KR102343020B1 - Apparatus for calibrating position signal of autonomous vehicle using road surface image information - Google Patents

Apparatus for calibrating position signal of autonomous vehicle using road surface image information Download PDF

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KR102343020B1
KR102343020B1 KR1020200159571A KR20200159571A KR102343020B1 KR 102343020 B1 KR102343020 B1 KR 102343020B1 KR 1020200159571 A KR1020200159571 A KR 1020200159571A KR 20200159571 A KR20200159571 A KR 20200159571A KR 102343020 B1 KR102343020 B1 KR 102343020B1
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road surface
vehicle
position signal
gps
autonomous vehicle
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김태형
윤경수
조봉균
이명수
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재단법인 지능형자동차부품진흥원
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B60W40/076—Slope angle of the road
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
    • G06K9/00798—
    • B60W2420/42—
    • B60W2420/52—
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/15—Road slope, i.e. the inclination of a road segment in the longitudinal direction
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/50—External transmission of data to or from the vehicle of positioning data, e.g. GPS [Global Positioning System] data
    • G05D2201/0213—

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  • Automation & Control Theory (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Physics & Mathematics (AREA)
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  • Aviation & Aerospace Engineering (AREA)
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Abstract

The present invention relates to an apparatus for correcting a GPS location signal of an autonomous vehicle by using road surface image information obtained during driving. According to the present invention, the autonomous vehicle corrects the GPS vehicle location signal which is inevitably affected by a slope of the driving road to be suitable for the position of the vehicle. Therefore, the vehicle location is accurately recognized during autonomous driving and an accident is prevented as the apparatus responses to surrounding environmental information without error. The location signal correction apparatus comprises a camera, a road surface slope measurement unit, and a GPS location signal correction unit.

Description

노면 영상정보를 이용한 자율주행 차량의 위치신호 보정장치{Apparatus for calibrating position signal of autonomous vehicle using road surface image information}Apparatus for calibrating position signal of autonomous vehicle using road surface image information

본 발명은 주행 중 취득되는 노면의 영상정보를 이용하여 자율주행 차량의 GPS 위치 신호를 보정하는 장치에 관한 것이다. The present invention relates to an apparatus for correcting a GPS position signal of an autonomous vehicle by using image information of a road surface acquired while driving.

최근 운전자의 개입이 전혀 없거나, 최소화하면서 운전자와 탑승자를 안전하게 운송하는 자율주행 차량의 개발이 활발하게 이루어지고 있다. In recent years, the development of autonomous vehicles that safely transport the driver and passengers with no or minimal driver intervention is being actively developed.

자율주행 차량은 운전자의 개입 없이 주행 차선의 유지, 인접차량과의 안전거리 확보와 근접 장애물의 검출과 충돌회피 등과 같이 교통상황이나 도로 환경에 따른 차량속도 제어 등이 자동으로 수행된다. Autonomous vehicles automatically perform vehicle speed control according to traffic conditions or road environments, such as maintaining a driving lane, securing a safe distance from adjacent vehicles, detecting nearby obstacles, and avoiding collisions without driver intervention.

이와 같은 자율주행이 이루어지도록 차량에는 주변 환경을 감지하는 카메라, 레이더(Radio Detecting And Ranging; RADAR), 라이다(Light Detection And Ranging; LIDAR), 초음파 센서 등 다양한 센서가 장착된다.To achieve such autonomous driving, various sensors such as a camera that detects the surrounding environment, a radar (Radio Detecting And Ranging; RADAR), a Light Detection And Ranging (LIDAR), and an ultrasonic sensor are installed in the vehicle.

자율주행 차량은 다수의 센서로부터 감지되는 주변정보를 융합하여 차량의 주변 환경을 인식하는데, 정확하게 주위 환경을 인식하도록 차량에 장착된 각각의 센서로부터 감지되는 정보가 정확하게 융합되어야 하는데, 이를 위해서는 센서 상호 간의 보정이 이루어지고 있다. The autonomous driving vehicle recognizes the surrounding environment of the vehicle by fusing the surrounding information sensed from multiple sensors. In order to accurately recognize the surrounding environment, the information sensed from each sensor installed in the vehicle must be accurately fused. Intermediate correction is being made.

