KR20180124685A - Autonomous vehicle and method of controlling the same - Google Patents

Abstract

The present invention relates to an autonomous vehicle and a control method thereof. According to an embodiment of the present invention, the autonomous vehicle comprises a processor for learning a path that the autonomous vehicle drives from a start position to an end position in a manual mode, starting to drive the learned path in an autonomous driving mode, and parking the autonomous vehicle in a detected parking slot when an empty parking slot is detected on the learned path through an object detector.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an autonomous vehicle,

The present invention relates to an autonomous vehicle and a control method thereof.

A vehicle is a device that moves a user in a desired direction by a boarding user. Typically, automobiles are examples.

On the other hand, various sensors and electronic devices are provided for the convenience of users using the vehicle. Particularly, for the convenience of the user, research on the ADAS (Advanced Driver Assistance System) is being actively carried out. Furthermore, development of an autonomous vehicle is being actively carried out.

Particularly, a technique is being developed for learning a parking slot and performing self parking for the self-driving vehicle in the learned parking slot.

However, according to the related art, when there is an obstacle in the learned parking slot, the autonomous vehicle can not perform autonomous parking. That is, there is a problem in the prior art that the autonomous vehicle can not actively learn a plurality of parking slots.

In order to solve the above problems, according to an embodiment of the present invention,

And an object of the present invention is to provide an autonomous driving vehicle for judging and storing an attribute of an object detected on a route while learning a route on which the autonomous vehicle travels from a start position to an end position.

It is also an object of the present invention to provide an autonomous vehicle that starts running along a learned route, detects an empty parking slot on the route, and carries out parking in the detected parking slot.

The problems of the present invention are not limited to the above-mentioned problems, and other problems not mentioned can be clearly understood by those skilled in the art from the following description.

In order to achieve the above object, an embodiment of the present invention provides a method for controlling an autonomous vehicle, comprising: learning a path that the autonomous vehicle travels from a start position to an end position in a manual mode; In an autonomous mode, starting traveling along the learned path; And parking the self-driving vehicle in the detected parking slot when an empty parking slot is detected on the learned route.

Further, in the embodiment of the present invention, the step of learning the path may include: determining an attribute of the object detected on the path from the start position to the end position; And storing the attribute of the determined object.

Further, in an embodiment of the present invention, a method for controlling an autonomous vehicle in a parking facility is provided, wherein the attribute of the object includes fixed information or mobile information.

Further, in the embodiment of the present invention, the step of learning the route may include the step of learning the route between the first position and the second position based on the attribute of the object judged between the first position and the second position by the self- And storing a path different from the path on which the autonomous vehicle traveled as a learning path.

Further, in the embodiment of the present invention, learning the path includes learning a partial path including at least one of a start position and an end position; And generating the entire learning path by combining the learned partial paths.

Further, in the embodiment of the present invention, the step of learning the route may include: detecting at least one turning point on the route that the autonomous vehicle travels; And storing the path connecting the detected at least one branch point as a learning path.

Further, in the embodiment of the present invention, in the autonomous running mode, the step of starting traveling along the learned route detects, through the object detection device, that the autonomous vehicle reaches within a predetermined distance from the starting position step; And receiving a user input to start traveling along the learned route through the user interface device.

The method may further include, in an embodiment of the present invention, receiving additional information regarding use of the parking facility, wherein in the autonomous mode, starting a journey along the learned path further comprises: Correcting the learned path by reflecting information; And starting traveling along the modified learned route.

Further, in an embodiment of the present invention, in the autonomous mode, starting traveling along the learned route may include receiving a user input requesting the autonomous vehicle to return to at least one of the start position and the end position ; And controlling the autonomous vehicle to return to at least one of the start position and the end position along the learned path in response to the user input.

Further, in the embodiment of the present invention, in response to the user input, the step of controlling the autonomous vehicle to return to at least one of the start position and the end position along the learned route may include: Determining a current position of the autonomous vehicle; And determining whether to maintain the running direction of the autonomous vehicle based on the determination result.

Further, in the embodiment of the present invention, the step of parking the autonomous vehicle in the detected parking slot may include a step of detecting a result of detection through the object detecting apparatus and an attribute of an object on the learned route stored in the step of learning the route And detecting an empty parking slot using the information on the free parking slot.

Further, in an embodiment of the present invention, parking the self-driving vehicle in the detected parking slot may include selecting a specific parking slot based on a predetermined priority when a plurality of empty parking slots are detected ; ≪ / RTI >

Further, in an embodiment of the present invention, the parking slot is a reserved parking slot, and the ending position is a position of the reserved parking slot.

Further, in an embodiment of the present invention, when parking is performed in the reserved parking slot, if an object not detected in the step of learning the route is detected in the reserved parking slot, Wherein the step of parking the slot includes the steps of: determining an area in which the autonomous vehicle can park in consideration of an area occupied by the object in the reserved parking slot; And parking the autonomous vehicle in the parkable area.

Further, in an embodiment of the present invention, when the autonomous vehicle is parked in the detected parking slot, storing the position of the detected parking slot in a memory; Recalling information about the location of the parked parking slot and the learned route in response to user input; Generating an outgoing route from the parking slot to the ending location, wherein the outgoing route includes at least a portion of the learned route; And controlling the autonomous traveling vehicle to exit along the generated departure route.

Further, in an embodiment of the present invention, there is provided a method of detecting an object, comprising the steps of: detecting an object existing outside the autonomous vehicle through an object detection device; And generating a path that can reach the learned path based on the detected object.

Further, in the embodiment of the present invention, when the position of the autonomous vehicle is changed after the time when the autonomous vehicle is parked, the step of controlling the autonomous vehicle to exit includes the step of determining the position of the changed autonomous vehicle ; And controlling, when the determined position is within the learned route, controlling the self-driving vehicle to depart from the learned route by using the learned route, and when the determined position is outside the learned route, And controlling the self-driving vehicle to exit using the generated route and the learned route.

In addition, in an embodiment of the present invention, there is provided a method for controlling a vehicle, comprising: identifying a user of the autonomous vehicle; Determining whether the identified user's location is within the learned path; And controlling the autonomous vehicle to stop at a position of the identified user when it is determined that the identified user's position is within the learned path.

Further, in the embodiment of the present invention, when the position of the identified user is determined to be outside the learned route, a step of generating a route to reach the position of the identified user is performed. And controlling the autonomous traveling vehicle to travel along a path for reaching the identified user's location.

The details of other embodiments are included in the detailed description and drawings.

According to an embodiment of the present invention, there is one or more of the following effects.

First, there is an effect that at least one or more parking slots are actively learned at a stage where the autonomous driving vehicle learns a route.

Second, when the autonomous vehicle travels along the learned path, it detects an empty parking slot, and even if the autonomous vehicle does not have a previous history of parking in the parking slot, the autonomous- There is a parking effect.

Third, there is an effect of leaving the vehicle from the parking slot by using the remaining route except for the route used for parking in the learned route.

The effects of the present invention are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description of the claims.

1 is a view showing an appearance of a vehicle according to an embodiment of the present invention.
2 is a view of a vehicle according to an embodiment of the present invention viewed from various angles.
3 to 4 are views showing an interior of a vehicle according to an embodiment of the present invention.
5 to 6 are drawings referred to explain an object according to an embodiment of the present invention.
FIG. 7 is a block diagram of a vehicle according to an embodiment of the present invention.
8 is a flowchart showing a learning-based vehicle parking method according to an embodiment of the present invention.
9 shows that a processor of a vehicle learns a path in a manual mode or a learning mode according to an embodiment of the present invention.
FIG. 10 shows that a processor of a vehicle learns a path in a manual mode or a learning mode according to another embodiment of the present invention.
FIG. 11 shows that a processor of a vehicle learns a path in a manual mode or a learning mode according to another embodiment of the present invention.
12 shows that a processor of a vehicle learns a path in a manual mode or a learning mode according to another embodiment of the present invention.
13 illustrates that a processor of a vehicle learns a path in a manual mode or a learning mode according to another embodiment of the present invention.
FIG. 14 shows that a processor of a vehicle learns a path in a manual mode or a learning mode according to another embodiment of the present invention.
15 shows that a processor of a vehicle learns a path in a manual mode or a learning mode according to another embodiment of the present invention.
16 shows that the processor of the vehicle according to the embodiment of the present invention runs the vehicle along the learned path.
17 shows that the processor of the vehicle according to another embodiment of the present invention drives the vehicle along the learned path.
FIG. 18 shows that the processor of the vehicle according to another embodiment of the present invention drives the vehicle along the learned path.
FIG. 19 shows that a processor of a vehicle according to another embodiment of the present invention drives a vehicle along a learned path.
20 shows that the processor of the vehicle according to another embodiment of the present invention drives the vehicle along the learned path.
Fig. 21 shows that the processor of the vehicle according to another embodiment of the present invention drives the vehicle along the learned path.
22 shows that the processor of the vehicle according to the embodiment of the present invention parks the vehicle in an empty parking slot on the learned path.
23 shows that the processor of the vehicle according to another embodiment of the present invention parks the vehicle in an empty parking slot on the learned path.
24 shows that the processor of the vehicle according to another embodiment of the present invention parks the vehicle in an empty parking slot on the learned path.
25 shows a learning-based vehicle departure method according to an embodiment of the present invention.
26 shows a learning-based vehicle departure method according to another embodiment of the present invention.
27 shows a learning-based vehicle departure method according to another embodiment of the present invention.
28 shows a learning-based vehicle departure method according to another embodiment of the present invention.
29 shows a learning-based vehicle departure method according to another embodiment of the present invention.
30 shows a learning-based vehicle departure method according to another embodiment of the present invention.
31 shows a learning-based vehicle departure method according to another embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings, wherein like reference numerals are used to designate identical or similar elements, and redundant description thereof will be omitted. The suffix " module " and " part " for the components used in the following description are given or mixed in consideration of ease of specification, and do not have their own meaning or role. In the following description of the embodiments of the present invention, a detailed description of related arts will be omitted when it is determined that the gist of the embodiments disclosed herein may be blurred. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory and are intended to provide further explanation of the invention as claimed. , ≪ / RTI > equivalents, and alternatives.

Terms including ordinals, such as first, second, etc., may be used to describe various elements, but the elements are not limited to these terms. The terms are used only for the purpose of distinguishing one component from another.

