WO2014090247A1 - Détection basée sur la vidéo d'obstacles sur une voie de roulement - Google Patents

Détection basée sur la vidéo d'obstacles sur une voie de roulement Download PDF

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Publication number
WO2014090247A1
WO2014090247A1 PCT/DE2013/200338 DE2013200338W WO2014090247A1 WO 2014090247 A1 WO2014090247 A1 WO 2014090247A1 DE 2013200338 W DE2013200338 W DE 2013200338W WO 2014090247 A1 WO2014090247 A1 WO 2014090247A1
Authority
WO
WIPO (PCT)
Prior art keywords
vehicle
obstacles
image data
roadway
detected
Prior art date
Application number
PCT/DE2013/200338
Other languages
German (de)
English (en)
Inventor
Stefan Hegemann
Stefan LÜKE
Stefan Heinrich
Original Assignee
Conti Temic Microelectronic Gmbh
Continental Teves Ag & Co. Ohg
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, Continental Teves Ag & Co. Ohg filed Critical Conti Temic Microelectronic Gmbh
Priority to DE112013003326.7T priority Critical patent/DE112013003326A5/de
Publication of WO2014090247A1 publication Critical patent/WO2014090247A1/fr

Links

Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/165—Anti-collision systems for passive traffic, e.g. including static obstacles, trees
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • G06V20/647—Three-dimensional objects by matching two-dimensional images to three-dimensional objects

