KR20180124713A - An electronic device and method thereof for estimating shape of road - Google Patents

Abstract

Disclosed is a method for estimating a shape of the road by a running vehicle, comprising: determining whether the plurality of objects stop (stop) state on the basis of the relative speed vector with respect to a plurality of objects located in the vicinity of the vehicle; calculating an average vector of the relative speed vector of the object, respectively of the vehicle of at least one stationary state of the plurality of objects; and estimating a running speed and running direction of the vehicle by using a mean vector of the output; and estimating the shape of the road based on the running speed, the running direction, and the position for objects located in the vicinity of the vehicle with respect to the vehicle.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an electronic device for estimating a shape of a road,

The present invention relates to an electronic device for estimating the shape of a road and a method of operating the same. More particularly, the present invention relates to an electronic device included in a running vehicle and estimating the shape of a road around the vehicle, and an operation method thereof.

Research on autonomous vehicles is actively being carried out. An autonomous vehicle refers to a vehicle that uses one or more sensors to detect objects in a traveling path and can move to a desired destination while avoiding sensed objects.

For autonomous driving, it is necessary to estimate the shape of the road around the autonomous vehicle. The autonomous vehicle can estimate the running direction of the autonomous driving vehicle by receiving the yaw rate using the CAN communication in the steering device provided in the autonomous driving vehicle without using a separate sensor, There was a limit in terms of utilizing information about other objects.

Various embodiments can provide an electronic device included in a running vehicle to estimate the shape of a road around the vehicle and an operation method thereof.

As a technical means for achieving the above-mentioned technical object, a first aspect of the present disclosure is a vehicle control system for a vehicle, comprising: a plurality of objects stopping on the basis of relative velocity vectors of the plurality of objects, Determining whether the state is a state; Calculating an average vector of relative velocity vectors for each of at least one stationary object among the plurality of objects with respect to the vehicle; Estimating a traveling speed and a traveling direction of the vehicle using the calculated average vector; And estimating a shape of the road based on the traveling speed, the running direction, and the position of each of a plurality of objects located in the periphery of the vehicle with respect to the vehicle, Can provide a method of estimating the shape of the road.

Also, a second aspect of the present disclosure is a sensing device comprising: a sensing unit; A memory in which at least one program is stored; A communication unit for transmitting and receiving data to and from an external device; And at least one processor for estimating the shape of the road by executing the at least one program, wherein the at least one program is based on at least one of relative speed vectors for each of a plurality of objects located around the vehicle, Determining whether the plurality of objects is in a stop state; Calculating an average vector of relative velocity vectors for each of at least one stationary object among the plurality of objects with respect to the vehicle; Estimating a traveling speed and a traveling direction of the vehicle using the calculated average vector; And estimating a shape of the road based on the running speed, the running direction, and the position of each of a plurality of objects located in the periphery of the vehicle with respect to the vehicle , And an electronic device included in the running vehicle to estimate the shape of the road can be provided.

In addition, the third aspect of the present disclosure can provide a computer-readable recording medium on which a program for causing a computer to execute the method of the first aspect is recorded.

1 is a schematic diagram for explaining a method of estimating a shape of a road by an electronic device according to an embodiment.
2 is a flowchart showing a process of estimating the shape of a road by an electronic device according to an embodiment.
FIG. 3 is a flowchart illustrating a process of estimating the shape of a road according to an embodiment of the present invention.
4 is a flow chart illustrating the process of estimating the shape of a road according to another embodiment of the present invention.
5 is a diagram for explaining a process of estimating a running speed and a running direction of a vehicle according to an embodiment of the present invention.
6 is a diagram showing information about an object around the vehicle, which is obtained by the electronic device according to the embodiment.
7 and 8 are block diagrams showing the configuration of an electronic device according to some embodiments.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, which will be readily apparent to those skilled in the art. However, the disclosure may be embodied in many different forms and is not limited to the embodiments described herein. In order to clearly illustrate the invention in the drawings, parts not related to the description are omitted, and like parts are denoted by like reference numerals throughout the specification.