It is to be understood that when an element is referred to as being "connected" or "connected" to another element, it may be directly connected or connected to the other element, . On the other hand, when an element is referred to as being "directly connected" or "directly connected" to another element, it should be understood that there are no other elements in between.

The singular expressions include plural expressions unless the context clearly dictates otherwise.

In the present application, the terms "comprises", "having", and the like are used to specify that a feature, a number, a step, an operation, an element, a component, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

The vehicle described herein may be a concept including a car, a motorcycle. Hereinafter, the vehicle will be described mainly with respect to the vehicle.

The vehicle described in the present specification may be a concept including both an internal combustion engine vehicle having an engine as a power source, a hybrid vehicle having an engine and an electric motor as a power source, and an electric vehicle having an electric motor as a power source.

In the following description, the left side of the vehicle means the left side in the running direction of the vehicle, and the right side of the vehicle means the right side in the running direction of the vehicle.

1 is a view showing an appearance of a vehicle according to an embodiment of the present invention.

2 is a view of a vehicle according to an embodiment of the present invention viewed from various angles.

3 to 4 are views showing an interior of a vehicle according to an embodiment of the present invention.

5 to 6 are drawings referred to explain an object according to an embodiment of the present invention.

FIG. 7 is a block diagram of a vehicle according to an embodiment of the present invention.

Referring to FIGS. 1 to 7, the vehicle 100 may include a wheel rotated by a power source, and a steering input device 510 for adjusting the traveling direction of the vehicle 100.

The vehicle 100 may be an autonomous vehicle.

The vehicle 100 can be switched to the autonomous running mode or the manual mode based on the user input.

For example, the vehicle 100 can be switched from the manual mode to the autonomous mode, or switched from the autonomous mode to the manual mode, based on the received user input, via the user interface device 200. [

The vehicle 100 can be switched to the autonomous running mode or the manual mode based on the running situation information.

The running situation information may include at least one of object information outside the vehicle, navigation information, and vehicle condition information.

For example, the vehicle 100 can be switched from the manual mode to the autonomous mode or switched from the autonomous mode to the manual mode based on the running condition information generated by the object detection device 300. [

For example, the vehicle 100 can be switched from the manual mode to the autonomous mode or switched from the autonomous mode to the manual mode based on the running condition information received via the communication device 400. [

The vehicle 100 can be switched from the manual mode to the autonomous mode based on information, data and signals provided from the external device, or can be switched from the autonomous mode to the manual mode.

When the vehicle 100 is operated in the self-running mode, the autonomous vehicle 100 can be operated on the basis of the running system 700. [

For example, the autonomous vehicle 100 may be operated based on information, data, or signals generated in the traveling system 710, the outbound system 740, and the parking system 750.

When the vehicle 100 is operated in the manual mode, the autonomous vehicle 100 can receive a user input for driving through the driving operation device 500. [ Based on the user input received through the driving operation device 500, the vehicle 100 can be operated.

The overall length means the length from the front portion to the rear portion of the vehicle 100 and the width is the width of the vehicle 100 and the height means the length from the bottom of the wheel to the roof. In the following description, it is assumed that the total length direction L is a direction in which the full length direction of the vehicle 100 is measured, the full width direction W is a reference for the full width measurement of the vehicle 100, Which is a reference for the measurement of the height of the object 100.

7, the vehicle 100 includes a user interface device 200, an object detection device 300, a communication device 400, a driving operation device 500, a vehicle driving device 600, A navigation system 770, a sensing unit 120, an interface unit 130, a memory 140, a control unit 170, and a power supply unit 190.

According to the embodiment, the vehicle 100 may further include other components than the components described herein, or may not include some of the components described. The sensing unit 120 can sense the state of the vehicle. The sensing unit 120 may include a sensor such as a yaw sensor, a roll sensor, a pitch sensor, a collision sensor, a wheel sensor, a velocity sensor, A head sensor, a gyro sensor, a position module, a vehicle forward / backward sensor, a battery sensor, a fuel sensor, a tire sensor, a steering sensor by steering wheel rotation, a vehicle An internal temperature sensor, an in-vehicle humidity sensor, an ultrasonic sensor, an illuminance sensor, an accelerator pedal position sensor, a brake pedal position sensor, and the like.

The sensing unit 120 is configured to generate the sensing information based on the vehicle attitude information, the vehicle collision information, the vehicle direction information, the vehicle position information (GPS information), the vehicle angle information, the vehicle speed information, Obtain a sensing signal for information, fuel information, tire information, vehicle lamp information, vehicle interior temperature information, vehicle interior humidity information, steering wheel rotation angle, vehicle exterior illumination, pressure applied to the accelerator pedal, pressure applied to the brake pedal, can do.

The sensing unit 120 may further include an accelerator pedal sensor, a pressure sensor, an engine speed sensor, an air flow sensor AFS, an intake air temperature sensor ATS, a water temperature sensor WTS, (TPS), a TDC sensor, a crank angle sensor (CAS), and the like.

The sensing unit 120 can generate vehicle state information based on the sensing data. The vehicle status information may be information generated based on data sensed by various sensors provided in the vehicle.

For example, the vehicle state information includes at least one of attitude information of the vehicle, speed information of the vehicle, tilt information of the vehicle, weight information of the vehicle, direction information of the vehicle, battery information of the vehicle, fuel information of the vehicle, Vehicle steering information, vehicle interior temperature information, vehicle interior humidity information, pedal position information, and vehicle engine temperature information.

The interface unit 130 may serve as a pathway to various kinds of external devices connected to the vehicle 100. For example, the interface unit 130 may include a port that can be connected to the mobile terminal, and may be connected to the mobile terminal through the port. In this case, the interface unit 130 can exchange data with the mobile terminal.

Meanwhile, the interface unit 130 may serve as a channel for supplying electrical energy to the connected mobile terminal. When the mobile terminal is electrically connected to the interface unit 130, the interface unit 130 may provide the mobile terminal with electric energy supplied from the power supply unit 190 under the control of the controller 170.

The memory 140 is electrically connected to the control unit 170. The memory 140 may store basic data for the unit, control data for controlling the operation of the unit, and input / output data. The memory 140 may be, in hardware, various storage devices such as ROM, RAM, EPROM, flash drive, hard drive, and the like. The memory 140 may store various data for operation of the vehicle 100, such as a program for processing or controlling the controller 170. [

According to the embodiment, the memory 140 may be formed integrally with the controller 170 or may be implemented as a subcomponent of the controller 170. [

The control unit 170 can control the overall operation of each unit in the vehicle 100. [ The control unit 170 may be called an ECU (Electronic Control Unit).

The power supply unit 190 can supply power necessary for the operation of each component under the control of the control unit 170. Particularly, the power supply unit 190 can receive power from a battery or the like inside the vehicle.

One or more processors and controls 170 included in vehicle 100 may be implemented as application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs) field programmable gate arrays, processors, controllers, micro-controllers, microprocessors, and other electrical units for performing other functions.

The sensing unit 120, the interface unit 130, the memory 140 power supply unit 190, the user interface unit 200, the object detection unit 300, the communication unit 400, the driving operation unit 500, The vehicle drive system 600, the operating system 700 and the navigation system 770 may have separate processors or may be integrated into the controller 170. [

The user interface device 200 is a device for communicating between the vehicle 100 and a user. The user interface device 200 may receive user input and provide information generated by the vehicle 100 to the user. The vehicle 100 can implement UI (User Interfaces) or UX (User Experience) through the user interface device 200. [

The user interface device 200 may include an input unit 210, an internal camera 220, a biological sensing unit 230, an output unit 250, and a processor 270. Each component of the user interface device 200 can be structurally and functionally separated or integrated with the interface 130 described above.

According to the embodiment, the user interface device 200 may further include other components than the components described, or may not include some of the components described.

The input unit 210 is for receiving information from a user. The data collected by the input unit 210 may be analyzed by the processor 270 and processed by a user's control command.

The input unit 210 may be disposed inside the vehicle. For example, the input unit 210 may include one area of a steering wheel, one area of an instrument panel, one area of a seat, one area of each pillar, one area of the head console, one area of the door, one area of the center console, one area of the head lining, one area of the sun visor, one area of the windshield, One area or the like.

The input unit 210 may include a voice input unit 211, a gesture input unit 212, a touch input unit 213, and a mechanical input unit 214.

The voice input unit 211 can switch the voice input of the user into an electrical signal. The converted electrical signal may be provided to the processor 270 or the control unit 170.

The voice input unit 211 may include one or more microphones.

The gesture input unit 212 can switch the user's gesture input to an electrical signal. The converted electrical signal may be provided to the processor 270 or the control unit 170.

The gesture input unit 212 may include at least one of an infrared sensor and an image sensor for detecting a user's gesture input.

According to an embodiment, the gesture input 212 may sense a user's three-dimensional gesture input. To this end, the gesture input unit 212 may include an optical output unit for outputting a plurality of infrared rays or a plurality of image sensors.

The gesture input unit 212 can sense a user's three-dimensional gesture input through a time of flight (TOF) method, a structured light method, or a disparity method.

The touch input unit 213 can switch the touch input of the user into an electrical signal. The converted electrical signal may be provided to the processor 270 or the controller 170.

The touch input unit 213 may include a touch sensor for sensing a touch input of a user.

According to the embodiment, the touch input unit 213 is integrated with the display unit 251, thereby realizing a touch screen. Such a touch screen may provide an input interface and an output interface between the vehicle 100 and a user.

The mechanical input unit 214 may include at least one of a button, a dome switch, a jog wheel, and a jog switch. The electrical signal generated by the mechanical input 214 may be provided to the processor 270 or the controller 170.

The mechanical input 214 may be disposed on a steering wheel, a center fascia, a center console, a cockpit module, a door, or the like.

The processor 270 initiates the learning mode of the vehicle 100 in response to user input to at least one of the voice input unit 211, the gesture input unit 212, the touch input unit 213 and the mechanical input unit 214 described above. can do. In the learning mode, the vehicle 100 can perform the traveling path learning of the vehicle 100 and the surrounding environment learning. The learning mode will be described in detail below with respect to the object detecting apparatus 300 and the operating system 700. [

The internal camera 220 can acquire the in-vehicle image. The processor 270 can sense the state of the user based on the in-vehicle image. The processor 270 can obtain the user's gaze information from the in-vehicle image. The processor 270 may sense the user's gesture in the in-vehicle video.

