EP2812652A1 - Détermination de la structure d'une surface de chaussée au moyen d'une caméra 3d - Google Patents

Détermination de la structure d'une surface de chaussée au moyen d'une caméra 3d

Info

Publication number
EP2812652A1
EP2812652A1 EP13709741.6A EP13709741A EP2812652A1 EP 2812652 A1 EP2812652 A1 EP 2812652A1 EP 13709741 A EP13709741 A EP 13709741A EP 2812652 A1 EP2812652 A1 EP 2812652A1
Authority
EP
European Patent Office
Prior art keywords
road surface
camera
height
image data
vehicle
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP13709741.6A
Other languages
German (de)
English (en)
Inventor
Stefan Hegemann
Stefan Heinrich
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Conti Temic Microelectronic GmbH
Original Assignee
Conti Temic Microelectronic GmbH
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Conti Temic Microelectronic GmbH filed Critical Conti Temic Microelectronic GmbH
Publication of EP2812652A1 publication Critical patent/EP2812652A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • 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
    • B60W40/064—Degree of grip
    • 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
    • B60W40/068—Road friction coefficient
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00—Measuring arrangements characterised by the use of optical techniques
    • G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
    • G01B11/306—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces for measuring evenness
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C7/00—Tracing profiles
    • G01C7/02—Tracing profiles of land surfaces
    • G01C7/04—Tracing profiles of land surfaces involving a vehicle which moves along the profile to be traced
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/42—Simultaneous measurement of distance and other co-ordinates
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/46—Indirect determination of position data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/40—Analysis of texture
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/18—Conjoint control of vehicle sub-units of different type or different function including control of braking systems
    • B60W10/184—Conjoint control of vehicle sub-units of different type or different function including control of braking systems with wheel brakes
    • 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
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
    • 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
    • B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
    • B60W2420/403—Image sensing, e.g. optical camera
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G01S17/894—3D imaging with simultaneous measurement of time-of-flight at a 2D array of receiver pixels, e.g. time-of-flight cameras or flash lidar
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00—Indexing scheme for image data processing or generation, in general
    • G06T2200/04—Indexing scheme for image data processing or generation, in general involving 3D image data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G06T2207/10012—Stereo images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G06T2207/30261—Obstacle