The terms used in the specification may be used to describe various components, but the components should not be limited by terms. Terms are used only for the purpose of distinguishing one component from another.

Throughout the specification, when a part is referred to as being "connected" to another part, it includes not only "directly connected" but also "electrically connected" with another part in between . Also, when a part is "connected" to another part, it includes a case where a part is in a state capable of performing data communication with another part and signal transmission / reception.

Also, when an element is referred to as " comprising ", it means that it can include other elements as well, without departing from the other elements unless specifically stated otherwise.

The accompanying drawings may be schematically illustrated to illustrate one embodiment of the invention, and some dimensions may be exaggerated for clarity. Similarly, a substantial portion of the figures may be expressed arbitrarily.

The term " module " as used in the disclosure should be interpreted as including software, hardware, or a combination thereof, depending on the context in which the term is used. For example, the software may be machine language, firmware, embedded code, and application software. As another example, the hardware may be a circuit, a processor, a computer, an integrated circuit, an integrated circuit core, a sensor, a micro-electro-mechanical system (MEMS), a passive device, or a combination thereof.

The terminology used in the description is used only to describe a specific embodiment and is not intended to limit the invention. Although the terminology used in the present invention selects general terms that are widely used in the present invention while considering the functions in the invention, it may vary depending on the intention of the artisan, the precedent, or the emergence of new technology. Also, in certain cases, there may be a term selected arbitrarily by the applicant, in which case the meaning thereof will be described in detail in the description of the corresponding invention. Therefore, the term used in the invention should be defined based on the meaning of the term, not on the name of a simple term, but on the entire contents of the invention.

The singular expressions include plural expressions unless the context clearly dictates otherwise. In the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

The embodiments described in the disclosure and the accompanying drawings are for explaining the invention through some of the various embodiments of the invention, and the invention is not limited to the embodiments described in the disclosure and the accompanying drawings.

In the present specification, the term " autonomous driving " may mean that a vehicle uses one or more sensors to detect objects present in a traveling path, and moves to a desired destination by avoiding sensed objects.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will now be described in detail with reference to the accompanying drawings.

1 is a schematic diagram for explaining a method of estimating a shape of a road by an electronic device according to an embodiment.

As used herein, the term " electronic device " may refer to an apparatus included in a running vehicle 100 to estimate the shape of the road 120. [ The electronic device may be, but is not limited to, a device installed in the vehicle 100, for example the electronic device may mean the vehicle 100 itself. The vehicle 100 may be an autonomous vehicle, but is not limited thereto.

The electronic device according to one embodiment may obtain information about a plurality of objects located in the periphery of the vehicle 100. [ The plurality of objects may be, for example, trees, electric poles, etc. shown in Fig.

More specifically, the electronic device can sense through the sensing unit a plurality of signals relating to each of a plurality of objects located within a predetermined distance from the vehicle being driven. A signal relating to an object may mean, for example, a radar signal sensed by an electronic device, but is not limited thereto. The electronic device can acquire the position information of the plurality of objects, the size information, the relative velocity vectors of the plurality of objects with respect to the vehicle 100, and the intensity of the plurality of signals by analyzing the plurality of sensed signals.

The electronic device according to one embodiment uses the relative velocity vectors of the plurality of objects located in the periphery of the vehicle 100, the size information of the plurality of objects, and the intensity of the plurality of signals, Objects can be classified.

For example, an electronic device can first classify a plurality of objects based on size information of a plurality of objects. Next, the electronic device can classify a plurality of objects that are primarily classified based on the relative velocity vectors of the plurality of objects located in the periphery of the vehicle 100, relative to the vehicle 100. Then, the electronic device can classify a plurality of objects that are secondary classified by tertiary using the intensity of a plurality of signals.