이와 같은 보정은 주로 라이다와 카메라와 같이 시야각이 서로 다른 센서 간에 주로 이루어지고 있는 것과 비교하여, GPS 센서로 측정되는 위치신호의 경우 차량의 실제 위치와 일치되도록 보정이 이루어지지 않고 있다.Compared to the case where the correction is mainly performed between sensors having different viewing angles, such as lidar and camera, in the case of a position signal measured by a GPS sensor, correction is not made to match the actual position of the vehicle.

즉, 도 1에 도시되는 바와 같이 자율주행 차량(20)은 경사진 노면(30)을 주행하는 경우, 노면(30)의 경사각(θ)으로 인하여 GPS 위성(10)을 통하여 측정되는 차량의 위치와 실제 위치와는 편차(△S)가 발생함에 따라, 차량의 위치를 정확하게 인지할 수 없는 문제가 있다. That is, as shown in FIG. 1 , when the autonomous vehicle 20 travels on the inclined road surface 30 , the location of the vehicle measured through the GPS satellite 10 due to the inclination angle θ of the road surface 30 . As there is a deviation (ΔS) from the actual position, there is a problem in that the position of the vehicle cannot be accurately recognized.

대한민국 공개특허공보 제10-2018-0055292호(발명의 명칭: 다중 라이다 좌표계 통합 방법)Republic of Korea Patent Publication No. 10-2018-0055292 (Title of the Invention: Multi-LiDAR Coordinate System Integration Method) 대한민국 공개특허공보 제10-2014-0065627호(발명의 명칭: 차량용 카메라 캘리브레이션 장치 및 방법)Korean Patent Laid-Open Publication No. 10-2014-0065627 (Title of the Invention: In-vehicle camera calibration apparatus and method)

따라서, 본 발명은 자율주행 차량이 경사진 노면을 주행하더라도 정확한 차량의 위치를 인지할 수 있도록 GPS의 위치정보를 보정할 수 있는 자율주행 차량의 위치신호 보정장치를 제공하는데 그 목적이 있다. Accordingly, an object of the present invention is to provide an apparatus for correcting a location signal of an autonomous vehicle capable of correcting location information of a GPS so that the autonomous vehicle can accurately recognize the location of the vehicle even when the autonomous vehicle travels on an inclined road surface.

상기와 같은 기술적 과제를 해결하기 위하여, 본 발명은 자율주행 차량의 주변 환경을 영상 데이터로 취득하는 카메라, 영상 데이터로부터 노면을 인식하고 상기 노면의 경사각을 측정하는 노면경사 측정부 및, 노면의 경사각에 의해 산출된 보정값으로 GPS 위치신호를 보정하는 GPS 위치신호 보정부를 구비하는 자율주행 차량의 위치신호 보정장치를 제공한다. In order to solve the above technical problem, the present invention provides a camera for acquiring the surrounding environment of an autonomous vehicle as image data, a road slope measuring unit for recognizing a road surface from the image data and measuring an inclination angle of the road surface, and an inclination angle of the road surface To provide an apparatus for correcting a position signal for an autonomous vehicle having a GPS position signal correcting unit for correcting a GPS position signal with a correction value calculated by .

본 발명에 있어서, GPS 위치신호 보정부는 GPS 위치신호에 의해 측정된 노면의 지점과, 경사각이 형성된 노면 상에 위치한 차량의 중심선이 노면과 직각으로 만나는 노면의 지점과의 차이를 보정값으로 산출한다. In the present invention, the GPS position signal correcting unit calculates the difference between a point on the road surface measured by the GPS location signal and a point on the road surface where the center line of the vehicle located on the road surface on which the inclination angle is formed meets the road surface at a right angle to the road surface as a correction value. .