Definitions

  • the invention relates to a method and a device for detecting the condition of a road surface with ⁇ means of a (spatially resolving) 3D camera.
  • DE 102009033219 Al discloses a method and an on ⁇ device for determining a vehicle vorausdorf- a road profile of a lane.
  • a Babyfas ⁇ sungsvorraum or from the vehicle's own motion data a street height profile of the lane ahead the vehicle is determined.
  • the image capture device may in this case be a camera which is fixedly arranged in the front region of the vehicle and comprises two image acquisition units.
  • an active suspension control or adjustment damping can be regulated.
  • Accident prevention is becoming increasingly important in driver assistance systems.
  • emergency braking systems slightest ⁇ th this an important contribution.
  • Their effect depends ever ⁇ but crucially on the coefficient of friction and friction coefficient of the surface with respect to the tires of the vehicle from. In particular, wetness considerably reduces the coefficient of friction compared with that on a dry road.
  • WO 2011/007015 A1 shows a laser-based method for friction coefficient classification in motor vehicles. Signals from a lidar or CV sensor that are placed on the road surface. are judged are evaluated for this purpose and then a friction coefficient is assigned in particular on the basis of the amplitude of the measured road surface. It can be estimated at ⁇ play as whether snow, asphalt or ice form the road surface.
  • the object of the present invention to overcome these drawbacks and to provide a more favorable, more reliable and vo ⁇ out looking recognition of the nature of a roadway surface.
  • the object is achieved by Minim ⁇ least a picture of the surroundings of the vehicle is recorded with a 3D camera. From the image data of the 3D camera, height profiles of the road surface transversely to the direction of travel of the vehicle are determined along a plurality of lines. This Li ⁇ nien also referred to as scan lines. Along each line of thus height profile is "scanned".
  • the condition of the vehicle is detected ground surface from which he ⁇ mediated level courses. As a condition here in particular, the material which the road surface bil ⁇ det (tar, sand, ice, snow), the shape of the surface (flat, rough, bumpy) (as well as local changes in the material or the flatness of the road surface oil track, puddle, pothole, ruts, etc. .) Understood.
  • the condition of the road surface is detected from a comparison of the ascertained height courses with stored height courses of known nature.
  • a Beillesheitsklassifikator can be vortrai ⁇ ned which thereby learns which detected height profiles correspond to which textures of road surfaces.
  • a quantitative evaluation of the level curves determined can be performed, for example, egg ⁇ ne frequency analysis (or width and / or expansion in the direction of travel of individual recesses or projections of the road surface), amplitude determination, gradient or the like. From this quantitative analysis, typical textures can be identified on the basis of characteristic quantities, eg strong noise of the height gradients in a gravel path.
  • water or a layer of ice on the road leads to a smooth road surface. Ice often occurs along with snow along with the roadway.
  • At least one monocular camera of the 3D camera can be evaluated and into the recognition of the condition of the road surface.
  • the evaluation of the 2D image data in this case need not be limited to the area of the road surface, but may in particular include areas next to the roadway.
  • the 2D image data can be evaluated by means of a texture or pattern analysis.
  • the texture and / or pattern analysis may in particular be a classification based on trained textures and / or patterns, e.g. using a neural network. For example, due to the characteristic textures or patterns, a head-stone patch can be well recognized in the 2D image.
  • the 2D image data are evaluated by means of an edge and / or color analysis.
  • edge detection algorithms known per se for edge detection can be used.
  • the position of the edges in particular enables or supports the recognition of textures of the road surface whose edge profile is known.
  • a gray scale or color analysis for example, snow can be detected from white areas on or next to the roadway.
  • ⁇ Licher texture difference may be estimated by a respective local coefficient of friction.
  • the at least one estimated coefficient of friction is used for a precontrol of steering and / or braking interventions (ABS, ESP, ACC, emergency brake assistant, lane keeping, backup and / or emergency steering assistant).
  • ABS steering and / or braking interventions
  • ESP ESP
  • ACC emergency brake assistant
  • lane keeping lane keeping
  • backup and / or emergency steering assistant a precontrol of steering and / or braking interventions
  • the 3D camera is preferably a stereo camera or a photonic mixer camera or PMD sensor (English: Photonic Mixing Device).
  • the invention further comprises a device for detecting the condition of a road surface.
  • a 3D camera, evaluation and detection means are pre ⁇ see.
  • the 3D camera allows the recording of at least ei ⁇ Nes image of the lying in front of the vehicle environment including the road ahead.
  • the evaluation means serve to determine height profiles of the road surface along a plurality of lines transversely to the direction of travel of the vehicle from the image data of the 3D camera.
  • the Erken ⁇ voltage medium used for detecting the condition of the road surface from the determined height gradients.
  • Fig. 1 lines transverse to the direction of travel, along which the height profile of the road surface is determined;
  • FIG. 2 shows an exemplary height profile of the road surface transversely to the direction of travel in the presence of a striking hole
  • Fig. 7 is a 2D camera recording in wet conditions
  • Fig. 8 is a 2D camera recording on dry roads.
  • Fig. 1 the scanning of the height profile (h) along lines (5) transversely (y) to the direction of travel (1) of the vehicle is shown schematically.
  • the road surface is monitored from right to left, left to right or in both transverse directions (y) along the scan lines (5) having any given density.
  • a raised lane boundary such as a curb limits the road surface left (3) and right (4).
  • the substantially flat road surface is lowered locally in the left front of the region ⁇ a pothole (2) or a similar interruption.
  • This lowering is clearly visible in the course of the height (h) of the road surface transversely (y) to the direction of travel (1) as shown in FIG.
  • This height profile (h) has, in addition to two jumps due to the raised roadway boundaries (3, 4) a dotted lowering in the left area, which can be assigned to the pothole (2) of FIG.
  • a roadway is shown, which is formed by a KopfSteinpflaster (6).
  • chassis components could be controlled accordingly and / or measures to improve the driving noise (counter-noise or tire pressure changes) could be taken.
  • FIG. 4 An exemplary height profile (h) of the head plaster (6) in the transverse direction (y) is shown in FIG. 4. More height profiles along other scan lines (5) in Fig. Wür ⁇ look similar to Figure 3.
  • the typical width and height of the variations in altitude (h) allows the assignment of such characteristic height gradients to a head-stone pavement as the nature of the road surface.
  • the recognition can be additionally supported by a texture or pattern analysis of the 2D camera image (see Fig. 3). This analysis also allows the road surface to be recognized as a head stone patch, thus confirming the recognition from the height profiles from the 3D camera data.
  • Fig. 5 is a roadway with two ruts (7, 8) parallel to the direction of travel (1) in the right part of the road surface to see.
  • two Absen ⁇ kungen (dotted) can be seen in the right part of the road surface.
  • Fig. 7 a wet road surface is in a 2D camera image (gray scale image of a monocular camera) to se ⁇ hen.
  • mirroring effects on the wet road surface can be recognized from the 2D image since trees (or in general the environment) appear mirrored on the road surface.
  • mirroring effects lead to a greater perceived distance in the disparity image of the stereo camera.
  • This supposed distance ent ⁇ speaks the actual distance to the trees next to the roadway ermit- from the disparity of the environment can be telt.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Theoretical Computer Science (AREA)
  • Transportation (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Mechanical Engineering (AREA)
  • Mathematical Physics (AREA)
  • Automation & Control Theory (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Multimedia (AREA)
  • Traffic Control Systems (AREA)
  • Length Measuring Devices By Optical Means (AREA)
  • Image Analysis (AREA)
  • Image Processing (AREA)

