery of a host vehicle. The vehicle tracking device includes: an estimation unit that estimates a rectangular frame approximating an external shape of the target vehicle on the basis of past data; and a specifying unit that specifies an advancing direction of the target vehicle on the basis of layout of contour data composed of a plurality of pieces of detection point data, which is detected by a sensor that is mounted to the host vehicle and detects a relative position of a detection target with respect to the host vehicle as the detection point data, and indicates a contour of the target vehicle, with respect to a reference side that is a side on the host vehicle side among sides of the rectangular frame along a vehicle width direction of the rectangular frame.

A method, system, and device for mobile robot operations. The method comprises a mobile robot comprising at least one sensor configured to capture data related to the robot's surroundings traveling on a pedestrian pathway. The method also comprises the mobile robot using the sensor to collect data relating to moving objects in the robot's surroundings. The method further comprises detecting at least one pedestrian within the collected data, said pedestrian moving with a motion pattern. The method also comprises analyzing the pedestrian's motion pattern to determine and output the pedestrian's intent. The system comprises at least one mobile robot configured to travel on pedestrian pathways. The robot comprises at least one sensor configured to capture data related to the robot's surroundings and to collect data relating to moving objects in said surroundings. The system also comprises at least one pedestrian detector. The pedestrian detector is configured to process the sensor data to at least detect a pedestrian moving with a motion pattern. It is also configured to analyze the pedestrian's motion pattern and determine and output the pedestrian's intent. The robot comprises at least one sensor configured to capture data related to the robot's surroundings and to collect data relating to moving objects in said surroundings. The robot also comprises at least one processing component configured to process the sensor data to at least detect a pedestrian moving with a motion pattern, and analyze the pedestrian's motion pattern, and determine and output the pedestrian's intent.

A method for monitoring a data fusion function of an infrastructure system for the infrastructure-supported assistance of motor vehicles during an at least semi-automated driving task within an infrastructure, the infrastructure including multiple infrastructure surroundings sensors for detecting an area of the infrastructure. The method includes: receiving multiple input data sets intended for the data fusion function, each of which includes surroundings data based on the respective detection of the area, which represent the detected area; receiving output data based on a data fusion of the input data sets, output by the data fusion function; checking the input data sets and/or the output data for consistency; outputting a check result of the check. A device, a computer program, and a machine-readable memory medium are also provided.

Various aspects of the subject technology relate to a mobile support platform for vehicle sensor calibration. The mobile support platform includes a chassis, lift posts on the chassis configured to interface with one or more lift points on a vehicle and raise the vehicle, and a set of wheels mounted to the chassis configured to carry the vehicle through a calibration sequence.

A digital self-injection-locked (SIL) radar includes a digital SIL oscillator, a wireless signal transceiver and a digital frequency demodulator. The digital SIL oscillator generates a digital output signal. The wireless signal transceiver is electrically connected to the digital SIL oscillator to convert the digital output signal into a wireless signal for transmission to a target, receives a reflected signal from the target, and converts the reflected signal into a digital injection signal for injection into the digital SIL oscillator. Accordingly, the digital SIL oscillator operates in an SIL state and generates a digital oscillation signal. The digital frequency demodulator is electrically connected to the digital SIL oscillator to receive and demodulate the digital oscillation signal into a digital demodulation signal.

The present disclosure provides a circuitry for radar detection data disambiguation for a mobile platform. The circuitry is configured to obtain radar detection data from a radar sensor mounted on the mobile platform, wherein the radar detection data indicate, for each of a plurality of targets, a radial velocity and an angle of arrival; estimate, based on the radar detection data, an ego-motion of the mobile platform; and determine an unambiguous radial velocity value of a target of the plurality of targets based on the ego-motion and the radar detection data.

A traffic monitoring assembly includes a roof rack that is mountable to a roof of a vehicle. A global positioning system transceiver is attached to the roof rack to receive global positioning system coordinates of the vehicle. A laser sensor is attached to the roof rack for detecting the distance between the vehicle and adjacent traffic vehicles traveling on the same roadway as the vehicle. An ultrasonic sensor is attached to the roof rack to capture ultrasonic sound waves reflected from objects near the vehicle. A camera is attached to the roof rack to capture imagery of the environment surrounding the vehicle. A radar sensor is coupled to the roof rack to emit a radar signal for detecting the speed of adjacent traffic vehicles travelling on the same roadway as the vehicle.