본 발명에 있어서, GPS 위치신호 보정부는 노면경사 측정부에 의해 측정된 노면의 경사각과, 차량에 구비되는 관성센서로부터 측정된 노면의 경사각으로부터 산출된 보정값으로 GPS 위치신호를 보정한다. In the present invention, the GPS position signal correcting unit corrects the GPS position signal with a correction value calculated from the inclination angle of the road surface measured by the road surface inclination measurement unit and the inclination angle of the road surface measured by an inertial sensor provided in the vehicle.

본 발명에 있어서, 노면경사 측정부는 카메라로부터 취득되는 영상 데이터와 함께 차량에 구비되는 라이더 센서에 의해 측정되는 영상 데이터로부터 노면을 인식하고 노면의 경사각을 측정한다. In the present invention, the road slope measuring unit recognizes the road surface from the image data measured by the lidar sensor provided in the vehicle together with the image data obtained from the camera and measures the inclination angle of the road surface.

본 발명에 있어서, 노면경사 측정부는 라이다 센서에 의해 측정되는 전방 노면과의 거리정보에 대응하여 노면 경사각을 측정한다.In the present invention, the road slope measuring unit measures the road slope angle in response to distance information with the front road surface measured by the lidar sensor.

본 발명에 따르면, 자율주행 차량은 주행하는 노면의 경사각으로 인한 필연적으로 발생하는 GPS 차량 위치신호를 보정함으로써, 자율 주행 시 보다 정확한 차량위치를 인지하여 주변의 환경정보에 오류 없이 대응하여 사고 등을 예방할 수 있다.According to the present invention, the autonomous vehicle recognizes a more accurate vehicle location during autonomous driving by correcting the GPS vehicle location signal that is inevitably generated due to the inclination angle of the driving road surface, and responds without errors to surrounding environmental information to prevent accidents, etc. It can be prevented.

도 1은 경사진 노면에 위치하는 자율주행 차량을 도시한 도면이다.
도 2는 본 발명에 따른 자율주행 차량의 위치신호 보정장치의 구성을 도시한 블록도이다.
도 3(a),(b)는 각각 자율주행 차량에 장착된 라이다 및 카메라에 의해 취득되는 영상의 예를 도시한 도면이다.
도 4는 차량의 GPS 위치정보와 노면의 경사각에 따른 차량 위치를 도시한 도면이다.1 is a diagram illustrating an autonomous vehicle positioned on a sloped road surface.
2 is a block diagram illustrating a configuration of an apparatus for correcting a position signal for an autonomous vehicle according to the present invention.
3A and 3B are diagrams illustrating examples of images acquired by a lidar and a camera mounted on an autonomous vehicle, respectively.
4 is a view illustrating a vehicle location according to GPS location information of the vehicle and an inclination angle of a road surface.

이하, 첨부 도면을 참조하여 본 발명의 실시예를 상세히 설명한다. Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

본 실시 예는 당업계에서 평균적인 지식을 가진 자에게 본 발명을 보다 완전하게 설명하기 위해서 제공되어지는 것으로서, 도면에서의 요소의 형상, 요소의 크기, 요소간의 간격 등은 보다 명확한 설명을 강조하기 위해서 과장되거나 축소되어 표현될 수 있다.This embodiment is provided to more completely explain the present invention to those with average knowledge in the art, and the shape of elements in the drawings, the size of elements, the spacing between elements, etc. are emphasized more clearly may be exaggerated or reduced for

또한, 실시 예를 설명하는데 있어서, 만일 어떤 구성요소가 다른 구성요소에 "형성되어", "포함되어", "결합되어", "고정되어" 있다고 기재된 때에는, 그 다른 구성요소에 직접적으로 형성, 포함, 결합 또는 고정되어 있을 수도 있지만, 중간에 다른 구성요소가 존재할 수도 있다고 이해되어야 할 것이다.In addition, in describing the embodiment, if a component is described as “formed”, “included”, “coupled”, or “fixed” to another component, it is formed directly in the other component, It may be included, coupled, or fixed, but it will be understood that other components may be present in between.