The biometric sensor 230 can acquire biometric information of the user. The biometric sensor 230 includes a sensor capable of acquiring biometric information of a user, and can acquire fingerprint information, heartbeat information, etc. of a user using a sensor. Biometric information can be used for user authentication.

The output unit 250 is for generating an output related to a visual, auditory or tactile sense or the like.

The output unit 250 may include at least one of a display unit 251, an acoustic output unit 252, and a haptic output unit 253.

The display unit 251 may display graphic objects corresponding to various information.

The display unit 251 may be a liquid crystal display (LCD), a thin film transistor-liquid crystal display (TFT LCD), an organic light-emitting diode (OLED) display, a 3D display, and an e-ink display.

The display unit 251 may have a mutual layer structure with the touch input unit 213 or may be integrally formed to realize a touch screen.

The display unit 251 may be implemented as a Head Up Display (HUD). When the display unit 251 is implemented as an HUD, the display unit 251 may include a projection module to output information through an image projected on a windshield or a window.

The display unit 251 may include a transparent display. The transparent display may be attached to the windshield or window.

The transparent display can display a predetermined screen while having a predetermined transparency. Transparent displays can be used to have transparency, transparent displays include transparent TFEL (Thin Film Electroluminescent), transparent OLED (Organic Light-Emitting Diode), transparent LCD (Liquid Crystal Display), transmissive transparent display, Or the like. The transparency of the transparent display can be adjusted.

Meanwhile, the user interface device 200 may include a plurality of display units 251a to 251g.

The display unit 251 includes one region of the steering wheel, one region 251a, 251b and 251e of the inspiration panel, one region 251d of the sheet, one region 251f of each filler, 251g), one area of the center console, one area of the head lining, one area of the sun visor, one area 251c of the windshield, and one area 251h of the window.

The audio output unit 252 converts an electric signal provided from the processor 270 or the control unit 170 into an audio signal and outputs the audio signal. To this end, the sound output section 252 may include one or more speakers.

The haptic output unit 253 generates a tactile output. For example, the haptic output section 253 may operate to vibrate the steering wheel, the seat belt, the seat 110FL, 110FR, 110RL, and 110RR so that the user can recognize the output.

The processor 270 may control the overall operation of each unit of the user interface device 200.

In accordance with an embodiment, the user interface device 200 may include a plurality of processors 270, or may not include a processor 270. [

If the user interface device 200 does not include the processor 270, the user interface device 200 may be operated under the control of the processor or the control unit 170 of another apparatus in the vehicle 100. [

On the other hand, the user interface device 200 may be referred to as a vehicle display device.

The user interface device 200 may be operated under the control of the control unit 170.

The object detecting apparatus 300 is an apparatus for detecting an object located outside the vehicle 100. [ The object detecting apparatus 300 can generate object information based on the sensing data.

The object information may include information on the presence or absence of the object, position information of the object, distance information between the vehicle 100 and the object, and relative speed information between the vehicle 100 and the object.

The object may be various objects related to the operation of the vehicle 100.

5 to 6, an object O is a vehicle that is a vehicle that has a lane OB10, another vehicle OB11, a pedestrian OB12, a two-wheeled vehicle OB13, traffic signals OB14 and OB15, Speed bumps, terrain, animals, and the like.

The lane OB10 may be a driving lane, a side lane of the driving lane, or a lane on which the opposed vehicle runs. The lane OB10 may be a concept including left and right lines Line forming a lane.

The other vehicle OB11 may be a vehicle running in the vicinity of the vehicle 100. [ The other vehicle may be a vehicle located within a predetermined distance from the vehicle 100. For example, the other vehicle OB11 may be a vehicle preceding or following the vehicle 100. [

The pedestrian OB12 may be a person located in the vicinity of the vehicle 100. [ The pedestrian OB12 may be a person located within a predetermined distance from the vehicle 100. [ For example, the pedestrian OB12 may be a person who is located on the delivery or driveway.

The two-wheeled vehicle OB13 may mean a vehicle located around the vehicle 100 and moving using two wheels. The two-wheeled vehicle OB13 may be a rider having two wheels positioned within a predetermined distance from the vehicle 100. [ For example, the two-wheeled vehicle OB13 may be a motorcycle or a bicycle located on a sidewalk or a motorway.

The traffic signal may include a traffic light (OB15), a traffic sign (OB14), a pattern drawn on the road surface, or text.

The light may be light generated from lamps provided in other vehicles. Light can be light generated from a street light. Light can be solar light.

The road may include a slope such as a road surface, a curve, an uphill, a downhill, and the like.

The structure may be an object located around the road and fixed to the ground. For example, the structure may include street lamps, street lamps, buildings, electric poles, traffic lights, and bridges.

The terrain may include mountains, hills, and the like.

On the other hand, an object can be classified into a moving object and a fixed object. For example, the moving object may be a concept including an other vehicle, a pedestrian. For example, the fixed object may be a concept including a traffic signal, a road, and a structure.

The object detection apparatus 300 may include a camera 310, a radar 320, a LR 330, an ultrasonic sensor 340, an infrared sensor 350, and a processor 370. Each component of the object detecting apparatus 300 can be structurally and functionally separated or integrated with the sensing unit 120 described above.

According to the embodiment, the object detecting apparatus 300 may further include other elements other than the described elements, or may not include some of the described elements.

The camera 310 may be located at an appropriate location outside the vehicle to obtain the vehicle exterior image. The camera 310 may be a mono camera, a stereo camera 310a, an AVM (Around View Monitoring) camera 310b, or a 360 degree camera.

The camera 310 can acquire the position information of the object, the distance information to the object, or the relative speed information with the object using various image processing algorithms.

For example, the camera 310 can acquire distance information and relative velocity information with respect to the object based on a change in the object size with time in the acquired image.

For example, the camera 310 can acquire distance information and relative speed information with respect to the object through a pin hole model, a road surface profiling, and the like.

For example, the camera 310 may acquire distance information and relative speed information with respect to the object based on disparity information in the stereo image acquired by the stereo camera 310a.

For example, the camera 310 may be disposed in the interior of the vehicle, close to the front windshield, to acquire an image of the front of the vehicle. Alternatively, the camera 310 may be disposed around a front bumper or radiator grill.

For example, the camera 310 can be disposed in the interior of the vehicle, close to the rear glass, to acquire images of the rear of the vehicle. Alternatively, the camera 310 may be disposed around a rear bumper, trunk, or tailgate.

For example, the camera 310 may be disposed close to at least one of the side windows in the interior of the vehicle to obtain the image of the side of the vehicle. Alternatively, the camera 310 may be disposed around a side mirror, fender, or door.

The camera 310 may provide the acquired image to the processor 370.

The radar 320 may include an electromagnetic wave transmitting unit and a receiving unit. The radar 320 may be implemented by a pulse radar system or a continuous wave radar system in terms of the radio wave emission principle. The radar 320 may be implemented by a frequency modulated continuous wave (FMCW) scheme or a frequency shift keying (FSK) scheme according to a signal waveform in a continuous wave radar scheme.

The radar 320 detects an object based on a time-of-flight (TOF) method or a phase-shift method through an electromagnetic wave, and detects the position of the detected object, the distance to the detected object, Can be detected.

The radar 320 may be placed at a suitable location outside the vehicle to sense objects located at the front, rear, or side of the vehicle.

The ladder 330 may include a laser transmitting unit and a receiving unit. The LIDAR 330 may be implemented in a time of flight (TOF) scheme or a phase-shift scheme.

The lidar 330 may be implemented as a drive or an unshifted drive.

When implemented in a driving manner, the LIDAR 330 is rotated by a motor and can detect an object in the vicinity of the vehicle 100. [

In the case of non-driven implementation, the LIDAR 330 can detect an object located within a predetermined range with respect to the vehicle 100 by optical steering. The vehicle 100 may include a plurality of non-driven RRs 330. [

The lidar 330 detects an object based on a laser light medium, a time of flight (TOF) method, or a phase-shift method, and detects the position of the detected object, The relative speed can be detected.

The lidar 330 may be disposed at an appropriate location outside the vehicle to sense objects located at the front, rear, or side of the vehicle.

The ultrasonic sensor 340 may include an ultrasonic transmitter and a receiver. The ultrasonic sensor 340 can detect the object based on the ultrasonic wave, and can detect the position of the detected object, the distance to the detected object, and the relative speed.

The ultrasonic sensor 340 may be disposed at an appropriate position outside the vehicle for sensing an object located at the front, rear, or side of the vehicle.

The infrared sensor 350 may include an infrared ray transmitter and a receiver. The infrared sensor 340 can detect the object based on the infrared light, and can detect the position of the detected object, the distance to the detected object, and the relative speed.

The infrared sensor 350 may be disposed at an appropriate position outside the vehicle for sensing an object located at the front, rear, or side of the vehicle.

The processor 370 can control the overall operation of each unit of the object detecting apparatus 300. [

The processor 370 compares the data sensed by the camera 310, the radar 320, the lidar 330, the ultrasonic sensor 340, and the infrared sensor 350 with the stored data to detect or classify the object can do.

The processor 370 can detect and track the object based on the acquired image. The processor 370 can perform operations such as calculating a distance to an object, calculating a relative speed with respect to the object, and the like through an image processing algorithm.

For example, the processor 370 can obtain distance information and relative speed information with respect to the object, based on a change in the object size with time, in the acquired image.

For example, the processor 370 can acquire distance information and relative speed information with respect to the object through a pin hole model, a road surface profiling, and the like.

For example, the processor 370 may acquire distance information and relative speed information with respect to the object based on disparity information in the stereo image acquired by the stereo camera 310a.

The processor 370 can detect and track the object based on the reflected electromagnetic waves that are reflected from the object by the transmitted electromagnetic waves. The processor 370 can perform operations such as calculating a distance to an object and calculating a relative speed with respect to the object based on electromagnetic waves.

The processor 370 can detect and track the object based on the reflected laser light reflected back from the object by the transmitted laser. Based on the laser light, the processor 370 can perform operations such as calculating the distance to the object and calculating the relative speed with respect to the object.

The processor 370 can detect and track the object on the basis of the reflected ultrasonic waves reflected by the object and transmitted back. The processor 370 can perform operations such as calculating the distance to the object and calculating the relative speed with respect to the object based on the ultrasonic waves.