The electronic device according to one embodiment can estimate the shape of the road 120 using relative velocity vectors for the vehicle 100 of each of a plurality of objects located in the vicinity of the vehicle 100. [ FIG. 1 is an enlarged view of an example of a user interface screen 110 of an electronic device for estimating the shape of the road 120. FIG. Referring to the shape of the road 120 estimated by the electronic device displayed on the user interface screen 110, the vehicle 100 can perform autonomous driving. When the vehicle 100 is not an autonomous vehicle, the user can operate the vehicle 100 by referring to the user interface screen 110. [

The user interface screen 110 of FIG. 1 displays only the road 120 and the vehicle 100, but the embodiment is not limited thereto. For example, the user interface screen 110 may display other vehicles on the road 120, and may also display a plurality of objects around the vehicle 100.

2 is a flowchart showing a process of estimating the shape of a road by an electronic device according to an embodiment.

In step 210, the electronic device can determine whether a plurality of objects are stationary, based on the relative velocity vectors for the vehicle 100 of each of a plurality of objects located in the periphery of the vehicle 100. [

An electronic device according to an embodiment may obtain relative velocity vectors for the vehicle 100 of each of a plurality of objects located in the vicinity of the vehicle 100. [ More specifically, the electronic device can obtain relative velocity vectors for the vehicle 100 of each of a plurality of objects located within a predetermined distance from the vehicle 100. [

For example, an electronic device may obtain relative velocity vectors for a first tree, a second tree, and a sign on a vehicle located within a radius of 100 meters from the vehicle. The relative velocity vectors for the vehicle may be expressed as a two-dimensional vector or a three-dimensional vector, but are not limited thereto.

The electronic device according to an embodiment can determine whether a plurality of objects are in a stop state based on the obtained relative velocity vectors.

For example, if the relative velocity vector of the first object with respect to the vehicle 100 is similar to the origin vector symmetric to the current velocity vector of the vehicle 100 estimated using the steering system, It can be determined that the first object is in a stopped state.

In yet another example, the electronic device can determine whether the second object is in a stationary state, based on an index indicated in the radar signal of the second object.

In step 220, the electronic device may calculate an average vector of relative velocity vectors for the vehicle 100 of each of at least one stationary object of the plurality of objects.

The electronic device according to the embodiment can calculate the average vector of the relative velocity vectors for the vehicle 100 of each of the at least one stationary object at a plurality of points of time. The minimum unit of the inter-view interval may be a predetermined time value. For example, the second point of time, which is the earliest point of time after the first point in time, may come after a preset time from the first point of time.

The electronic device according to an embodiment is configured to track a change in position of an object located on the road 120 among at least one non-stop object among a plurality of objects through a trace algorithm . Information about the positional change of the object located on the road 120 tracked by the tracking algorithm can be used for autonomous driving of the vehicle 100. [

In step 230, the electronic device can estimate the running speed and running direction of the vehicle using the calculated average vector.

The electronic device can estimate the shape of the road 120 based on the traveling speed of the vehicle 100, the direction of travel, and the position of each of a plurality of objects located in the periphery of the vehicle 100 with respect to the vehicle have.

FIG. 3 is a flowchart illustrating a process of estimating the shape of a road according to an embodiment of the present invention.

Here, the description overlapping with the description of FIG. 2 will be briefly described.

In step 310, the electronic device can determine whether a plurality of objects are stationary, based on the relative velocity vectors for the vehicle 100 of each of a plurality of objects located in the periphery of the vehicle 100. [

In step 320, the electronic device may calculate an average vector of relative velocity vectors for the vehicle 100 of each of at least one stationary object of the plurality of objects.

In step 330, the electronic device can calculate the running vector of the vehicle 100 by making the calculated average vector symmetrical to the origin.

Alternatively, the electronic device moves the start point of the calculated mean vector to the origin of the predetermined two-dimensional vector space, and calculates the travel vector of the vehicle 100 by symmetricizing the mean vector shifted to the origin with respect to the origin .