또한, 실시 예를 설명하는데 있어서 원칙적으로 관련된 공지의 기능이나 공지의 구성과 같이 이미 당해 기술 분야의 통상의 기술자에게 자명한 사항으로서 본 발명의 기술적 특징을 불필요하게 흐릴 수 있다고 판단되는 경우에는 그 상세한 설명을 생략하기로 한다. In addition, when it is determined that the technical features of the present invention may be unnecessarily obscured as it is already obvious to a person skilled in the art, such as a known function or a known configuration related in principle in explaining the embodiment, the detailed description thereof A description will be omitted.

본 발명은 자율주행 차량이 주행 중에 인식되는 노면의 경사각에 따라 GPS 센서로 인식되는 차량의 위치정보를 보정하는 기술로, 도 2에 본 발명에 따른 위치신호 보정장치(100)의 구성이 개시되어 있다. The present invention is a technology for correcting location information of a vehicle recognized by a GPS sensor according to an inclination angle of a road surface recognized while an autonomous vehicle is driving. have.

본 발명은 GPS 센서(110), 카메라(120), 노면경사 측정부(130), 라이다 센서(140), GPS 위치신호 보정부(150), 및 관성센서(160)로 이루어진다. 이와 같은 위치신호 보정장치(100)의 구성은 하드웨어 모듈 또는 소프트웨어 모듈 형태로 구현되거나, 하드웨어 모듈과 소프트웨어 모듈이 조합된 형태로도 구현될 수 있다. 여기서, 소프트웨어 모듈이란, 예컨대 위치신호 보정장치(100) 내에서 연산을 수행하는 프로세서에 의해 실행되는 명령어로 이해될 수 있으며, 이러한 명령어는 위치신호 보정부(100)내 메모리에 탑재된 형태를 가질 수 있을 것이다. The present invention includes a GPS sensor 110 , a camera 120 , a road slope measuring unit 130 , a lidar sensor 140 , a GPS position signal correcting unit 150 , and an inertial sensor 160 . Such a configuration of the position signal correcting apparatus 100 may be implemented in the form of a hardware module or a software module, or may be implemented in a form in which a hardware module and a software module are combined. Here, the software module may be understood as, for example, an instruction executed by a processor that performs an operation in the position signal correcting device 100 , and these instructions have a form mounted in a memory in the position signal correcting unit 100 . will be able

GPS(Global Positioning System) 센서(110)는 GPS 위성(10)에서 전송하는 신호를 수신하여 차량의 위치를 감지하도록 자율주행 차량에 장착되는 센서이다. GPS 센서(110)로 인식되는 차량의 현재위치는 도 1에 도시된 바와 같이, GPS 위성(10)과 차량(20)을 연결하는 직선(L1)이 만나는 지점(S1)의 좌표이다. The Global Positioning System (GPS) sensor 110 is a sensor mounted on the autonomous vehicle to detect the location of the vehicle by receiving a signal transmitted from the GPS satellite 10 . As shown in FIG. 1 , the current location of the vehicle recognized by the GPS sensor 110 is the coordinate of the point S 1 where the straight line L 1 connecting the GPS satellite 10 and the vehicle 20 meets.

카메라(120)는 GPS 센서(110)와 함께 자율주행 차량(20)에 탑재되어 차량 주변의 환경을 영상 데이터로 취득하는데, 취득된 영상 데이터는 후술하는 노면경사 측정부(130)에 의해 노면(30)을 인식하도록 활용된다. 카메라(120)로는 적외선 카메라, RGB 카메라, RGB-Depth 카메라 및 열화상 카메라 중 어느 하나가 사용될 수 있다. The camera 120 is mounted on the autonomous vehicle 20 together with the GPS sensor 110 to acquire the environment around the vehicle as image data, and the acquired image data is used by the road slope measuring unit 130 to be described later. 30) is used to recognize As the camera 120 , any one of an infrared camera, an RGB camera, an RGB-Depth camera, and a thermal imaging camera may be used.