The processor 370 can detect and track the object based on the reflected infrared light that the transmitted infrared light reflects back to the object. The processor 370 can perform operations such as calculating the distance to the object and calculating the relative speed with respect to the object based on the infrared light.

As described above, when the learning mode of the vehicle 100 is started in response to a user input to the input unit 210, the processor 370 may include a camera 310, a radar 320, And the data sensed by the infrared sensor 350 and the infrared sensor 350 may be stored in the memory 140.

The steps of the learning mode based on the analysis of the stored data and the operation modes following the learning mode will be described in detail below with respect to the operation system 700. According to the embodiment, the object detecting apparatus 300 may include a plurality of processors 370 or may not include the processor 370. [ For example, each of the camera 310, the radar 320, the RI 330, the ultrasonic sensor 340, and the infrared sensor 350 may individually include a processor.

The object detecting apparatus 300 can be operated under the control of the processor of the apparatus in the vehicle 100 or the controller 170 when the object detecting apparatus 300 does not include the processor 370. [

The object detecting apparatus 300 can be operated under the control of the control section 170. [

The communication device 400 is a device for performing communication with an external device. Here, the external device may be another vehicle, a mobile terminal, or a server.

The communication device 400 may include at least one of a transmission antenna, a reception antenna, an RF (Radio Frequency) circuit capable of implementing various communication protocols, and an RF device to perform communication.

The communication device 400 includes a local communication unit 410, a location information unit 420, a V2X communication unit 430, an optical communication unit 440, a broadcast transmission / reception unit 450, an ITS (Intelligent Transport Systems) communication unit 460, (470).

According to the embodiment, the communication device 400 may further include other components than the components described, or may not include some of the components described.

The short-range communication unit 410 is a unit for short-range communication. The short-range communication unit 410 may be a wireless communication unit such as Bluetooth®, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Ultra Wideband (UWB), ZigBee, Near Field Communication (NFC) -Fidelity), Wi-Fi Direct, and Wireless USB (Wireless Universal Serial Bus) technology.

The short-range communication unit 410 may form short-range wireless communication networks to perform short-range communication between the vehicle 100 and at least one external device.

The position information section 420 is a unit for acquiring the position information of the vehicle 100. [ For example, the location information unit 420 may include a Global Positioning System (GPS) module or a Differential Global Positioning System (DGPS) module.

The V2X communication unit 430 is a unit for performing wireless communication with a server (V2I: Vehicle to Infra), another vehicle (V2V: Vehicle to Vehicle), or a pedestrian (V2P: Vehicle to Pedestrian). The V2X communication unit 430 may include an RF circuit capable of implementing communication with the infrastructure (V2I), inter-vehicle communication (V2V), and communication with the pedestrian (V2P) protocol.

The optical communication unit 440 is a unit for performing communication with an external device via light. The optical communication unit 440 may include a light emitting unit that converts an electric signal into an optical signal and transmits it to the outside, and a light receiving unit that converts the received optical signal into an electric signal.

According to the embodiment, the light emitting portion may be formed so as to be integrated with the lamp included in the vehicle 100. [

The broadcast transmission / reception unit 450 is a unit for receiving a broadcast signal from an external broadcast management server through a broadcast channel or transmitting a broadcast signal to a broadcast management server. The broadcast channel may include a satellite channel and a terrestrial channel. The broadcast signal may include a TV broadcast signal, a radio broadcast signal, and a data broadcast signal.

The ITS communication unit 460 can exchange information, data, or signals with the traffic system. The ITS communication unit 460 can provide information and data acquired in the traffic system. The ITS communication unit 460 can receive information, data or signals from the traffic system. For example, the ITS communication unit 460 can receive the road traffic information from the traffic system and provide it to the control unit 170. [ For example, the ITS communication unit 460 may receive a control signal from the traffic system and provide it to the control unit 170 or a processor provided in the vehicle 100. [

The processor 470 can control the overall operation of each unit of the communication device 400.

In accordance with an embodiment, the communication device 400 may include a plurality of processors 470 or may not include a processor 470. [

When the processor 400 is not included in the communication device 400, the communication device 400 can be operated under the control of the processor or the control unit 170 of another apparatus in the vehicle 100. [

On the other hand, the communication device 400 can implement the vehicle display device together with the user interface device 200. [ In this case, the vehicle display device may be called a telematics device or an AVN (Audio Video Navigation) device.

The communication device 400 may be operated under the control of the control unit 170. [

The driving operation device 500 is a device for receiving a user input for operation.

In the manual mode, the vehicle 100 can be operated on the basis of the signal provided by the driving operation device 500.

The driving operation device 500 may include a steering input device 510, an acceleration input device 530, and a brake input device 570.

The steering input device 510 may receive a forward direction input of the vehicle 100 from a user. The steering input device 510 is preferably formed in a wheel shape so that steering input is possible by rotation. According to an embodiment, the steering input device may be formed as a touch screen, a touch pad, or a button.

The acceleration input device 530 may receive an input for acceleration of the vehicle 100 from a user. The brake input device 570 can receive an input for deceleration of the vehicle 100 from the user. The acceleration input device 530 and the brake input device 570 are preferably formed in a pedal shape. According to an embodiment, the acceleration input device or the brake input device may be formed as a touch screen, a touch pad, or a button.

The driving operation device 500 can be operated under the control of the control unit 170. [

The vehicle driving device 600 is an apparatus for electrically controlling the driving of various devices in the vehicle 100. [

The vehicle driving apparatus 600 includes a power train driving unit 610, a chassis driving unit 620, a door / window driving unit 630, a safety driving unit 640, a lamp driving unit 650 and an air conditioning driving unit 660 .

According to the embodiment, the vehicle drive system 600 may further include other elements other than the described elements, or may not include some of the elements described.

On the other hand, the vehicle drive apparatus 600 may include a processor. Each unit of the vehicle drive apparatus 600 may individually include a processor.

The power train driving unit 610 can control the operation of the power train apparatus.

The power train driving unit 610 may include a power source driving unit 611 and a transmission driving unit 612.

The power source drive unit 611 can perform control on the power source of the vehicle 100. [

For example, when the fossil fuel-based engine is a power source, the power source drive unit 610 can perform electronic control of the engine. Thus, the output torque of the engine and the like can be controlled. The power source drive unit 611 can adjust the engine output torque under the control of the control unit 170. [

For example, when the electric energy based motor is a power source, the power source driving unit 610 can perform control on the motor. The power source drive unit 610 can adjust the rotation speed, torque, and the like of the motor under the control of the control unit 170. [

The transmission drive unit 612 can perform control on the transmission.

The transmission drive unit 612 can adjust the state of the transmission. The transmission drive unit 612 can adjust the state of the transmission to forward (D), reverse (R), neutral (N), or parking (P).

On the other hand, when the engine is a power source, the transmission drive unit 612 can adjust the gear engagement state in the forward (D) state.

The chassis driving unit 620 can control the operation of the chassis apparatus.

The chassis driving unit 620 may include a steering driving unit 621, a brake driving unit 622, and a suspension driving unit 623.

The steering driver 621 may perform electronic control of the steering apparatus in the vehicle 100. [ The steering driver 621 can change the traveling direction of the vehicle.

The brake driver 622 can perform electronic control of the brake apparatus in the vehicle 100. [ For example, it is possible to reduce the speed of the vehicle 100 by controlling the operation of the brakes disposed on the wheels.

On the other hand, the brake driver 622 can individually control each of the plurality of brakes. The brake driving unit 622 can control the braking forces applied to the plurality of wheels to be different from each other.

The suspension driving unit 623 can perform electronic control on a suspension apparatus in the vehicle 100. [ For example, when there is a curvature on the road surface, the suspension driving unit 623 can control the suspension device so as to reduce the vibration of the vehicle 100. [

On the other hand, the suspension driving unit 623 can individually control each of the plurality of suspensions.

The door / window driving unit 630 may perform electronic control of a door apparatus or a window apparatus in the vehicle 100.

The door / window driving unit 630 may include a door driving unit 631 and a window driving unit 632.

The door driving unit 631 can control the door device. The door driving unit 631 can control the opening and closing of a plurality of doors included in the vehicle 100. [ The door driving unit 631 can control the opening or closing of a trunk or a tail gate. The door driving unit 631 can control the opening or closing of the sunroof.

The window driving unit 632 may perform an electronic control on a window apparatus. It is possible to control the opening or closing of the plurality of windows included in the vehicle 100. [

The safety device driving unit 640 can perform electronic control of various safety apparatuses in the vehicle 100. [

The safety device driving unit 640 may include an airbag driving unit 641, a seat belt driving unit 642, and a pedestrian protection device driving unit 643. [

The airbag driver 641 may perform electronic control of the airbag apparatus in the vehicle 100. [ For example, the airbag driver 641 can control the deployment of the airbag when a danger is detected.

The seat belt driving unit 642 can perform electronic control of the seatbelt apparatus in the vehicle 100. [ For example, the seat belt driving portion 642 can control the passenger to be fixed to the seats 110FL, 110FR, 110RL, and 110RR using the seat belt when a danger is detected.

The pedestrian protection device driving section 643 can perform electronic control on the hood lift and the pedestrian airbag. For example, the pedestrian protection device driving section 643 can control the hood lift-up and the pedestrian airbag deployment when a collision with a pedestrian is detected.

The lamp driving unit 650 can perform electronic control of various lamp apparatuses in the vehicle 100. [

The air conditioning driving unit 660 can perform electronic control on the air conditioner in the vehicle 100. [ For example, when the temperature inside the vehicle is high, the air conditioning driving unit 660 can control the air conditioner to operate so that the cool air is supplied to the inside of the vehicle.

The vehicle drive apparatus 600 may include a processor. Each unit of the vehicle drive apparatus 600 may individually include a processor.

The vehicle drive apparatus 600 can be operated under the control of the control section 170. [

The operating system 700 is a system for controlling various operations of the vehicle 100. [ The travel system 700 can be operated in the autonomous mode.

The travel system 700 may include a travel system 710, an outbound system 740, and a parking system 750.

According to the embodiment, the travel system 700 may further include other components than the components described, or may not include some of the components described.

On the other hand, the travel system 700 may include a processor. Each unit of the travel system 700 may each include a processor individually.