For example, the running vector of the vehicle 100 may be indicative of the running speed and running direction of the vehicle 100. [

In step 340, the electronic device can estimate the shape of the road based on the running vector of the vehicle 100 and the position of each of a plurality of objects located in the periphery of the vehicle 100 with respect to the vehicle.

An electronic device according to an embodiment can calculate an average vector of a plurality of average vectors calculated at a plurality of time points. Also, the electronic device may perform extrapolation using at least one vector having a degree of similarity to a mean vector of average vectors calculated at a plurality of points of time from a plurality of average vectors calculated at a plurality of points of time, The shape of the road 120 can be estimated. A more detailed description will be given later with reference to FIG.

The electronic device according to an embodiment can identify at least one object continuously positioned within a predetermined distance from the vehicle 100 at a first point of time and a second point of time of the plurality of points of time. In addition, the electronic device can track the positional change of the identified at least one object through a tracking algorithm. In addition, the electronic device can correct position information based on tracking.

4 is a flow chart illustrating the process of estimating the shape of a road according to another embodiment of the present invention.

Here, the description overlapping with the description of FIG. 2 or FIG. 3 will be briefly described.

In step 410, the electronic device can determine whether a plurality of objects are stationary, based on the relative velocity vectors for the vehicle 100 of each of a plurality of objects located in the vicinity of the vehicle 100. [

In step 420, the electronic device may calculate an average vector of relative velocity vectors of the at least one stationary object of the plurality of objects with respect to the vehicle 100 at a plurality of points in time.

In step 430, the electronic device may calculate an average vector of a plurality of mean vectors calculated at a plurality of points in time.

For example, if the average vector calculated at the first time point is (5, 11), the mean vector calculated at the second time point is (6, 8) , The electronic device can calculate the average vectors (4, 7) of a plurality of average vectors calculated at the first time point to the third time point.

In step 440, the electronic device calculates an average value of a plurality of average vectors calculated at a plurality of points of time using an extrapolation method using at least one vector whose similarity to average vectors of average vectors calculated at a plurality of points of time is equal to or greater than a predetermined threshold value. The shape of the road 120 can be estimated.

In other words, the electronic device applies the method of least squares to a plurality of average vectors calculated at a plurality of points of view to remove different vectors, and then applies the extrapolation method using the remaining vectors, Can be estimated.

For example, the electronic device may include an average vector (5, 11) calculated at a first time point, an average vector (6, 8) calculated at a second time point, (5, 11) calculated at the first point in time, at which the degree of similarity to the mean vectors (4, 7) of the mean vectors calculated at the first point of time to the third point of time is equal to or greater than a predetermined threshold, The shape of the road 120 can be estimated by applying the extrapolation method using the average vectors 6 and 8 calculated at the time point.

5 is a diagram for explaining a process of estimating a running speed and a running direction of a vehicle according to an embodiment of the present invention.

5 is a diagram for explaining a process of estimating the running speed and the running direction of the vehicle 500. FIG. The vehicle 500 includes an electronic device for estimating a running speed and a running direction. On the road 10, there are three vehicles 505, 510, 515 in addition to the vehicle 500.

A vehicle 500 having a speed vector 520 and a plurality of objects around the vehicle 500 have a relative speed with each other. The electronic device according to an embodiment can use relative velocity vectors 555, 560, and 565 for the vehicle 500 of each of the stationary objects among the plurality of objects to estimate the shape of the road 10 . The electronic device can calculate an average vector of relative velocity vectors 555, 560, and 565 of the plurality of objects with respect to the vehicle 500 of each of the stationary objects and calculate the average vector of the vehicle 500 using the calculated average vector. It is possible to estimate the running vector 570 of the vehicle. The electronic device can estimate the shape of the road 10 based on the running vector 570 of the estimated vehicle 500. [