영상 센서(120)로는 레이저가 조사되는 객체의 반사광을 입체 영상(stereo image)으로 매핑하는 라이다(Light Detection And Ranging; LIDAR), 이미지 센서가 탑재되어 차량 주변의 이미지를 촬영하는 카메라가 사용될 수 있다. 도 3(a)에 도시된 바와 같이 라이다에서 취득되는 영상(200)은 차량 주변의 공간정보를 획득하는데 용이하고, 도3(b)에 도시된 바와 같이 카메라에 의해 취득되는 영상(300)은 해당 공간에 존재하는 특정 객체의 정보를 취득하는데 유용하여, 주변 환경을 보다 정확하게 인식하도록 이들 라이다와 카메라의 영상은 융합되어 활용된다. As the image sensor 120, a light detection and ranging (LIDAR) that maps reflected light of an object irradiated with a laser to a stereo image, and a camera equipped with an image sensor to capture images around the vehicle may be used. have. As shown in Fig. 3(a), the image 200 acquired from the lidar is easy to acquire spatial information around the vehicle, and the image 300 acquired by the camera as shown in Fig. 3(b). is useful for acquiring information on specific objects in the space, and the images of these lidars and cameras are fused and utilized to more accurately recognize the surrounding environment.

노면경사 측정부(130)는 카메라(120)에 의해 취득된 차량(10)의 전방 주행경로의 영상 데이터로부터 노면(30)을 인식하고 노면의 경사각를 측정한다. 이때, 노면경사 측정부(130)는 보다 정확한 노면(30)을 인식하도록 자율주행 차량(20)에 장착된 라이다(150.Light Detection And Ranging; LIDAR) 센서로부터 획득한 3차원 입체영상(stereo image)을 더 활용할 수도 있다. The road inclination measuring unit 130 recognizes the road surface 30 from the image data of the forward driving path of the vehicle 10 acquired by the camera 120 and measures the inclination angle of the road surface. At this time, the road slope measuring unit 130 obtains a three-dimensional stereoscopic image (stereo) obtained from a LIDAR (Light Detection And Ranging; LIDAR) sensor mounted on the autonomous driving vehicle 20 to more accurately recognize the road surface 30 . image) can also be used.

라이다 센서(140)는 주행 중 발견되는 객체로 레이저를 조사하여 반사되는 광으로부터 객체와의 거리와 3차원 입체영상을 획득하는 센서로, 라이다 센서(140)에 의해 취득한 입체영상(200)의 예가 도 3(a)에 도시되어 있는데, 도시된 바와 같이 차량 주변의 공간정보를 인식하는데 유용하다. 이와 비교하여, 카메라의 영상 데이터(300)가 도 3(b)에 도시되어 있는데, 도시된 바와 같이 주행 중 라이다 센서(140)에 의해 인식되는 공간정보 내의 객체와 같은 특징정보를 취득하는데 유리하다. The lidar sensor 140 is a sensor that irradiates a laser to an object found while driving and obtains a distance to the object and a three-dimensional image from the reflected light. The stereoscopic image 200 acquired by the lidar sensor 140 is An example of is shown in Fig. 3(a), which is useful for recognizing spatial information around a vehicle as shown. In comparison, the image data 300 of the camera is shown in FIG. 3(b), which is advantageous for acquiring characteristic information such as objects in spatial information recognized by the lidar sensor 140 while driving as shown. do.

따라서, 노면경사 측정부(130)는 라이다 센서(140)로부터 취득되는 공간정보와 카메라(120)로부터 취득되는 공간정보 내의 특징정보를 융합하여 노면(30)을 인식할 수 도 있다. 이와 같은 노면의 인식은 딥 러닝을 통해 다양한 노면 이미지를 학습한 인식기가 적용될 수 있으며, 노면경사 측정부(130)는 인식된 노면으로부터 노면(30)의 경사각을 측정한다.Accordingly, the road slope measuring unit 130 may recognize the road surface 30 by fusing the spatial information acquired from the lidar sensor 140 and the feature information in the spatial information acquired from the camera 120 . Such recognition of the road surface may be applied to a recognizer that has learned various road surface images through deep learning, and the slope measuring unit 130 measures the inclination angle of the road surface 30 from the recognized road surface.