On the other hand, the driving system 700 can control the running of the autonomous driving mode based on the learning. In this case, the learning mode and the operation mode based on completion of learning can be performed. A method for the processor of the driving system 700 to perform a learning mode and an operating mode will be described below.

The learning mode can be performed in the manual mode described above. In the learning mode, the processor of the driving system 700 can perform the traveling path learning of the vehicle 100 and the surrounding environment learning.

The traveling route learning may include generating map data on the route that the vehicle 100 travels. In particular, the processor of the navigation system 700 can generate map data based on the information detected through the object detection apparatus 300 while the vehicle 100 travels from the origin to the destination.

The surrounding environment learning may include storing and analyzing information on the environment of the vehicle 100 during the driving process and the parking process of the vehicle 100. [ Particularly, the processor of the driving system 700 detects the information detected through the object detecting apparatus 300 in the parking process of the vehicle 100, for example, the position information of the parking space, the size information, the fixed (or non-fixed) Information on the surrounding environment of the vehicle 100 can be stored and analyzed based on information such as obstacle information and the like.

The operation mode can be performed in the autonomous mode described above. The operation mode will be described on the assumption that the traveling route learning or the surrounding environment learning is completed through the learning mode.

The operation mode may be performed in response to user input through the input unit 210, or may be performed automatically when the vehicle 100 reaches the driving route and the parking space where learning has been completed.

The operation mode includes a semi-autonomous operating mode requiring a part of the user's operation on the driving control device 500 and a fully-autonomous operation requiring no user's operation on the driving control device 500 Mode (fully autonomous operating mode).

Meanwhile, according to the embodiment, the processor of the driving system 700 can control the driving system 710 in the operating mode to drive the vehicle 100 along the traveling path on which learning has been completed.

Meanwhile, according to the embodiment, the processor of the driving system 700 can control the outgoing system 740 in the operating mode to leave the parked vehicle 100 from the learned parking space.

Meanwhile, according to the embodiment, the processor of the driving system 700 can control the parking system 750 in the operation mode to park the vehicle 100 from the current position to the learned parking space. Meanwhile, according to the embodiment, when the driving system 700 is implemented in software, it may be a sub-concept of the control unit 170.

According to the embodiment, the operating system 700 includes a user interface device 270, an object detecting device 300 and a communication device 400, a driving operation device 500, a vehicle driving device 600, a navigation system A sensing unit 770, a sensing unit 120, and a control unit 170.

The traveling system 710 can perform traveling of the vehicle 100. [

The navigation system 710 can receive navigation information from the navigation system 770 and provide a control signal to the vehicle drive system 600 to perform the travel of the vehicle 100. [

The traveling system 710 can receive the object information from the object detecting apparatus 300 and provide the vehicle driving apparatus 600 with a control signal to perform the traveling of the vehicle 100. [

The traveling system 710 can receive the signal from the external device through the communication device 400 and provide a control signal to the vehicle driving device 600 to perform the traveling of the vehicle 100. [

The navigation system 710 includes a user interface device 270, an object detection device 300 and a communication device 400, a driving operation device 500, a vehicle driving device 600, a navigation system 770, 120, and a control unit 170, and may be a system concept for performing driving of the vehicle 100. [

Such a traveling system 710 may be referred to as a vehicle running control apparatus.

The departure system 740 can perform the departure of the vehicle 100.

The outpost system 740 can receive navigation information from the navigation system 770 and provide control signals to the vehicle driving apparatus 600 to perform the departure of the vehicle 100. [

The departure system 740 can receive object information from the object detecting apparatus 300 and provide a control signal to the vehicle driving apparatus 600 to carry out the departure of the vehicle 100. [

The departure system 740 can receive a signal from the external device via the communication device 400 and provide a control signal to the vehicle driving device 600 to perform the departure of the vehicle 100. [

The destination system 740 includes a user interface device 270, an object detection device 300 and a communication device 400, a driving operation device 500, a vehicle driving device 600, a navigation system 770, 120 and a control unit 170. The control unit 170 may be a system concept that carries out the departure of the vehicle 100. [

This outgoing system 740 may be termed a vehicle outbound control device.

The parking system 750 can perform parking of the vehicle 100. [

The parking system 750 may receive navigation information from the navigation system 770 and provide a control signal to the vehicle driving device 600 to perform parking of the vehicle 100. [

The parking system 750 is capable of performing parking of the vehicle 100 by receiving object information from the object detecting apparatus 300 and providing a control signal to the vehicle driving apparatus 600. [

The parking system 750 can receive the signal from the external device via the communication device 400 and provide a control signal to the vehicle driving device 600 to perform parking of the vehicle 100. [

The parking system 750 includes a user interface device 270, an object detection device 300 and a communication device 400, a driving operation device 500, a vehicle driving device 600, a navigation system 770, 120 and a control unit 170. The system 100 may be a system concept that carries out parking of the vehicle 100. [

Such a parking system 9750) may be referred to as a vehicle parking control apparatus.

The navigation system 770 may provide navigation information. The navigation information may include at least one of map information, set destination information, route information according to the destination setting, information about various objects on the route, lane information, and current location information of the vehicle.

The navigation system 770 may include a memory, a processor. The memory can store navigation information. The processor may control the operation of the navigation system 770.

According to an embodiment, the navigation system 770 can receive information from an external device via the communication device 400 and update the stored information.

According to an embodiment, the navigation system 770 may be classified as a subcomponent of the user interface device 200.

8 is a flowchart illustrating a learning-based vehicle parking method according to an embodiment of the present invention. On the other hand, the processor of the vehicle 100 described below can be understood as a configuration corresponding to the controller 170 of Fig.

As in step 810, the processor of the vehicle 100 in the manual mode or the learning mode learns the path that the vehicle 100 travels from the starting position to the ending position. Step 810 may correspond to the execution of the learning mode of the travel system 700 described above. The more various embodiments related to step 810 will be described in detail below in the description of Figs. 9 to 15. Fig.

Next, as in step 820, the processor of the vehicle 100 in the operation mode starts running the vehicle 100 along the learned path. Regarding the start and running of the driving, a more various embodiment of the step 820 will be described in detail below with reference to FIG. 16 to FIG.

Finally, as in step 830, the processor of the vehicle 100 parks the vehicle 100 in the detected parking slot when an empty parking slot is detected on the learned route. More specific embodiments of step 830 will now be described in detail in FIGS. 22-24.

9 shows that a processor of the vehicle 100 learns a path in a manual mode or a learning mode according to an embodiment of the present invention. 9 shows vehicle 100 entering parking space 900, such as a public car park or garage, through entrance 910. [

At the start position 920, the processor of the vehicle 100 initiates the learning mode in response to user input through the user interface device 200. [ The learning mode may be performed in a manual mode in which the vehicle 100 is manually operated by the user. That is, the learning for the route 940 in the learning mode is performed while the user manually operates the vehicle 100 and travels.

Learning for the route 940 means generating map data for the route 940 that the vehicle 100 travels. In particular, the processor of the navigation system 700 can generate map data based on the information detected through the object detection device 300 while the vehicle 100 is traveling from the starting position 920 to the ending position 930 have.

Learning about the route 940 may be a concept distinguished from learning about the space in which the vehicle 100 can travel, that is, the road in the parking space 900. Learning about the path 940 means learning about the running locus of the vehicle 100 from the starting position 920 to the ending position 930.

On the other hand, the learning about the space that the vehicle 100 can travel is performed by learning about the travelable space based on the full width, the total length of the vehicle 100, the width of the road, and the parking line painted on the bottom surface of the parking space 900 it means. Learning about the space in which the vehicle 100 can travel can be a concept included in the step of determining the attribute of the object.

Learning in the path 940 means learning about the trajectory of the vehicle 100 traveling in the parking space 900 in a narrow sense. In a broad sense, however, the vehicle 100 detects an object in the parking space 900 And learning about objects, parking slots, and the like detected through the device 300. FIG.

The processor of the vehicle 100 can learn the information detected through the object detecting apparatus 300 in the path learning step, that is, the information about the attribute of the object, by dividing the information into the fixed information and the mobile information.

The fixed type information refers to information that does not change over time, such as a pillar of a parking lot, a tree, or a space that the vehicle 100 can travel. The fixed type information is information used when the vehicle 100 autonomously travels along the learned route.

The mobile type information means non-permanent information such as position information of a parked other vehicle, for example. The processor of the vehicle 100 can learn the position at a position where it can be parked, through the information about the other vehicle parked at the position where the parking line is not recognized.

On the other hand, there may be a limitation on the maximum speed of the vehicle 100 during learning in the manual mode. That is, when the speed of the vehicle 100 becomes equal to or greater than a preset maximum speed, the processor of the vehicle 100 can output a warning message to the user through the output unit 250 and control the learning to be canceled.

On the other hand, the traveling pattern of the user can be learned together with the route learning step. For example, the processor of the vehicle 100 may generate and store in the memory 140 a speed profile relating to the speed variation of the vehicle 100 on the running route during learning. Alternatively, the processor of the vehicle 100 may store, in the memory 140, information that the steering wheel of the vehicle 100 has been operated on the running route during learning via the steering sensor. The learned driving pattern including the speed profile or the information that the steering wheel is manipulated, etc. can be used when the vehicle 100 performs the autonomous driving in the autonomous driving mode in the future.

Similar to the start of learning, termination of learning is also performed in response to user input through user interface device 200. [ That is, when the vehicle 100 arrives at the end position 930, when the user input for terminating the learning is received, the processor of the vehicle 100 determines whether the learning from the start position 920 to the end position 930 Path 940 is stored.

On the other hand, the learned route 940 in the parking space 900 is utilized for parking and departing the vehicle 100, which will be described below. In this regard, the corresponding portions will be described in detail.

10 shows that a processor of the vehicle 100 learns a path in a manual mode or a learning mode according to another embodiment of the present invention.

In a parking facility having a plurality of floors, such as a tower parking system, it is general that the structure of each floor is designed to be the same. Therefore, in such a case, path learning for each layer may not be necessary.

More specifically, as shown in FIG. 10A, the processor of the vehicle 100 learns the path 1040 in one layer. Next, as shown in FIG. 10B, the processor of the vehicle 100 may store the path 1050 for the other layer in the same manner as the path 1040.

11 shows that a processor of the vehicle 100 learns a path in a manual mode or a learning mode according to another embodiment of the present invention.