The relative velocity vectors 540, 545 and 550 for the vehicle 500 of each of the three vehicles 505, 510 and 515 other than the vehicle 500 are set such that the velocity of each of the three vehicles 505, 510 and 515 Can be calculated using the vectors 525, 530, and 535 and the velocity vector 520 of the vehicle 500. Since the three vehicles 505, 510 and 515 are non-stationary objects, the relative speed vectors 540, 545 and 550 of the three vehicles 505, 510 and 515, respectively, 500 are not used in the process of estimating the traveling vector 570 of the vehicle. However, the electronic device can track the change in the position of the object (i.e., three vehicles 505, 510, 515) located on the road 10 among the non-stationary objects through the tracking algorithm. Information regarding the change in the positions of the three vehicles 505, 510, and 515 can be used when the vehicle 500 makes autonomous travel.

6 is a diagram showing information about an object around the vehicle, which is obtained by the electronic device according to the embodiment.

6 shows information on the position, relative speed, object size, and signal size of a plurality of objects (object 1, object 2, ..., object 9, ...) .

The electronic device according to an embodiment can classify a plurality of objects in a primary classification based on size information of a plurality of objects. For example, the electronic device can include objects 1 and 2 having the length of 1 and the width of 2 in the same group through the primary classification.

Further, the electronic device can classify a plurality of objects that are primarily classified based on the relative speed of each of the plurality of objects with respect to the vehicle 100. Taking the objects 1 and 2 in FIG. 6 as an example, the relative speed in the X-axis direction of -1.25 and the relative speed in the X-axis direction of -2 of the object 2 are similar to each other. 8.875 and the Y-axis direction relative speed -9 of the object 2 are similar to each other, the electronic device can include the object 1 and the object 2 in the same group even in the secondary classification.

Further, the electronic device can classify a plurality of objects, which are secondary classified, into tertiary based on the intensity of a plurality of signals. For example, the electronic device can include object 1 and object 2 in Fig. 6 in different groups through tertiary classification. The RCS (Radar Cross Section), which is the intensity of the signal of the object 1, is -3.5, which is different from the RCS 1.5 of the object 2.

Based on the above-described primary, secondary and tertiary classification criteria, the electronic device can classify a plurality of objects into at least one group. Objects belonging to each classified group may be of the same type, but are not limited thereto.

7 and 8 are block diagrams showing the configuration of an electronic device according to some embodiments.

The components of the electronic device 700 shown in Figures 7 and 8 may perform the operations of the electronic device 700 described above in Figures 1-6. Therefore, the detailed description overlapping with the description of FIGS. 1 to 6 will be omitted or simplified.

7, an electronic device 700 according to an embodiment may include a processor 740, a communication unit 730, a memory 720, and a sensing unit 710. However, not all of the components shown in Fig. 7 are essential components of the electronic device 700. Fig. The electronic device 700 may be implemented by more components than the components shown in FIG. 7, or the electronic device 700 may be implemented by fewer components than the components shown in FIG.

8, an electronic device 700 according to some embodiments includes, in addition to the processor 740, the communication unit 730, the memory 720, and the sensing unit 710 shown in Fig. 7 An output unit 770, a user input unit 750, and a driver 760.

The sensing portion 710 may include a plurality of sensors configured to sense information about the environment of the electronic device 700 and may include one or more actuators configured to modify the position and / . For example, the sensing unit 710 may include a GPS (Global Positioning System) 711, an IMU (Inertial Measurement Unit) 712, a RADAR sensor 713, a LIDAR sensor 714, an image sensor 715, A proximity sensor 717, an RGB sensor 718, and a motion sensing unit 719. The proximity sensor 717, the RGB sensor 718,

The image sensor 715 may comprise a camera, a stereo camera, a mono camera, a wide angle camera, or a 3D vision sensor, according to one embodiment.

In addition, the environmental sensor 716 may include at least one of a temperature / humidity sensor 716-1, an infrared sensor 716-2, an air pressure sensor 716-3, and a dust sensor 716-4 , But is not limited thereto.

For example, the environmental sensor 716 may further include an ultrasonic sensor. The ultrasonic sensor may be a sensor configured to sense short-range obstacles from the electronic device 700 using an echo signal that is output by outputting ultrasonic waves.