도 4는 차량의 GPS 위치정보와 노면(30)의 경사각에 따른 차량의 위치가 도시된 도면으로, 이를 참조하면 먼저 인식된 전방의 노면(30) 상에 양측으로 이격된 두 지점(P1, P2)을 선정하고 이를 연결하여 노면선(LSUR)을 설정한다. 그리고, 차량이 주행되는 지점인 노면선(LSUR)의 이등분 지점(S2)을 설정하는데, 이때 지점(S2)은 도 4에 도시된 바와 같이 차량(20)의 중심선(L2)이 노면(30)과 직각으로 만나는 노면 지점이다. 그리고, 설정된 이등분 지점(S2)과 두 지점(P1, P2) 중 어느 한 지점을 연결하는 직선(L3)이 수평선(LO)과 이루는 경사각(θ)을 측정한다. 이와 같은 노면의 경사각(θ)은 설정된 소정시간 간격으로 측정되며, 라이다 센서(140)에 의해 측정되는 전방 노면(30)과의 거리정보에 대응하여 측정된다.4 is a view showing the position of the vehicle according to the GPS location information of the vehicle and the inclination angle of the road surface 30. Referring to this, two points (P 1 , Select P 2 ) and connect them to set the road surface line (L SUR ). And, the bisector point S 2 of the road surface line L SUR which is a point at which the vehicle is driven is set, at this time the point S 2 is the center line L 2 of the vehicle 20 as shown in FIG. 4 . It is a road surface point that meets the road surface 30 at a right angle. Then, the measuring set bisector point (S 2) and two points (P 1, P 2) straight line connecting any one point of the (L 3) a horizontal line (L O) and constituting the tilt angle (θ). The inclination angle θ of the road surface is measured at a set predetermined time interval, and is measured in response to distance information from the front road surface 30 measured by the lidar sensor 140 .

GPS 위치신호 보정부(150)는 측정된 노면의 경사각(θ)에 따라 GPS 센서(110)로 측정된 위치정보를 보정하는데, 도 4에 경사진 노면(30)에 위치하는 자율주행 차량(20)의 위치정보를 보정하는 과정이 도시되어 있다. The GPS position signal correcting unit 150 corrects the position information measured by the GPS sensor 110 according to the measured inclination angle θ of the road surface, and the autonomous vehicle 20 located on the inclined road surface 30 in FIG. ), the process of correcting the location information is shown.

GPS 위치신호 보정부(150)는 경사각(θ)이 측정된 노면에서 GPS 센서(110)로 측정되는 위치정보 즉, 도 4에서 GPS 위성(10)과 차량(20)을 일 직선으로 연결하는 직선(L1)이 만나는 노면 지점(S1)과, 경사진 노면(30)에 위치한 차량(20)의 중심선(L2)이 노면(30)과 직각으로 만나는 노면 지점(S2)과의 차이를 보정값으로 산출한다. 이와 같이 산출되는 보정값은 이들 노면 지점(S1, S2)의 좌표값 편차로, 소정시간 간격으로 측정되는 노면의 경사각(θ)에 따라 산출된다. The GPS position signal correcting unit 150 includes position information measured by the GPS sensor 110 on the road surface on which the inclination angle θ is measured, that is, a straight line connecting the GPS satellite 10 and the vehicle 20 in a straight line in FIG. 4 . a road surface point (S 1) and a center line of the vehicle 20 is located on an inclined road surface 30 (L 2) the difference between the road surface 30, at right angles with the road surface the point of intersection to the (S 2) (L 1) is met is calculated as a correction value. The correction value calculated in this way is the deviation of the coordinate values of these road surface points S 1 , S 2 , and is calculated according to the inclination angle θ of the road surface measured at predetermined time intervals.