9 to 10 show learning of a path based on the information detected through the object detecting apparatus 300, while Fig. 11 shows a case in which the learned path is corrected by user input through the user interface apparatus 200 And inputting additional information.

More specifically, Fig. 11 shows an external image 1100 of the vehicle 100 photographed by the camera 310, which is an arrangement of the object detecting apparatus 300. As shown in Fig. When a user input such as a touch input or a button input is received through the user interface device 200, the processor of the vehicle 100 can correct the learned path and input additional information. Examples of the correction for the path and the input of additional information are as follows.

First, if the other vehicle 1110 is parked at a predetermined position, the predetermined position may be set to a position where parking is possible.

Second, if there is an obstacle 1120 on the path, information on whether the obstacle 1120 is a temporary obstacle or a fixed obstacle may be added.

Third, if there is a path 1130 that is not a path that the vehicle 100 traveled but is passable, the processor of the vehicle 100 can learn path 1130 through a path that can pass.

In addition, various information such as the speed of the vehicle 100, the distance between the vehicles, and the like can be added by the user input through the user interface device 200.

12 shows that a processor of the vehicle 100 learns a path in a manual mode or a learning mode according to another embodiment of the present invention.

According to another embodiment of the present invention, the step of learning the route includes the step of learning the route based on the attribute of the object judged between the first position 1230 and the second position 1240, And storing a path different from the path traveled by the vehicle 100 between the first position 1230 and the second position 1240 as a learning path.

More specifically, the path 1210 and the path 1250 in FIG. 12A indicate the path that the vehicle 100 traveled. 12A shows that the vehicle 100 travels on the alternative route 1250 from the first position 1230 to the second position 1240 due to the obstacle 1220. [

Next, Fig. 12 (b) will be described. If the obstacle 1220 is set to be a temporary obstacle by a user input through the user interface device 200, such as another vehicle that is stationary for a while, the processor of the vehicle 100 can move from the first position 1230 to the second position 1240 to the alternative path 1250 and the other path 1260 that the vehicle 100 actually traveled. The other path 1260 may be, for example, a shortest path connecting the first position 1230 and the second position 1240, a minimum time path, or a more secure path.

Although not shown in FIG. 12, when the steering wheel rotation angle of the vehicle 100 is within a predetermined value within a predetermined interval, the processor of the vehicle 100 recognizes the path that the vehicle 100 travels straight, You can route by distance.

According to an embodiment of the present invention as shown in FIG. 12, it is possible to provide an optimal traveling route of the vehicle 100 in the autonomous driving mode by modifying the learned route in accordance with the type of the obstacle as well as the route There is a technical effect.

13 shows that a processor of the vehicle 100 learns a path in a manual mode or a learning mode according to another embodiment of the present invention.

13 shows that the vehicle 100 has reached the branch point 1320 in the step in which the processor of the vehicle 100 learns the route. A bifurcation (or intersection) means a point where two or more passages meet or intersect.

13, the object detecting apparatus 300 of the vehicle 100 at the branching point 1320 detects that there is a passable space on the left side of the vehicle 100 as a reference. A camera 310, a radar 320, a lidar 330, an ultrasonic sensor 340, an infrared ray sensor 350, and the like may be used to detect a passable space.

In Fig. 13, the vehicle 100 travels in the straight direction at the branch point 1320, but the processor of the vehicle 100 stores the positional information of the branch point 1320 and the direction information of the passable space with reference to the travel route.

When the vehicle 100 reaches another branch point 1330, it stores positional information of another branch point 1330 and direction information of the passable space with reference to the traveling path.

The processor of the vehicle 100 stores a new path connecting the two branch points 1320 and 1330 in the learning path in response to user input through the user interface device 200. [ Alternatively, the processor of the vehicle 100 may actively store a new path connecting the two branch points 1320 and 1330 as a learning path.

14 shows that the processor of the vehicle 100 learns a path in a manual mode or a learning mode according to another embodiment of the present invention.

There may be a case where the running direction of the parking space 1400 is limited to one-way traffic.

For example, in the parking space 1400 shown in Fig. 14, the passage of the vehicle is limited by one-way passage in the clockwise direction.

When the vehicle 100 attempts to start learning in the counterclockwise direction or actually performs learning, the processor of the vehicle 100 controls the output unit 250 of the user interface device 200 to travel to the user in the wrong direction .

15 shows that a processor of the vehicle 100 learns a path in a manual mode or a learning mode according to another embodiment of the present invention.

9 to 14, a method of learning one traveling path in one parking space has been described. However, according to another embodiment of the present invention, a plurality of partial paths having a start position and an end position can be learned even in one parking space.

As shown in FIG. 15A, the processor of the vehicle 100 learns two partial paths 1510 and 1520 having a start position and an end position. 15B, the processor of the vehicle 100 generates a full path in which the partial path 1510 and the partial path 1520 are integrated in response to the user input through the user interface apparatus 100, The generated entire path can be stored in the memory 140. Alternatively, the processor of the vehicle 100 may actively generate the entire path without user input, and store the generated whole path in the memory 140.

On the other hand, for the partial path 1510, the processor of the vehicle 100 receives the user input for starting the learning, but does not receive the user input for ending the learning when the parking of the vehicle 100 is completed, A processing method when the learning can not be completed will be described.

In this case, the processor of the vehicle 100 determines whether or not to perform the learning of the partial path 1520, following the learning of the partial path 1510 that was not previously completed when the vehicle 100 departs the user interface apparatus 200 ) From the user.

If there is user input, the processor of the vehicle 100 may generate the entire path in which the partial path 1510 and the partial path 1520 are integrated, and store the generated whole path in the memory 140. [

8 to 15, a method in which the vehicle 100 learns a path in a manual mode or a learning mode has been described. 16 to 21, a description will be given of a method in which the vehicle travels along a learned route in the autonomous mode.

16 shows that the processor of the vehicle 100 travels the vehicle 100 along a learned path according to an embodiment of the present invention.

In the autonomous running mode, the following conditions may be required for the vehicle 100 to start autonomous travel along the learned route 1640:

First, it may be required that the vehicle 100 reach within a predetermined distance (preferably within 2 m) from the starting position 1620. The current position of the vehicle 100 can be detected through the camera 310 and the position information section 420. [

The processor of the vehicle 100 may store semantic information such as a landmark in an image photographed through the camera 310 in advance and may store semantic information such as a landmark or the like in an image photographed through the camera 310 at the current position of the vehicle 100 The semantic information can be extracted. The processor of the vehicle 100 compares the detected current position of the vehicle 100 with the start position 1620 through the above process.

Second, a user input via the user interface device 200, such as a button input for starting an autonomous running, may be required. This is to give credibility through user input in starting autonomous driving.

On the other hand, the two conditions described above are exemplary, and two conditions may be required together or only one of them may be selectively required.

The processor of the vehicle 100 detects an empty parking slot while autonomously running the learned route 1640 from the starting position 1620 to the ending position 1630. [

On the other hand, in the autonomous mode, when the vehicle 100 autonomously travels along the learned route 1640, the maximum speed of the vehicle 100 can be limited.

17 shows that the processor of the vehicle 100 travels the vehicle 100 along a learned path according to another embodiment of the present invention.

The processor of the vehicle 100 may not detect an empty parking slot while the vehicle 100 travels along the learned route 1740 from the starting position 1720 to the ending position 1730 as shown in Fig.

In this case, the processor of the vehicle 100 can stop the vehicle 100 at the end position 1730 and inform the user that the parking slot has not been detected through the output unit 250.

18 shows that the processor of the vehicle 100 drives the vehicle 100 along a learned path according to another embodiment of the present invention.

FIG. 18 shows that the obstacle 1810 recognized as a fixed obstacle in the learning mode disappears over time to generate a new route in the autonomous driving mode.

18 (a) shows that the vehicle has learned a route by avoiding traveling by the fixed obstacle 1810 in the learning mode.

18B shows that the fixed obstacle 1810 disappears and the vehicle 100 travels on a new route in the autonomous mode. First, the vehicle 100 stops at a position where the fixed obstacle 1810 is present. Then, the processor of the vehicle 100 notifies the user of information indicating that the existing fixed obstacle 1810 has disappeared through the output unit 250.

Next, the processor of the vehicle 100 requests the user to confirm whether or not to generate a new path 1820 through the output unit 250. The processor of the vehicle 100 creates a new path 1820 and creates a new path 1820 along the generated new path 1820 if there is a match for creating a new path 1820 by user input through the user interface device 200. [ Thereby causing the vehicle 100 to travel.

18, the processor of the vehicle 100 calculates the time at which the collision is predicted based on the current speed of the vehicle 100 and the distance to the obstacle . If the collision prediction time is longer than the preset value, that is, if the collision risk is not very high, the vehicle 100 can be controlled to be decelerated without stopping the vehicle immediately.

19 shows that the processor of the vehicle 100 travels the vehicle 100 along a learned path according to another embodiment of the present invention.

Fig. 19 illustrates a vehicle 100 running on a learned route in a parking facility having a plurality of floors, such as a tower parking system.

FIG. 19 (a) shows that the vehicle 100 travels on a route 1910 which is sequentially learned from the first floor to the third floor.

On the other hand, the communication device 400 of the vehicle 100 can receive additional information on the use of the parking facility from an external device such as a parking lot server. 19, the communication device 400 of the vehicle 100 receives from the parking lot server additional information on the prohibition of parking on the first and second basement floors.

In this case, the processor of the vehicle 100 can modify the learned route by reflecting the received additional information. That is, as shown in FIG. 19B, the processor of the vehicle 100 does not travel along the learned route 1910 in the first and second basement floors, but immediately follows a new route 1920 reaching the third floor Can be generated.

Next, the processor of the vehicle 100 controls the vehicle 100 to travel along the generated route 1920.

According to one embodiment of the present invention shown in FIG. 19, the vehicle 100 does not run unconditionally from the starting position to the ending position along the learned route, but the optimum traveling route is determined based on the information received from the external device There is a technical effect to generate.

20 shows that the processor of the vehicle 100 drives the vehicle 100 along a learned path according to another embodiment of the present invention.

20 shows that the travel path of the vehicle 100 in the autonomous mode is adaptively changed based on the information directly input by the user.

The user can set the exclusion list 2000 of FIG. 20 and store the exclusion list 2000 in the memory 140.

