152 results about "Stationary object" patented technology

The invention discloses a slow space driving anti-collision early warning method based on a risk field model, and the method comprises the steps: firstly constructing a potential energy field intensity model for static objects and road traffic markings in a slow shared space on an urban non-motor vehicle lane, and then constructing a kinetic energy field intensity model for non-motor vehicles driving on the urban non-motor vehicle lane, a behavior field intensity model is constructed for non-motor vehicle drivers driving on urban non-motor vehicle lanes, then potential energy field, kinetic energy field and behavior field force models in a risk field model are calculated, and finally a comprehensive risk field model is obtained. Based on field force vector analysis, the application path of the potential energy of the risk field in the shared space of the non-motor vehicles is defined, and a conflict evaluation index under the risk field theory is provided on the basis. The index can be used for dynamically identifying potential conflicts, and provides a basis for early warning and intervention of non-motor vehicles.

The invention discloses an occupied grid labeling method and device, and the method comprises the steps: extracting an inter-frame pose transformation matrix and a detection frame tracking identifier corresponding to time sequence data when multiple frames of time sequence data are received; according to the inter-frame pose transformation matrix, carrying out occupied grid labeling on a static object in the time sequence data, and generating a static labeling result; tracking the position of the detection frame in each frame of time sequence data in real time according to the detection frame tracking identifier, and constructing a motion track of a target to which each detection frame belongs; in each frame of time sequence data, carrying out occupied grid labeling on the region where each motion track is located, and generating a motion labeling result; and fusing the static labeling result and the motion labeling result to generate an occupied grid labeling result corresponding to the time sequence data. Therefore, the occupancy grid label of the static object is propagated in combination with the inter-frame pose transformation matrix, and meanwhile, by fusing the occupancy grid label of the static object and the occupancy grid label of the motion trail, the requirements of the occupancy grid label for efficiency, precision and generalization are effectively met.

A method and device for vehicle camera autocalibration during vehicle travel for driver assistance systems and automated driving. A vehicle camera images a region of vehicle surroundings through a window. The method includes: providing a vehicle camera projection model including multiple extrinsic parameters, at least one intrinsic vehicle camera parameter and at least one window parameter; capturing a sequence of camera images during vehicle cornering; determining a curve type during the cornering; estimating the parameters using pixels in the sequence of images of stationary objects in the vehicle surroundings, the current vehicle movement, and the determined curve type, by minimizing an error function indicating the deviation between pixels which correspond to stationary objects in the vehicle surroundings and which are established from the sequence of images and pixels of the stationary objects which are projected by the projection model; and outputting at least one of the estimated parameters.

Methods and apparatus for monitoring user performance in launching objects at sporting events are described. A described method includes capturing, with a camera on glasses worn by a player participating in a sporting event, a plurality of two-dimensional (2-D) images of an object launched by a player participating in the sporting event. The launched object is identified and tracked with the camera for which an orientation is determined using an accelerometer. Based on the tracking, a position of the launched object at a point along a trajectory relative to a stationary object is determined, and an output indicative of user performance is provided based on the determined position of the launched object.

A driver assist apparatus includes one or more processors configured to collectively provide instructions of settings with group, the settings being set to driver assist functions included in the group, and the group being configured so that the driver assist function of a vehicle is allowed to be added to or deleted from the group, wherein a plurality of the driver assist functions included in the group, to which the instructions are provided, is a driver assist function group including at least a function concerned with alert in a case where the vehicle approaches an obstacle and a function concerned with detection of a stationary object around when parking.

The invention discloses an active sonar target identification method based on message passing multi-hypothesis tracking, and belongs to the technical field of underwater target detection. The method comprises the following steps: firstly, processing single-cycle sonar data by using adaptive constant false alarm detection, obtaining observation points, and forming an effective observation set through hierarchical clustering; thirdly, extrapolating the existing target, calculating the association probability of the existing target and the current observation by adopting a message passing method, and generating a plurality of groups of association hypotheses; then, the target state is corrected through Kalman filtering, target rejection and new management are executed, and a high-probability hypothesis is reserved; and finally, estimating the motion speed based on the target multi-period position sequence, and distinguishing a static object from a suspicious motion target according to a speed threshold. Through the multi-hypothesis tracking and probability message passing mechanism, clutter interference and static target influence in a complex underwater environment are effectively overcome, and the stability of target tracking, the accuracy of speed estimation and the overall reliability of system identification are remarkably improved.