The sensing unit 710 may be a combination of the image sensor 715 and the RADAR sensor 713 or may be a combination of the image sensor 715 and the LIDAR sensor 714. The function of each sensor can be intuitively deduced from the name by those skilled in the art, so a detailed description will be omitted.

The motion sensing unit 719 can sense the motion of the electronic device 700. [ The motion sensing unit 719 may include a magnetic sensor 719-1, an acceleration sensor 719-2, and a gyroscope sensor 719-3.

The GPS 711 may be a sensor configured to estimate the geographic location of the electronic device 700. That is, the GPS 711 may include a transceiver configured to estimate the position of the electronic device 700 relative to the earth.

IMU 712 may be a combination of sensors configured to sense position and orientation changes of electronic device 700 based on inertial acceleration. For example, the combination of sensors may include accelerometers and gyroscopes.

The RADAR sensor 713 may be a sensor configured to sense objects within the environment in which the electronic device 700 is located using a wireless signal. In addition, the RADAR sensor 713 can be configured to sense the velocity and / or direction of objects.

The LIDAR sensor 714 may be a sensor configured to measure the distance to an object by analyzing the light reflected on the object, using Near Infrared (NIR). The data measured by the LIDAR sensor 714 can be used to implement a three-dimensional image. Further, in one embodiment, the LIDAR sensor 714 may be a sensor configured to use laser to sense objects within the environment in which the electronic device 700 is located. More specifically, the LIDAR sensor 714 may include a laser light source and / or a laser scanner configured to emit a laser, and a detector configured to detect the reflection of the laser. The LIDAR sensor 714 may be configured to operate in coherent (e.g., using heterodyne detection) or in an incoherent detection mode.

The image sensor 715 may be a still camera or a video camera configured to record the environment outside the electronic device 700. [ For example, the image sensor 715 may include multiple cameras, and multiple cameras may be located at multiple locations on the interior and exterior of the electronic device 700.

The memory 720 may store a program for processing and control of the processor 740 and may store data input to or output from the electronic device 700. [

The memory 720 may be a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (e.g., SD or XD memory), a RAM (Random Access Memory) SRAM (Static Random Access Memory), ROM (Read Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory) , An optical disc, and the like.

The programs stored in the memory 720 can be classified into a plurality of modules according to their functions. For example, the programs can be classified into a UI module 721, a touch screen module 722, a notification module 723, .

The UI module 721 can provide a specialized UI, a GUI, and the like, which are interlocked with the electronic device 700 for each application. The touchscreen module 722 may detect a touch gesture on the user's touch screen and pass information to the processor 740 about the touch gesture. The touch screen module 722 according to one embodiment may recognize and analyze the touch code. The touch screen module 722 may be configured as separate hardware including a controller.

The notification module 723 may generate a signal for notifying the occurrence of an event of the electronic device 700. [ Examples of events generated in the electronic device 700 include call signal reception, message reception, key signal input, schedule notification, and the like. The notification module 723 may output a notification signal in the form of a video signal through the display unit 771 or may output a notification signal in the form of an audio signal through the sound output unit 772, It is possible to output a notification signal in the form of a vibration signal.

The communication unit 730 may include at least one antenna for wirelessly communicating with another device. According to one embodiment, the communication unit 730 may include a wireless communication module. For example, the communication unit 730 may include a local communication unit (e.g., Bluetooth communication unit, BLE (Bluetooth Low Energy) communication unit, NFC / RFID unit, WLAN communication unit, Zigbee communication unit, A mobile communication unit (e.g., 2G, 3G, 4G, LTE, and the like), an infrared communication unit, an IrDA (infrared data association) communication unit, a WiFi direct communication unit, a UWB (ultra wideband) communication unit, , But is not limited thereto.