Definitions

  • the invention relates to a method and a device for video-based detection of obstacles on a roadway, which are particularly suitable for use in driver assistance systems.
  • DE 10 2009 033 219 A1 describes a method for determining a road profile of a traffic lane in front of a vehicle on the basis of acquired image data.
  • a road height profile of the lane is determined by an estimation device, for example a Kalman filter.
  • the image data are generated by a camera fixedly arranged, for example, in the front region of the vehicle.
  • the object of the present invention is now to propose a method and a device for video-based detection of obstacles on a roadway, which are further improved compared to that from DE 10 2009 033 219 A1.
  • An underlying idea of the invention is to detect obstacles on a roadway by evaluating image data of a 3D camera, that is to implement a video-based recognition, in which is used by means of a 3D camera, an active evaluation zone for the detection of obstacles on a roadway, which is not limited to the immediate area of the vehicle or a vehicle tire, but comprises the entire road surface (width) in the Vorschau Schl of the vehicle.
  • the image data also contain spatial information of the preview area of the vehicle.
  • An embodiment of the invention now relates to a method for video-based detection of obstacles on a roadway comprising the steps of: receiving image data generated by a 3D camera provided for detecting a region of an environment in front of a vehicle, the 3D camera thus is aligned and formed such that the area covered by it comprises at least the entire width of the roadway in front of the vehicle, evaluating the image data for detecting obstacles transverse to the direction of travel of the vehicle, and outputting data to detected obstacles.
  • the evaluation of the image data for detecting obstacles transverse to the direction of travel of the vehicle may include the detection of several pixels in space, which are arranged approximately on a horizontal line, and determining an approximate height of the obstacle depending on the detected pixels.
  • the evaluation of the image data for detecting obstacles transverse to the direction of travel of the vehicle may include the detection of several pixels in space, which are arranged approximately on a vertical line, and the calculation of a roadway curvature depending on the detected pixels.
  • Outputting data on detected obstacles may include determining whether the vehicle can run over a detected obstacle and / or whether a detected obstacle may cause damage to the vehicle when crossing it, and outputting the result of the determining.
  • Outputting data on detected obstacles depending on the result of the determination may include issuing a warning, an intervention in the vehicle control and / or a change of vehicle characteristics.
  • a further embodiment of the invention relates to a device for video-based detection of obstacles on a roadway having first means for receiving image data generated by a 3D camera provided for detecting a region of an environment in front of a vehicle, the 3D camera being aligned in this way and configured such that the area covered by it comprises at least the entire width of the road ahead of the vehicle, second means for evaluating the image data for detecting obstacles transverse to the direction of travel of the vehicle, and third means for outputting data on detected obstacles.
  • the second means may be adapted to carry out a method according to the invention and as described herein
  • the third means may be adapted to carry out a method according to the invention and as described herein.
  • another embodiment of the invention relates to a driver assistance system having a device according to the invention and as described herein. Further advantages and possible applications of the present invention will become apparent from the following description in conjunction with the / in the drawing (s) illustrated embodiment (s).
  • FIG. 1 shows a flow chart of an embodiment of a method for video-based detection of obstacles on a roadway according to the invention
  • FIG. 2 shows an example of an image of a detected area of an environment in front of a vehicle with an area of a raised road surface at a construction site as an obstacle
  • FIG. 1 shows a flow chart of an embodiment of a method for video-based detection of obstacles on a roadway according to the invention
  • FIG. 2 shows an example of an image of a detected area of an environment in front of a vehicle with an area of a raised road surface at a construction site as an obstacle
  • FIG. 1 shows a flow chart of an embodiment of a method for video-based detection of obstacles on a roadway according to the invention
  • FIG. 2 shows an example of an image of a detected area of an environment in front of a vehicle with an area of a raised road surface at a construction site as an obstacle
  • FIG. 1 shows a flow chart of an embodiment of a method for video-based detection of obstacles on a roadway according to the invention
  • 3 is an example of an image of a detected area of an environment in front of a vehicle having an area of a raised road surface for traffic calming as an obstacle;
  • Fig. 5 shows an embodiment of a device for video-based detection of obstacles on a roadway according to the invention.
  • identical, functionally identical and functionally connected elements may be provided with the same reference numerals. Absolute values are given below by way of example only and are not to be construed as limiting the invention.
  • the present invention starting from an in-vehicle stereo or. 3D camera system observing the road surface in the surrounding area in front of the vehicle.
  • the image data of the detected environmental region generated by the 3D camera system are processed by an algorithm whose flow chart is shown in FIG. 1 and which will be explained below.
  • the algorithm receives in a first step S10 the image data from the 3D camera system for further processing.
  • a subsequent step S12 the received image data for detecting obstacles transverse to the direction of travel are evaluated.
  • the evaluation may include various steps to detect various obstacles, as explained below.
  • a plurality of pixels arranged on a horizontal line are detected in a step S120, as shown in the exemplary images of detected environmental regions in front of a vehicle shown in FIGS. 2 and 3.
  • Fig. 2 the course of a roadway 14 is shown in front of a vehicle, as it is detected by a 3-D camera system.
  • an area 10 (framed by the dashed rectangle) in which a portion 100 of the road surface is lifted, as is often the case, for example, in the renewal of the asphalt pavement of a roadway. Due to the raised road surface portion 100, a leading edge 102 and a trailing edge 104 are formed, respectively between the surface of the roadway 14 and the section 100. A crossing of these two edges 102 and 104, which are transverse to the direction of travel of the vehicle, could lead to damage to the vehicle. Therefore, a speed limit usually applies in the area of such sections.
  • the algorithm can now recognize the two edges 102 and 104 and in a subsequent step S122 determine the approximate height of these edges based on the spatial or 3D information contained in the image data generated by the 3D Kemerasystem, in particular calculate or estimate ,
  • a section 120 is raised, which is done, for example, for traffic calming on certain roads.
  • so-called speed bumper may be mounted on the road surface, which are slightly shorter than the section 120.
  • a front driveway 122 is provided at the front of the section 120 and a rear driveway 124 at the rear of the section 120, which defines an oblique transition between the section 120 and the surface of the roadway 14.
  • the driveway 122 and the exit 124 can also be recognized by the algorithm in step S120 as their representation in images acquired by the 3D camera system as a plurality of pixels arranged on a horizontal line.
  • the approximate height of the section 120 may be determined, in particular calculated or estimated, in step S122 from the space information to the driveway 122 and exit 124 pixels.
  • the algorithm in the context of the evaluation the curvature of the surface to be traveled, ie the roadway can be determined.
  • a step S124 pixels are recognized on a vertical line, for example the central strip of a road.
  • a step S126 the curvature of the road is calculated with the spatial positions of the pixels recognized on the vertical line.
  • the algorithm proceeds to a step S14 after the image data is evaluated in step S12, as explained above, in which data on detected obstacles are output. Also, the step S14 has a plurality of sub-steps, as will be explained in detail below.
  • step S140 the algorithm determines whether the vehicle can overrun an obstacle detected in step S12, or whether a detected obstacle when overrunning can cause damage to the vehicle.
  • the algorithm may perform various functions based on obstacle detection:
  • step S1420 Outputting a warning in step S1420 or intervention in the vehicle control (for example, active brake or
  • step S1422 in the case of impassable road curvatures (for example, low-lying garages, edges too high in front of garages, speed bumpers too high, etc.);
  • step S1424 Changing the vehicle characteristics in step S1424, so that driveability is given again and / or comfort when
  • FIG. 5 shows a block diagram of a video-based obstacle detection device 20 according to the invention, which processes data from a stereo-vision camera with left and right imagers 28 and 30, respectively.
  • the two imagers 28 and 30 provide image data of the surroundings in front of a vehicle.
  • This image data is supplied to an image data reception unit 22, which may be configured to calculate the position of pixels in the space.
  • the image data and possibly the calculated pixel positions in the space are transmitted to an image data evaluation unit 24, which evaluates the image data obtained in order to detect obstacles transverse to the direction of travel of the vehicle according to method step S12 explained above.
  • An obstacle output unit 26 then outputs data on detected obstacles, for example in the form of a warning (acoustically, visually and / or haptically), by an intervention in the vehicle control and / or by a change in the vehicle characteristics, for example by outputting a corresponding control signal for control devices of the vehicle , which are responsible for the vehicle control (eg active brakes), according to the method step S14 explained above.
  • the essence of the invention is the detection of areas in the vehicle environment that can not or should not be driven due to the vehicle characteristics or whose trafficability is limited or can cause damage to the vehicle when driving.
  • the areas in the vehicle are characterized by obstacles, which are transverse to the direction of travel and therefore can not be determined by conventional algorithms for environment assessment or difficult, especially since they usually do not cause jumps in a height gradient transverse to the direction of travel. Further aspects of the invention are listed below again:

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Traffic Control Systems (AREA)
  • Image Analysis (AREA)

Abstract

L'invention concerne un procédé pour la détection basée sur la vidéo d'obstacles sur une voie de roulement présentant les étapes suivantes : réception de données d'image (S10), qui sont générées par une caméra 3D destinée à enregistrer une zone d'un environnement devant un véhicule, la caméra 3D étant conçue et réalisée de manière telle que la zone qu'elle enregistre comprend au moins la largeur totale de la voie de roulement devant le véhicule, évaluation des données d'image (S12) pour détecter des obstacles transversaux par rapport au sens de roulement et sortie de données (S14) relatives aux obstacles détectés.
PCT/DE2013/200338 2012-12-12 2013-12-09 Détection basée sur la vidéo d'obstacles sur une voie de roulement WO2014090247A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
DE112013003326.7T DE112013003326A5 (de) 2012-12-12 2013-12-09 Videobasierte Erkennung von Hindernissen auf einer Fahrbahn

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102012112164.8 2012-12-12
DE102012112164.8A DE102012112164A1 (de) 2012-12-12 2012-12-12 Videobasierte erkennung von hindernissen auf einer fahrbahn

Publications (1)

Publication Number Publication Date
WO2014090247A1 true WO2014090247A1 (fr) 2014-06-19

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PCT/DE2013/200338 WO2014090247A1 (fr) 2012-12-12 2013-12-09 Détection basée sur la vidéo d'obstacles sur une voie de roulement

Country Status (2)

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DE (2) DE102012112164A1 (fr)
WO (1) WO2014090247A1 (fr)

Cited By (2)

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CN110770744A (zh) * 2017-06-29 2020-02-07 大众汽车有限公司 用于确定车辆的周围环境中的表面的性质的设备和方法
US11657532B2 (en) 2019-12-11 2023-05-23 Nvidia Corporation Surface profile estimation and bump detection for autonomous machine applications

Families Citing this family (3)

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Publication number Priority date Publication date Assignee Title
DE102015007592A1 (de) * 2015-06-16 2016-12-22 Audi Ag Trajektoriebasierte Fahrwerksregelung
US11772647B2 (en) 2016-06-24 2023-10-03 Jaguar Land Rover Limited Control system for a vehicle
GB2563198B (en) * 2017-03-15 2021-05-26 Jaguar Land Rover Ltd A system for identifying water ahead of a vehicle

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US5530420A (en) * 1993-12-27 1996-06-25 Fuji Jukogyo Kabushiki Kaisha Running guide apparatus for vehicle capable of keeping safety at passing through narrow path and the method thereof
DE102009033219A1 (de) 2009-01-23 2010-07-29 Daimler Ag Verfahren zur Ermittlung eines Fahrzeug vorausliegenden Straßenprofils einer Fahrspur
US20120294481A1 (en) * 2011-05-19 2012-11-22 Fuji Jukogyo Kabushiki Kaisha Environment recognition device and environment recognition method
US20120294485A1 (en) * 2011-05-19 2012-11-22 Fuji Jukogyo Kabushiki Kaisha Environment recognition device and environment recognition method

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DE102012004198A1 (de) * 2012-03-01 2012-10-04 Daimler Ag Verfahren und Vorrichtung zur Unterstützung eines Fahrers beim Führen eines Fahrzeugs im Gelände

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US5530420A (en) * 1993-12-27 1996-06-25 Fuji Jukogyo Kabushiki Kaisha Running guide apparatus for vehicle capable of keeping safety at passing through narrow path and the method thereof
DE102009033219A1 (de) 2009-01-23 2010-07-29 Daimler Ag Verfahren zur Ermittlung eines Fahrzeug vorausliegenden Straßenprofils einer Fahrspur
US20120294481A1 (en) * 2011-05-19 2012-11-22 Fuji Jukogyo Kabushiki Kaisha Environment recognition device and environment recognition method
US20120294485A1 (en) * 2011-05-19 2012-11-22 Fuji Jukogyo Kabushiki Kaisha Environment recognition device and environment recognition method

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Title
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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110770744A (zh) * 2017-06-29 2020-02-07 大众汽车有限公司 用于确定车辆的周围环境中的表面的性质的设备和方法
CN110770744B (zh) * 2017-06-29 2024-02-02 大众汽车有限公司 用于确定车辆的周围环境中的表面的性质的设备和方法
US11657532B2 (en) 2019-12-11 2023-05-23 Nvidia Corporation Surface profile estimation and bump detection for autonomous machine applications
US11900629B2 (en) 2019-12-11 2024-02-13 Nvidia Corporation Surface profile estimation and bump detection for autonomous machine

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DE112013003326A5 (de) 2015-03-19
DE102012112164A1 (de) 2014-06-12

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