The present application relates to an apparatus for determining the ego-motion of a radar apparatus, the apparatus configured to: process radar-point-cloud information comprising a plurality of points by neural network models, the processing comprising: pointwise mapping the features thereof to a greater number of mapped-features to provide mapped-radar-point-cloud information, determining a global feature vector indicative of characteristics of the mapped-radar-point-cloud information, generating a feature matrix wherein each point therein is characterized by a feature-set based on a combination of the features, the mapped-features and the global feature vector, determining a pointwise-weight representing a likelihood that the point represents a stationary object in the space, a pointwise-offset comprising a correction to be applied to the Doppler velocity measurement to at least reduce the Doppler velocity measurement for points having a greater than expected Doppler velocity, and providing an estimate of the motion of the radar apparatus.

The utility model discloses intelligent sensing radar monitoring equipment, and relates to the technical field of monitoring equipment, the radar monitoring equipment comprises a shell, and the interior of the shell is hollow; the monitoring camera is fixedly arranged on the shell and is used for monitoring a preset monitoring area; the circuit board is fixedly arranged in the shell, and a radar sensing device and a main control device are arranged on the circuit board; the radar sensing device is used for sensing a moving object or a static object in the predetermined monitoring area, and the main control device is connected with the monitoring camera and the radar sensing device through different interfaces and is used for sending the moving object or the static object to the radar sensing device under the condition that the radar sensing device senses an object of a preset type. And controlling the monitoring camera to start video recording. The utility model aims to improve the sensing accuracy of the sensing monitoring equipment.

This route acquisition system includes: a plurality of marks for identifying installation positions, the plurality of marks being provided at different positions in a travel passage or on a stationary object in the vicinity of the travel passage; a sensor that is mounted on a moving body and reads the marks; and a route acquisition device that, on the basis of the result of reading by the sensor, detects a passing position and a passing time of the moving body and acquires the travel route of the moving body.

A computer-implemented method is provided for estimating velocity of a moving object. The method includes receiving an image, which includes a first strip generated by a first sensor and a second strip generated by a second sensor, and recognizing a moving object in the first strip of the image. The method also includes selecting a plurality of stationary objects that are captured with the moving object in the first strip of the image, while excluding stationary object(s) in the second strip of the image, wherein the plurality of stationary objects are non-moving features. The method further includes combining misregistration values for the plurality of stationary objects in the first strip of the image and calculating a velocity of the moving object, based on a raw velocity of the moving object and the combined misregistration values.

This traveling route deciding device includes: an obstacle information acquisition unit which acquires obstacle information at regular intervals; an obstacle determination unit which determines whether each obstacle is a moving object or a static object, for all obstacles acquired by the obstacle information acquisition unit; a moving object list update unit which, in a case where it is determined that the obstacle is a moving object, registers the obstacle in a moving object list; a traveling prohibited area update unit which, in a case where it is determined that the obstacle is a static object, registers an area including the obstacle as a traveling prohibited area; and a traveling route deciding unit which performs calculation for avoiding collision between the vehicle and each obstacle on the basis of the updated moving object list and traveling prohibited area without using the continued traveling prohibited area, thus correcting a preset traveling route.

The techniques and systems herein enable ghost object detection. Specifically, a reflection line is determined that indicates a potential reflection surface between a first mobile object and a second mobile object. If enough stationary objects are within a region of the reflection line, then it is determined whether one or more of the stationary objects within the region are within a distance of a reflection point. The expected velocity of the second object is then determined and checked against the velocity of the second object. If the expected velocity is close to the velocity, then the second object is determined to be a ghost object. By doing so, the system can effectively identify ghost objects in a variety of environments, allowing downstream operations to function as designed.