For example, the exclusion list (2000) shows that parking is not available for the basement floor from March 1 to March 3, and parking for the basement level from April 1 to April 8 Information indicating that it is impossible is included.

When the exclusion list 2000 is set, the processor of the vehicle 100 may generate the parking profile 1 2010 or the parking profile 2 2020 by date according to the set exclusion list 2000.

For example, the processor of the vehicle 100 may add information indicating that parking for the second basement is prohibited by reflecting the information of the exclusion list 2000 in the parking profile 1 (2010) of April 3. Further, the processor of the vehicle 100 may add information indicating that parking is permitted in the first to third basement floors by reflecting the information of the exclusion list 2000 in the parking profile 2 (2020) of April 10 have.

As described above, the processor of the vehicle 100 generates the parking profile for each date by reflecting the information received from the user through the user input device 200, and applies the same to the driving route of the vehicle 100 in the self- It can be changed adaptively.

21 shows that the processor of the vehicle 100 travels the vehicle 100 along a learned path according to another embodiment of the present invention.

FIG. 21 shows that the vehicle 100 travels along the modified route, reflecting the various information, rather than running the vehicle 100 unconditionally from the start position to the end position along the learned route.

According to an embodiment of the present invention according to FIG. 21, the processor of the vehicle 100 may further learn the spare parking space according to time or day of the week to reflect the parking space in the parking path.

For example, the processor of the vehicle 100 does not travel along the learned route 2110 as shown in (a) of FIG. 21, but carries C It is possible to create a route 2120 that runs directly to the zone. However, in this process, the user's input through the user interface device 200 may be accompanied.

According to another embodiment of the present invention shown in FIG. 21, the processor of the vehicle 100 can learn the user's parking pattern according to time or day of the week and reflect the park pattern on the parking route.

For example, in the morning, when the user frequently parks in the area A close to the elevator, the processor of the vehicle 100 learns the parking pattern related thereto, ). ≪ / RTI >

On the other hand, if the user frequently parks in the area C on weekends, the processor of the vehicle 100 learns the parking pattern related thereto and can drive the vehicle 100 along the route 2120 as shown in FIG. 21 (b) have.

16 to 21, a description has been given of a method in which the vehicle travels along the learned route in the self-running mode. 22 to 24, a description will be given of a method of parking the vehicle 100 in a parking slot in which the processor of the vehicle 100 is empty on the learned route.

22 shows that the processor of the vehicle 100 according to an embodiment of the present invention parks the vehicle 100 in an empty parking slot on the learned route.

In the autonomous mode, when the vehicle 100 starts traveling along the learned path 2230 from the starting position 2210, the processor of the vehicle 100 controls the object detecting apparatus 300 to move the empty parking slot Search.

When the vehicle 100 arrives at the empty parking slot 2240, the processor of the vehicle 100 may be a camera 310, a radar 320, an LR 330, an ultrasonic sensor 340 and the infrared sensor 350 to detect an empty parking slot 2240.

In addition, the processor of the vehicle 100 can detect an empty parking slot 2240 using information about the attributes of the object stored in the learning of the path. For example, the processor of the vehicle 100 can detect an empty parking slot 2240 by detecting a parking line or detecting the position where the other vehicle was parked in the learning step described above.

That is, the processor of the vehicle 100 can detect the parking slot 2240 which is more accurate by using together the detection result of the object detecting apparatus 300, as well as the object information on the path stored in the learning step.

Next, the processor of the vehicle 100 controls the above-described parking system 750 to automatically park the vehicle 100 in the detected parking slot 2240.

According to another embodiment of the present invention, when a plurality of empty parking slots are detected, a step of selecting a specific parking slot may be added. The processor of the vehicle 100 can preset the priority for the parking slot. For example, the distance from the exit to the parking slot may be set to a priority. In this case, the processor of the vehicle 100 controls the vehicle 100 to be parked in a parking slot closer to the exit from the exit when a plurality of parking slots are detected.

Meanwhile, according to another embodiment of the present invention, the processor of the vehicle 100 stores position information of an empty parking slot 2240. The processor of the vehicle 100 uses the stored location information at the exit to determine whether to return to the departure location 2210 along the path 2230 that ran for parking or to go to the end location 2220 along the remaining path 2250 Can be determined.

23 shows that the processor of the vehicle 100 according to another embodiment of the present invention parks the vehicle 100 in an empty parking slot on the learned route.

23 shows a method for correcting a learned parking path in the case of a reserved or reserved parking slot in a private parking space, such as a garage, when an obstacle that was not present in the learning step is present in the parking procedure. 23 (a), the end position 2320 corresponds to the position of the reserved parking slot.

When parking in a reserved parking slot, if an object not detected in the step of learning the route is detected in the reserved parking slot, the processor of the vehicle 100 considers the area occupied by the object in the reserved parking slot And determines the area in which the vehicle 100 can park. Next, the processor of the vehicle 100 parks the vehicle 100 in the parkable area.

More specifically, FIG. 23A shows that the vehicle 100 travels along the travel path 2330 learned from the start position 2310 to the end position 2320. More specifically, FIG. 23A shows that the obstacle 2340, which is not present in the learning step, is obstructing the automatic parking of the vehicle 100 at the ending position 2320, unlike the embodiment of FIG. .

If the unexpected obstacle 2340 interferes with the parking at the end position 2320, the processor of the vehicle 100 firstly transmits the obstacle 2340 through the object detecting apparatus 300 as shown in FIG. ).

Then, the processor of the vehicle 100 determines whether or not the vehicle 100 can park in an area other than the area occupied by the obstacle 2340 in the parking slot.

Finally, the processor of the vehicle 100 avoids the obstacle 2340 and creates a new path 2350 to allow the vehicle 100 to park.

24 shows that the processor of the vehicle 100 according to another embodiment of the present invention parks the vehicle 100 in an empty parking slot on the learned route.

Fig. 24 shows another embodiment of the present invention related to Fig. That is, when there is an obstacle that was not present in the learning step in the learned parking slot, a new route to park the obstacle is generated.

In Fig. 23, since the parking slot is a private parking space such as a garage, it is not necessary to consider other vehicles. However, since the parking slot in Fig. 24 is a public parking lot, it is important not to obstruct the parking and departure of other vehicles.

24 (a) to 24 (d) show that an obstacle 2410, which did not exist in the learning stage, exists in the parking slot. In this case, the processor of the vehicle 100 does not generate a parking locus that simply avoids obstacles as shown in Figs. 24A to 24B, but rather recognizes the parking line as shown in Figs. 24C to 24D Thereby controlling the vehicle 100 to be parked in a parking slot adjacent thereto.

As described above, the present invention according to the embodiment of FIG. 24 has a technical effect of grasping the surrounding space in parking avoiding an obstacle so as not to obstruct traffic and parking of other vehicles.

22 to 24, a method of parking the vehicle 100 in an empty parking slot on the learned route of the processor of the vehicle 100 has been described. 25 to 31, a learning-based vehicle departure method according to an embodiment of the present invention will be described.

25 shows a learning-based vehicle departure method according to an embodiment of the present invention.

25 is for an outbound process after the vehicle 100 is parked in the detected parking slot, according to the embodiment of FIGS. 22-24.

The processor of the vehicle 100 stores the position of the detected parking slot 2520 in the memory 140 when the vehicle 100 is parked in the detected parking slot 2520. [

After the point in time when the vehicle 100 is parked, the processor of the vehicle 100 receives user input for leaving the vehicle 100, via the user interface device 200.

In response to user input, the processor of the vehicle 100 invokes the memory 140 with information about the location of the parked parking slot 2520 and the learned path 2530 of the vehicle 100.

The processor of the vehicle 100 generates an outgoing route 2530 from the parking slot to the end position that includes at least a portion of the learned route and along the generated outgoing route 2530, .

25, the processor of the vehicle 100 stores information about the parking trajectory in the parking step 140 and stores information about the stored parking trajectory in the memory 140 It is possible to control the vehicle 100 to exit.

On the other hand, unlike FIG. 25, there may be a case where the vehicle 100 has to return to the starting position before the vehicle 100 is parked in the parking slot. For example, after the user of the vehicle 100 gets out of the starting position and the vehicle 100 starts to travel on the learned route in the self-running mode, when the user wishes the vehicle 100 to return to the starting position again There may be cases.

The processor of the vehicle 100 receives user input via the user interface device 200 requesting the vehicle 100 to return to the starting or ending position again. For convenience, the request is referred to as a roll-back request.

When the processor of the vehicle 100 receives the rollback request, it determines the position of the vehicle 100 on the learned route 2510, 2530. Based on the determined position, the processor of the vehicle 100 determines whether to continue running in the direction in which it is running or in the opposite direction to the direction in which it was running.

The processor of the vehicle 100 stops the vehicle 100 and detects the space for changing the running direction through the object detecting apparatus 300. [

Finally, the processor of the vehicle 100 controls the traveling direction of the vehicle 100 to be changed using the detected space, and performs the traveling for returning to the starting position or the ending position.

26 shows a learning-based vehicle departure method according to another embodiment of the present invention.

More specifically, Fig. 26 shows an example in which, when the vehicle 100 can not exit using the information on the parking trajectory stored in the parking step owing to the other vehicle 2610 existing in front of the parking slot, Lt; / RTI >

The object detecting apparatus 300 of the vehicle 100 can detect an object located outside the vehicle 100. [ Taking Fig. 26 as an example, the processor of the vehicle 100 determines whether or not there is an obstacle in the rear of the vehicle 100, information indicating that another vehicle 2610 exists in front of the vehicle 100 through the object detecting apparatus 300 Information can be obtained.

Next, the processor of the vehicle 100 creates a new travel route 2620 that can move the vehicle 100 backward and return the learned travel route 2630 to the learned route. Then, the processor of the vehicle 100 controls the vehicle 100 to travel along the generated travel route 2620.

A method of detecting that the vehicle 100 returns to the learned travel route 2630 will be described. First, the processor of the vehicle 100 determines the current position of the vehicle 100 through the object detection device 300, the position information part 420, and the like.

Next, the processor of the vehicle 100 judges whether meaningful information such as a landmark such as a corner or a landmark stored in the learning stage is detected in the image photographed by the camera 310 at the current position of the vehicle 100 do. When meaningful information is detected, the processor of the vehicle 100 can determine that the vehicle 100 has reached the learned route.