The user input unit 750 means a means for inputting data for controlling the electronic device 700. [ For example, the user input unit 750 may include a key pad, a dome switch, a touch pad (contact type capacitance type, pressure type resistive type, infrared ray detection type, surface ultrasonic wave conduction type, A tension measuring method, a piezo effect method, etc.), a jog wheel, a jog switch, and the like, but is not limited thereto. In addition, the user input 750 may include a microphone, which may be configured to receive audio (e.g., a voice command) from a user of the electronic device 700.

The output unit 770 may output an audio signal or a video signal and may include a display unit 771, an acoustic output unit 772, and a vibration motor 773. [

The display 771 may be a liquid crystal display, a thin film transistor-liquid crystal display, an organic light-emitting diode, a flexible display, a three-dimensional display display, and electrophoretic display. Depending on the implementation of the output unit 770, the output unit 770 may include two or more display units 771.

The sound output unit 772 outputs audio data received from the communication unit 730 or stored in the memory 720. The sound output unit 772 may include a speaker, a buzzer, and the like.

The vibration motor 773 can generate physical vibration using electrical energy.

The user input unit 750 and the output unit 770 may include a network interface and may be implemented as a touch screen.

The processor 740 may be configured to execute the at least one program stored in the memory 720 so that the sensing unit 710, the communication unit 730, the user input unit 750, the memory 720, and the output unit 770, . In addition, processor 740 may include one or more processors. The processor 740 may also perform the functions of the electronic device 700 described in Figures 1-6 by executing at least one of the programs stored in the memory 720. [

At least one of the programs stored in the memory 720 includes the steps of obtaining relative velocity vectors for the vehicle of each of a plurality of objects located around the vehicle 100 including the electronic device 700, Calculating a mean vector of relative velocity vectors of at least one stationary object among the plurality of objects, calculating a mean vector of relative velocity vectors of at least one stationary object among the plurality of objects based on the calculated average vector, Based on the traveling speed and traveling direction of the vehicle 100 and the position of each of a plurality of objects located in the periphery of the vehicle 100 with respect to the vehicle 100, 120 of the first and second embodiments of the present invention.

The at least one programs stored in the memory 720 may also include calculating a mean vector of relative velocity vectors for the vehicle 100 of each of the at least one stationary object at a plurality of points of time, Calculating a mean vector of a plurality of average vectors and calculating an average vector of a plurality of average vectors calculated at a plurality of points of time from a plurality of average vectors calculated at a plurality of points of time, And estimating the shape of the road 120 by applying an extrapolation method using a vector.

It will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

The scope of the disclosure is to be defined by the appended claims, and all changes or modifications that come within the meaning and range of equivalency of the claims, and equivalents thereof, .

Claims (17)