An apparatus and a mehtod may enable a user equipment (UE) to more accurately identify whether certain radar detected objects are non-road objects / non-traffic participants, hence those non-road objects / non-traffic participants may be excluded from being fused as road objects / traffic participants. This may improve the accuracy and performance of assisted / autonomous driving. A UE detects a set of objects using at least one radar and at least one camera. The UE obtains at least one of: (1) a first indication of a first subset of objects in the set of objects being overridable or underridable based on a radar detection, or (2) a second indication of a second subset of objects in the set of objects being stationary based on a camera detection. The UE identifies a set of traffic-related objects in the set of objects based on at least one of the first indication or the second indication.

The present invention relates to a driving assistance device, a driving assistance method, and a program product, the driving assistance device including one or more processors configured to perform instructions of setting in a unified manner for a group, the setting being a setting for a driving assistance function of a vehicle included in the group, and the setting being a setting for a driving assistance function of the vehicle included in the group. The group is configured so that a driving assistance function can be added to the group or deleted from the group. The plurality of driving assistance functions included in the group on which the instruction has been made are a driving assistance function group including at least a function pertaining to an alarm when the vehicle approaches an obstacle and a function pertaining to a function pertaining to detection of a surrounding stationary object when the vehicle is parked.

The invention relates to a method for controlling an automatic overtaking manoeuvre involving a lateral lane change for passing a stationary object (340) in the current lane. The method comprises determining a necessary first maximum deceleration value (130) for braking in order, in the course of a first execution variant of the lane change, to come to a standstill at a predefined first relative distance (136) in front of the obstacle (340) in the current lane (370) before the lateral lane change is executed. Furthermore, a necessary second maximum deceleration value (132) for the lateral lane change in the course of a second execution variant of the lane change is determined, without coming to a standstill in front of the obstacle (340) in the current lane (370). The first maximum deceleration value (130) is compared with the second maximum deceleration value (132), and the execution of the lateral lane change is controlled in accordance with one of the two execution variants of the lane change according to a result of the comparison.

A system and method for providing ride assist in a vehicle (100), the system comprises of a plurality of transceiver (102) disposed on the vehicle (100), which is configured to detect at least one of a stationary object (108a) or a 5 moving object (108b). A control unit (104) communicatively coupled with the plurality of transceiver (102). The control unit (104) is configured to determine at least one of a vehicle (100) running data and an environmental data based on inputs from the plurality of transceiver (102) and analyse the vehicle (100) running data to determine at least one condition for performing 10 an overtake manoeuvre by the vehicle (100). A display unit (106), configured to display, to a user of the vehicle (100), an alert indicative of a safe overtake manoeuvre or an unsafe overtake manoeuvre based on the at least one condition.

[PROBLEM] Provided are a light detection device for accurately focusing by using an event signal while imaging a stationary object, an electronic apparatus, and a control method of the light detection device. [SOLUTION] A light detection device according to one aspect disclosed herein comprises: a light reception unit that photoelectrically converts incident light to generate an electric signal; a conversion circuit that converts the electric signal into a voltage signal; a first buffer circuit that outputs a first detection signal corresponding to the voltage signal; a second buffer circuit that outputs a second detection signal corresponding to an arbitrary first pseudo signal that does not depend on the voltage signal; and a subtractor that outputs a first output signal when the first or second detection signal exceeds a first threshold voltage higher than the first or second detection signal, and outputs a second output signal when the first or second detection signal is below a second threshold voltage lower than the first or second detection signal.

The vehicle-mounted object recognition device is mounted on a vehicle having an imaging unit. A calculation device of a vehicle-mounted object recognition device detects a stationary object on the basis of an image captured by an imaging unit, estimates a torque arm length, which is the distance from the center of rotation of a vehicle to the imaging unit, and determines the ground speed of the object on the basis of the estimated torque arm length.