When the vehicle 100 reaches the existing learned travel route 2630 at the location 2640, the processor of the vehicle 100 controls the vehicle 100 to depart along the existing learned travel route 2630 .

As described above, the present invention according to FIG. 26 has a technical effect of generating an outgoing route adaptively changed according to the environmental conditions of the vehicle at the time of departure.

FIG. 27 shows a learning-based vehicle departure method according to another embodiment of the present invention.

27 shows a case where the position of the vehicle is changed after the time when the vehicle 100 is parked, such as when the vehicle 100 is moved forward or backward by an external force after being double-parked.

In FIG. 27, the case where the changed position of the vehicle 100 is within the previously learned route and the case where the changed position is outside the route will be described separately. The processor of the vehicle 100 can determine the changed position of the vehicle 100 through the object detection device 300. [

In the case where the changed position of the vehicle 100 is within the previously learned route, that is, when the vehicle 100 moves forward (a) in FIG. 27, the processor of the vehicle 100 moves the learned route And controls the vehicle 100 to exit along the road 2710.

On the other hand, when the changed position of the vehicle 100 is located outside the learned route, that is, when the vehicle 100 moves backward and is in the position shown in Fig. 27, The processor of the vehicle 100 generates a path for reaching the previously learned path 2710 and controls the vehicle 100 to exit the path using the generated path and the previously learned path 2710.

28 shows a learning-based vehicle departure method according to another embodiment of the present invention.

Fig. 28 relates to Fig. In FIG. 12, even if the vehicle 100 learns the obstacle due to the obstacle, the processor of the vehicle 100 avoids the obstacle and travels through the learned travel path if the obstacle is a temporary obstacle, And stores the shortest path as the learned path.

On the other hand, in Fig. 28 (a), the processor of the vehicle 100 learns a traveling route avoiding the obstacle 2810 in the learning stage. 28 (b), when the processor of the vehicle 100 determines that the obstacle 2810 has disappeared through the object detection device 300 at the exit stage, the obstacle 2810 is not the already learned travel route 2820 Generates a shortest distance path 2830, and controls the vehicle 100 to exit along the shortest distance path 2830 generated.

That is, FIG. 12 relates to a method of storing a learning path in the shortest distance route, and FIG. 28 relates to a method of storing a learning route as an avoidance traveling route, and generating a shortest distance route at the time of departure.

FIG. 29 shows a learning-based vehicle departure method according to another embodiment of the present invention.

According to another embodiment of the present invention, the processor of the vehicle 100 may automatically change the departure route reflecting the changed surrounding environment information of the vehicle 100. [ That is, the processor of the vehicle 100 can detect an object existing outside the vehicle 100 through the object detection apparatus 300 and generate an advantageous route for reaching the learned route based on the detected object have.

29A and 29B show a case where the vehicle 100 is vertically parked and FIGS. 29C and 29D show a case where the vehicle 100 is parked in parallel.

29 (a) shows that the outgoing route 2920 is learned by the other vehicle 2910 parked on the right side of the vehicle 100. Fig. On the other hand, since there is no obstacle including the other vehicle 2910 on the right side of the vehicle 100 as shown in FIG. 29 (b), the processor of the vehicle 100 generates an easier or more advantageous outgoing route 2930 And controls the vehicle 100 to exit.

Likewise, FIG. 29C shows that the outgoing route 2950 has been learned by the other vehicle 2940 parked in front of the vehicle 100. FIG. On the other hand, since there are no obstacles including the other vehicle 2940 in front of the vehicle 100 as shown in FIG. 29 (d), the processor of the vehicle 100 generates an easier or more advantageous outgoing route 2960 And controls the vehicle 100 to exit.

Thus, the present invention as shown in FIG. 29 has a technical effect of generating an adaptively changed outgoing route when an outgoing route that is advantageous over the learned outgoing route can be generated as the surrounding environment changes.

30 to 31 show a learning-based vehicle departure method according to another embodiment of the present invention.

30 shows a case where the vehicle 100 has traced the traveling route 3010 and the user has identified the user 3020 within the learned traveling route using the camera 310 or the communication device 400 And stops before the identified user 3020 without driving to the end position 3030. [

In order to identify the user, a GPS module of the position information unit 420 may be used, or a face recognition method and a voice recognition method may be used.

On the other hand, Fig. 31 shows a case where the user 3120 is located outside the learned travel route, unlike Fig.

In this case, the vehicle 100 does not travel to the end position 3130, but creates a new route 3140 for stopping before the identified user 3120. [ Then, the vehicle 100 travels along the generated route 3140 and stops in front of the user 3120.

As described above, the present invention according to Figs. 30 to 31 can ensure user convenience by stopping in front of the user when the user is identified, without unconditionally traveling to the learned end position.

The present invention described above can be embodied as computer-readable codes on a medium on which a program is recorded. The computer readable medium includes all kinds of recording devices in which data that can be read by a computer system is stored. Examples of the computer readable medium include a hard disk drive (HDD), a solid state disk (SSD), a silicon disk drive (SDD), a ROM, a RAM, a CD-ROM, a magnetic tape, a floppy disk, , And may also be implemented in the form of a carrier wave (e.g., transmission over the Internet). In addition, the computer may include a processor or a control unit. Accordingly, the above description should not be construed in a limiting sense in all respects and should be considered illustrative. The scope of the present invention should be determined by rational interpretation of the appended claims, and all changes within the scope of equivalents of the present invention are included in the scope of the present invention.

100: vehicle

Claims (20)

A method of controlling an autonomous vehicle in a parking facility,
Learning a path that the autonomous vehicle traveled from a start position to an end position in a manual mode;
In an autonomous mode, starting traveling along the learned path; And
Parking the self-driving vehicle in the detected parking slot when an empty parking slot is detected on the learned route;
Wherein the self-propelled vehicle is a self-propelled vehicle. The method according to claim 1,
Wherein learning the path comprises:
Determining an attribute of the detected object on the path from the start position to the end position; And
Storing an attribute of the determined object;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 3. The method of claim 2,
Wherein the attribute of the object includes fixed information or mobile type information. 3. The method of claim 2,
Wherein learning the path comprises:
Wherein the autonomous vehicle travels a route different from the route on which the autonomous vehicle travels between the first position and the second position based on an attribute of the object determined between the first position and the second position in which the autonomous vehicle exists on the route Storing the learning path as a learning path;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. The method according to claim 1,
Wherein learning the path comprises:
Learning a partial path including at least one of a start position and an end position; And
Integrating the learned partial paths to generate an entire learning path;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. The method according to claim 1,
Wherein learning the path comprises:
Detecting at least one bifurcation point on a path that the autonomous vehicle travels; And
Storing a path connecting the detected at least one branch point as a learning path;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. The method according to claim 1,
In the self-running mode, starting the running along the learned route comprises:
Detecting, through the object detection device, that the autonomous vehicle arrives within a predetermined distance from the starting position; And
Receiving a user input through the user interface device to start traveling along the learned path;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. The method according to claim 1,
Further comprising receiving additional information regarding use of the parking facility,
In the self-running mode, starting the running along the learned route comprises:
Modifying the learned path by reflecting the received additional information; And
Starting traveling along the modified learned route;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. The method according to claim 1,
In the self-running mode, starting the running along the learned route comprises:
Receiving a user input requesting the autonomous vehicle to return to at least one of the start position and the end position; And
Controlling, in response to the user input, returning the autonomous vehicle to at least one of the start position and the end position along the learned path;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 10. The method of claim 9,
Controlling the autonomous vehicle to return to at least one of the start position and the end position along the learned path in response to the user input,
Determining a current position of the autonomous vehicle on the learned route; And
Determining whether to maintain the running direction of the autonomous vehicle based on the determination result;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 3. The method of claim 2,
Wherein parking the self-driving vehicle in the detected parking slot comprises:
Detecting an empty parking slot using information on the detection result through the object detection apparatus and the attribute of the object on the learned route stored in the learning of the route;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 12. The method of claim 11,
Wherein parking the self-driving vehicle in the detected parking slot comprises:
Selecting a specific parking slot based on a predetermined priority when a plurality of empty parking slots are detected;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. The method according to claim 1,
Wherein the parking slot is a reserved parking slot and the ending position is a position of the reserved parking slot. 14. The method of claim 13,
When parking in the reserved parking slot, if an object not detected in the step of learning the route is detected in the reserved parking slot,
Wherein parking the self-driving vehicle in the detected parking slot comprises:
Determining an area in which the autonomous vehicle can park in consideration of an area occupied by the object in the reserved parking slot; And
Parking the autonomous vehicle in the parkable area;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. The method according to claim 1,
Storing the position of the detected parking slot in a memory when the autonomous vehicle is parked in the detected parking slot;
Recalling information about the location of the parked parking slot and the learned route in response to user input; And
Controlling at least a part of the learned route to cause the autonomous vehicle to depart from the parking slot to the end position;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 16. The method of claim 15,
Detecting an object existing outside the autonomous vehicle through an object detection device; And
Generating a path that can reach the learned path based on the detected object;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 16. The method of claim 15,
When the position of the autonomous vehicle is changed after the time when the autonomous vehicle is parked,
Wherein the step of controlling the self-
Determining a position of the changed autonomous vehicle; And
When the determined position is within the learned route, controlling the autonomous traveling vehicle to exit using the learned route,
Generating a route to reach the learned route when the determined position is outside the learned route, and controlling the autonomous carriage to depart from the route using the generated route and the learned route;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 16. The method of claim 15,
Identifying a user of the autonomous vehicle;
Determining whether the identified user's location is within the learned path; And
Controlling the autonomous vehicle to stop at a position of the identified user when it is determined that the identified user's position is within the learned path;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. 19. The method of claim 18,
If it is determined that the position of the identified user is out of the learned route,
Generating a path for reaching the identified user's location; And
Controlling the autonomous traveling vehicle to travel along a path for reaching the identified user's position;
Further comprising the steps of: determining whether the vehicle is a self-propelled vehicle. In an autonomous vehicle,
In the manual mode, the route on which the autonomous vehicle travels from the start position to the end position is learned,
In the self-running mode, starts running along the learned route,
A processor for parking the self-driving vehicle in the detected parking slot when an empty parking slot is detected on the learned route through the object detection device;
.

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