A method of estimating a shape of a road by an electronic device included in a running vehicle,
Determining whether the plurality of objects is in a stop state based on relative velocity vectors of the plurality of objects located in the vicinity of the vehicle;
Calculating an average vector of relative velocity vectors for each of at least one stationary object among the plurality of objects with respect to the vehicle;
Estimating a traveling speed and a traveling direction of the vehicle using the calculated average vector; And
Estimating a shape of the road based on the traveling speed, the running direction, and the position of each of a plurality of objects located in the periphery of the vehicle with respect to the vehicle.
The method according to claim 1,
Wherein the step of estimating the running speed and running direction of the vehicle comprises:
And calculating the traveling vector of the vehicle by symmetrically calculating the calculated average vector.
The method according to claim 1,
Analyzing a plurality of signals relating to each of the plurality of objects, the signals being sensed by a sensor included in the vehicle; And
Further comprising analyzing the plurality of signals to obtain position information of the plurality of objects, size information, relative velocity vectors for the vehicle of each of the plurality of objects, and intensity of the plurality of signals .
The method of claim 3,
Further comprising classifying the plurality of objects using the relative velocity vectors for the vehicle, the magnitude information, and the intensity of the plurality of signals for each of the plurality of objects.
The method according to claim 1,
Wherein the step of calculating the average vector comprises:
Calculating an average vector of relative velocity vectors for each of the at least one stationary object relative to the vehicle at a plurality of time points.
6. The method of claim 5,
Wherein the step of estimating the running speed and running direction of the vehicle comprises:
And calculating an average vector of a plurality of average vectors calculated at the plurality of time points,
The step of estimating the shape of the road includes:
An extrapolation is applied using at least one vector having a similarity degree to a mean vector of a plurality of average vectors calculated at the plurality of time points from a plurality of average vectors calculated at the plurality of time points, Thereby estimating the shape of the road.
6. The method of claim 5,
Wherein the plurality of viewpoints include a first viewpoint and a second viewpoint,
The method comprises:
Identifying at least one object continuously positioned within a predetermined distance from the vehicle at the first viewpoint and the second viewpoint;
Tracking a change in position of the identified at least one object through a trace algorithm; And
And correcting position information of the plurality of objects based on the tracking.
The method according to claim 1,
Further comprising tracking, through a tracking algorithm, a positional change of an object located on the road from among at least one non-stop object among the plurality of objects.
1. An electronic device for estimating a shape of a road included in a running vehicle,
Sensing unit;
A memory in which at least one program is stored;
A communication unit for transmitting and receiving data to and from an external device; And
And at least one processor for estimating the shape of the road by executing the at least one program,
Wherein the at least one program comprises:
Determining whether the plurality of objects are in a stopped state based on relative velocity vectors of the plurality of objects located in the vicinity of the vehicle with respect to the vehicle;
Calculating an average vector of relative velocity vectors for each of at least one stationary object among the plurality of objects with respect to the vehicle; And
Estimating a traveling speed and a traveling direction of the vehicle using the calculated average vector; And
And estimating a shape of the road based on the traveling speed, the running direction, and the position of each of a plurality of objects located in the periphery of the vehicle with respect to the vehicle. Device.
10. The method of claim 9,
Wherein the step of estimating the running speed and running direction of the vehicle comprises:
And calculating the traveling vector of the vehicle by symmetrically calculating the calculated average vector.
10. The method of claim 9,
Analyzing a plurality of signals pertaining to each of the plurality of objects, the plurality of signals being sensed by the sensing unit; And
Further comprising analyzing the plurality of signals to obtain position information of the plurality of objects, size information, relative velocity vectors for the vehicle of each of the plurality of objects, and intensity of the plurality of signals, Device.
12. The method of claim 11,
Wherein the at least one program comprises:
Further comprising instructions for performing the step of classifying the plurality of objects using the relative velocity vectors for the vehicle, the magnitude information, and the intensity of the plurality of signals of each of the plurality of objects. Electronic device.
10. The method of claim 9,
Wherein the step of estimating the running speed and running direction of the vehicle comprises:
And calculating an average vector of relative velocity vectors for each of the at least one stationary object with respect to the vehicle at a plurality of points in time.
14. The method of claim 13,
Wherein the step of estimating the running speed and running direction of the vehicle comprises:
And calculating an average vector of a plurality of average vectors calculated at the plurality of time points,
The step of estimating the shape of the road includes:
Applying an extrapolation method using at least one vector having a similarity degree to a mean vector of a plurality of average vectors calculated at the plurality of time points from a plurality of average vectors calculated at the plurality of time points, And estimating the shape of the first portion.
14. The method of claim 13,
Wherein the plurality of viewpoints include a first viewpoint and a second viewpoint,
Wherein the at least one program comprises:
Identifying at least one object continuously positioned within a predetermined distance from the vehicle at the first viewpoint and the second viewpoint;
Tracking a change in position of the identified at least one object through a tracking algorithm; And
And correcting position information of the plurality of objects based on the tracking.
10. The method of claim 9,
Wherein the at least one program comprises:
Further comprising the step of tracking through a tracking algorithm a change in position of an object located on the road from among at least one non-stop object of the plurality of objects. Electronic device.
A computer-readable recording medium storing a program for executing the method according to any one of claims 1 to 8.

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