Abstract

La présente invention concerne un procédé et un dispositif pour reconnaître la structure d'une surface de chaussée au moyen d'une caméra 3D. La caméra 3D est employée pour prendre au moins une image de l'environnement qui se trouve à l'avant du véhicule. A partir des données d'image de la caméra 3D, des variations de hauteur (h) de la surface de la chaussée transversalement (y) à la direction de circulation (1) du véhicule, sont déterminées le long d'une pluralité de lignes (5). A partir des variations de hauteur (h), la structure (2; 6; 7; 8) de la surface de chaussée est reconnue.
EP13709741.6A 2012-02-10 2013-01-28 Détermination de la structure d'une surface de chaussée au moyen d'une caméra 3d Withdrawn EP2812652A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102012101085A DE102012101085A1 (de) 2012-02-10 2012-02-10 Bestimmung einer Beschaffenheit einer Fahrbahnoberfläche mittels einer 3D-Kamera
PCT/DE2013/100028 WO2013117186A1 (fr) 2012-02-10 2013-01-28 Détermination de la structure d'une surface de chaussée au moyen d'une caméra 3d

Publications (1)

Publication Number Publication Date
EP2812652A1 true EP2812652A1 (fr) 2014-12-17

Family

ID=47891329

Family Applications (1)

Application Number Title Priority Date Filing Date
EP13709741.6A Withdrawn EP2812652A1 (fr) 2012-02-10 2013-01-28 Détermination de la structure d'une surface de chaussée au moyen d'une caméra 3d

Country Status (5)

Country Link
US (1) US9679204B2 (fr)
EP (1) EP2812652A1 (fr)
JP (1) JP6117245B2 (fr)
DE (2) DE102012101085A1 (fr)
WO (1) WO2013117186A1 (fr)

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DE112013000914A5 (de) 2014-10-23
US9679204B2 (en) 2017-06-13
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