GPS 위치신호 보정부(150)는 이와 같이 전방 노면에 따라 보정값을 산출하고, 차량(20)이 진행하여 해당 경사각(θ)을 가지는 노면(30)에 이르면, GPS 센서(110)로 출력되는 위치정보를 보정한다. GPS 위치신호 보정부(150)는 보정값을 보다 정밀하게 산출하기 위하여, 상술한 바와 같이 측정된 노면(30)의 경사각(θ)과, 관성센서(170)로 측정된 해당 노면(30)의 경사각(θ)과 비교하여 두 측정값의 평균을 경사각(θ)으로 산출할 수도 있다. The GPS position signal correcting unit 150 calculates a correction value according to the front road surface in this way, and when the vehicle 20 proceeds and reaches the road surface 30 having the corresponding inclination angle θ, it is output to the GPS sensor 110 Correct location information. The GPS position signal correcting unit 150 includes the inclination angle θ of the road surface 30 measured as described above and the corresponding road surface 30 measured by the inertial sensor 170 in order to more precisely calculate the correction value. The average of the two measured values may be calculated as the inclination angle θ compared with the inclination angle θ.

이와 같이, 본 발명에 따르면 자율주행 차량은 주행하는 노면의 경사각으로 인한 필연적으로 발생하는 GPS 차량 위치신호를 차량의 위치에 맞게 보정할 수 있다. As described above, according to the present invention, the autonomous driving vehicle can correct the GPS vehicle position signal, which is inevitably generated due to the inclination angle of the driving road, to match the position of the vehicle.

따라서, 자율 주행 시 보다 정확한 차량위치를 인지할 수 있어, 주변의 환경정보에 오류 없이 대응하여 사고 등을 예방할 수 있다.Accordingly, it is possible to recognize a more accurate vehicle location during autonomous driving, and thus, it is possible to prevent an accident by responding to environmental information around the vehicle without errors.

이상 설명한 본 발명은 기재된 실시 예에 한정되는 것은 아니고, 본 발명의 사상 및 범위를 벗어나지 않고 다양하게 수정 및 변형할 수 있음은 이 기술의 분야에서 통상의 지식을 가진 자에게 자명하다. 따라서 그러한 변형 예 또는 수정 예들은 본 발명의 특허청구범위에 속한다 해야 할 것이다.The present invention described above is not limited to the described embodiments, and it is apparent to those skilled in the art that various modifications and variations can be made without departing from the spirit and scope of the present invention. Accordingly, it should be said that such variations or modifications fall within the scope of the claims of the present invention.

10 : 라이다 영상 데이터 　20 : 자율주행 차량
30 : 노면 100 : 위치정보 보정장치
110 :　GPS 센서 120 : 카메라
130 : 노면경사 측정부 140 : 라이다 센서
150 :　GPS 위치신호 보정부 160：관성센서
P1, P2 : 노면 지점 L1 : 직선
L2 : 차량 중심선 LO : 수평선
LSUR : 노면선 θ : 노면경사각
S1 : 직선 L1 과 만나는 노면지점
S2 : 차량 중심선 L2 와 만나는 노면지점
△S : S1, S2 사이의 편차10: lidar image data 20: autonomous vehicle
30: road surface 100: location information correction device
110: GPS sensor 120: camera
130: road slope measuring unit 140: lidar sensor
150: GPS position signal correction unit 160: inertial sensor
P 1 , P 2 : Road surface point L 1 : Straight
L 2 : vehicle center line L O : horizontal
L SUR : Road surface line θ : Road slope angle
S 1 : The point of the road where the straight line L 1 meets
S 2 : The road surface point where the vehicle center line L 2 meets
△S : S 1 , S 2 between Deviation

Claims (5)