An apparatus to be viewed by a driver to aid parking a car parallel to the walls of a garage, as well as the correct distance into the garage. The driver is able to park in exactly the same spot each time, at the desired distance from other cars, walls, or other stationary objects via the aid apparatus. This helps minimize banging car doors on objects upon opening, or bumping into anything in front of the vehicle, while maximizing use of space within the garage. The apparatus is installed in a fixed position in front of the driver at eye level as they sit comfortably in a driver's seat of the vehicle. As the driver drives their car into their garage to park, they are guided by visual cues from the apparatus to park the car in the same footprint on the floor each time.

The invention relates to a method for detecting false detection situations of a vehicle ultrasonic sensor (9). In this method, first sensor signals recorded at the beginning of a parking period are compared with second sensor signals recorded at the end of the parking period from the ultrasonic sensor (9) for static objects (2, 7) in the immediate vicinity. If this comparison reveals a deviation of the second sensor signals from the first sensor signals, it is concluded that the ultrasonic sensor (9) is covered with snow, and a predetermined safety measure is executed. The invention also relates to an assistance system (11) for carrying out the method and a correspondingly equipped motor vehicle (4).

The invention relates to a computer-implemented method for determining and learning vehicle parameters of an ego vehicle (V) in the ego vehicle (V), comprising the following steps: - Recording (S1) a series of environmental representations of the environment of the ego vehicle (V) using at least one environmental sensor (2) during a defined period at different time steps; - Measuring (S2) the wheel rotation angle with at least one wheel speed sensor (3) during the defined period at different time steps; - Identifying (S3) features (6) of stationary objects (5a-5d) by analyzing the series of environment representations; - continuous localization (S4) of the ego vehicle (V) based on the detected features (6) of the stationary objects (5a-5d) at the different time steps; - Generating (S5) a first trajectory (T1) driven by the ego vehicle (V) based on the continuous localization of the ego vehicle (V); - Generating (S6) a second trajectory (T2) by calculating the distance traveled using the measured wheel rotation angles and known vehicle parameters; - Comparing (S7) the first (T1) and the second trajectory (T2) and determining deviations between the two trajectories (T1, T2); - Setting (S8) at least one of the trajectories (T1, T2) to adapt it to the other trajectory, and generating a set trajectory (TA); - Calculating (S9) vehicle parameters; - Learning (S10) the calculated vehicle parameters by updating the known vehicle parameters.

Turning assistance device (2) as a retrofit solution for a vehicle (1) for retrofitting the vehicle (1) with the turning assistance device (2), comprising a radar sensor device (3) and a control device (4), wherein the radar sensor device (3) is configured to - to detect an object (10) and its relative position (11) with respect to the vehicle (1) in a predetermined spatial detection area (8) in an external environment of the vehicle (1) according to a predetermined detection method, characterized in that the control device (4) is configured to - to classify the object (10) as a road user (6) using a predetermined classification procedure, and - to issue a warning signal (12) when the object (10) classified as a road user (6) is located in a predetermined spatial danger zone (7) related to the vehicle (1), wherein a warning is only issued if the object (10) in the danger zone (7) is the road user (6), and that the control device (4) is configured to - to determine a relative motion (16) of the object (10) with respect to the vehicle (1) according to a predetermined motion determination procedure, - to classify the object (10) as either a stationary object (17) or a dynamic object (18) using a predetermined determination procedure, and - to determine a movement (19) of the vehicle (1) from the relative movement (16) of at least one object (10) classified as a stationary object (17), so that the turning assistance device (2) can independently determine the movement (19) of the vehicle (1).

The driving assistance device 1 controls the notification device 30 to issue a predetermined alert to the occupants of the own vehicle if, at a first point in time, it detects the existence of a first driving lane L1 adjacent to the lane L0 in which the own vehicle is traveling, and no stationary object is present in a predetermined area R[n+10] located ahead of the own vehicle in that first driving lane L1, and then, at a second point in time after the first point in time, when the own vehicle is positioned on the side of this predetermined area, it detects the presence of a solid object OB within said area and that the distance Δd between this solid object OB and the own vehicle is less than a threshold.