자율주행 차량의 GPS 위치신호를 보정하는 장치에 있어서,
상기 차량의 주변 환경을 영상 데이터로 취득하는 카메라;
상기 영상 데이터로부터 노면을 인식하고 상기 노면의 경사각을 측정하는 노면경사 측정부; 및,
상기 GPS 위치신호에 의해 측정된 노면의 지점과, 상기 경사각이 형성된 노면 상에 위치한 상기 차량의 중심선이 노면과 직각으로 만나는 노면의 지점과의 차이로 보정값을 산출하여 GPS 위치신호를 보정하는 GPS 위치신호 보정부;를 구비하는 것을 특징으로 하는 자율주행 차량의 위치신호 보정장치.An apparatus for correcting a GPS position signal of an autonomous vehicle, comprising:
a camera for acquiring the surrounding environment of the vehicle as image data;
a road slope measuring unit for recognizing a road surface from the image data and measuring an inclination angle of the road surface; and,
GPS for correcting the GPS position signal by calculating a correction value as a difference between a point on the road surface measured by the GPS location signal and a point on the road surface where the center line of the vehicle located on the road surface on which the inclination angle is formed meets the road surface at a right angle A position signal correcting device for an autonomous vehicle, comprising: a position signal correcting unit. 삭제delete 삭제delete 제1항에 있어서,
상기 노면경사 측정부는,
상기 카메라로부터 취득되는 영상 데이터와 함께 상기 차량에 구비되는 라이더 센서에 의해 측정되는 영상 데이터로부터 노면을 인식하고 상기 노면의 경사각을 측정하는 것을 특징으로 하는 자율주행 차량의 위치신호 보정장치.The method of claim 1,
The road slope measuring unit,
The apparatus for correcting a position signal for an autonomous vehicle, characterized in that the road surface is recognized from image data measured by a lidar sensor provided in the vehicle together with the image data obtained from the camera and the inclination angle of the road surface is measured. 제4항에 있어서,
상기 노면경사 측정부는,
상기 라이다 센서에 의해 측정되는 전방 노면과의 거리정보에 대응하여 노면 경사각을 측정하는 것을 특징으로 하는 자율주행 차량의 위치신호 보정장치.5. The method of claim 4,
The road slope measuring unit,
The apparatus for correcting a position signal of an autonomous vehicle, characterized in that the road surface inclination angle is measured in response to distance information from the front road surface measured by the lidar sensor.
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7163829B2 (en) * 2019-03-05 2022-11-01 トヨタ自動車株式会社 Vehicle Mounted Lidar Axis Deviation Detector

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH06317652A (en) * 1993-04-30 1994-11-15 Suzuki Motor Corp Gps vehicle position detecting system
JP2006275969A (en) * 2005-03-30 2006-10-12 Clarion Co Ltd Apparatus for calculating inclination angle, and navigation apparatus
JP2012007922A (en) * 2010-06-23 2012-01-12 Nec Corp Road structure measuring method and road surface measuring device
KR20140065627A (en) 2012-11-19 2014-05-30 한국전자통신연구원 Method and apparatus for providing camera calibration for vehicles
KR20180055292A (en) 2016-11-16 2018-05-25 국민대학교산학협력단 Integration method for coordinates of multi lidar
KR20190064798A (en) * 2017-12-01 2019-06-11 현대자동차주식회사 Road surface detection system using Lidar and road surface detection method using the same
KR101977749B1 (en) * 2017-11-21 2019-08-28 현대오트론 주식회사 Apparatus and method for estimating position of vehicle using road slope

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101416385B1 (en) * 2012-12-06 2014-07-08 현대자동차 주식회사 Method for correcting the gps position error of vehicle

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH06317652A (en) * 1993-04-30 1994-11-15 Suzuki Motor Corp Gps vehicle position detecting system
JP2006275969A (en) * 2005-03-30 2006-10-12 Clarion Co Ltd Apparatus for calculating inclination angle, and navigation apparatus
JP2012007922A (en) * 2010-06-23 2012-01-12 Nec Corp Road structure measuring method and road surface measuring device
KR20140065627A (en) 2012-11-19 2014-05-30 한국전자통신연구원 Method and apparatus for providing camera calibration for vehicles
KR20180055292A (en) 2016-11-16 2018-05-25 국민대학교산학협력단 Integration method for coordinates of multi lidar
KR101977749B1 (en) * 2017-11-21 2019-08-28 현대오트론 주식회사 Apparatus and method for estimating position of vehicle using road slope
KR20190064798A (en) * 2017-12-01 2019-06-11 현대자동차주식회사 Road surface detection system using Lidar and road surface detection method using the same

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20230117819A (en) 2022-02-03 2023-08-10 한화에어로스페이스 주식회사 Driving apparatus and driving controlling method

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