The present disclosure relates to an object recognition apparatus and method, and the object recognition apparatus includes a sensor and a processor. The processor may determine, based on sensing information of the sensor, longitudinal position information, and lateral position information, determine, lane information determine whether at least one other object, which is different from the object and which is identified as a moving object or a stationary object, is located within the lane in which the object is located, assign a reliability value to the object, wherein a first value corresponds to the reliability value for the object based on the at least one other object being located within the lane in which the object is located, or a second value smaller than the first value as the reliability value, and determine the object as a moving object or a stationary object.

A method for monitoring user performance in launching objects at sporting events includes capturing, with an image sensor on glasses worn by a user at a sporting event, two-dimensional (2-D) images of an object launched by a player participating in the sporting event. The launched object and a stationary object at the sporting event are identified. An orientation of the image sensor is determined based on a shape of the stationary object within the 2D images, and locations of the launched object in 3D space are determined based on the 2D images and the determined orientation of the image sensor. The trajectory of the launched object in 3D space is then determined, and the trajectory is used to determine a parameter indicative of a performance of the player for the sporting event. Feedback indicative of the performance of the player is then provided based on the determined parameter.

Methods and systems are disclosed for employing an ultrasonic sensor to estimate a range for a moving object. At least one processor separates returned signals received by an ultrasonic transducer into a stationary object signal and a moving object signal. A gain is determined based at least in part on the stationary object signal. The stationary object signal is combined with the moving object signal using the gain and then filtered. The range for the moving object is estimated using the filtered combined stationary and moving object signal.

The present invention executes: first angular error estimation processing (S40) for determining an estimated first angular error value obtained by estimating an angular error in a radar device using azimuthal dependence of relative velocity with respect to a stationary object; second angular error estimation processing (S50) for calculating a stationary object movement direction in which the stationary object moves when viewed from a moving body if the moving body is assumed to be travelling straight, calculating the next distance to the stationary object at the next azimuth on the basis of the movement direction average value and the distance to the stationary object, calculating a true estimated angle value on the basis of the next distance and a reference movement direction in which the stationary object moves when there is no angular error, and determining an estimated second angular error value on the basis of the difference between the true estimated angle value and the next azimuth; and angular error integration processing (S60) for using the estimated first angular error value and / or the estimated second angular error value to estimate an angular error in an object detected by the radar device.

To reduce an operation amount required for estimating a three dimensional field.SOLUTION: The image processing apparatus 102 according to the present disclosure acquires a plurality of captured images obtained by imaging from a plurality of directions, sets, for each object, a three dimensional space including the object as a learning space on the basis of the plurality of captured images, and learns, for each set learning space, a three dimensional field corresponding to the learning space on the basis of the plurality of captured images. Here, when the image processing apparatus 102 learns a three dimensional field corresponding to a learning space based on a plurality of captured images obtained by synchronized imaging at a certain time point, for a learning space in which an object included in the learning space is a stationary object, the image processing apparatus 200 learns a feature amount of a three dimensional field corresponding to a learning space including a moving object using a feature amount of a three dimensional field already obtained as a result of learning based on a plurality of captured images obtained by synchronized imaging at another time point as a feature amount of a three dimensional field corresponding to the learning space.SELECTED DRAWING: Figure 4

The invention relates to the technical field of automotive electronics, and particularly discloses an angle self-calibration method and system for a vehicle-mounted millimeter-wave radar, and the method comprises the steps: collecting the measurement data of a static object in a view field range through the radar when a vehicle carrying the vehicle-mounted millimeter-wave radar runs in a straight line, the measurement data includes a measured azimuth angle and a relative velocity of each stationary object. According to the method, the key function is constructed by collecting the measurement data of the static object, the angle error coefficient and the vehicle speed error coefficient are jointly estimated in combination with the nonlinear least square method, the parameter estimation precision is improved through data optimization means such as azimuth interval classification and filtering smoothing, and finally accurate compensation of the radar measurement azimuth is achieved. The problem of error drift in the dynamic driving process of the millimeter wave radar can be effectively solved, the identification precision of the radar on static vehicles and roadside obstacles is improved, and the functional reliability of vehicle-mounted safety systems such as ACC and vehicle distance early warning is guaranteed.