DE102010020688A1 - Driving track course determining method for motor vehicle, involves identifying structures limiting driving tracks based on length, contrast, direction and three dimensional position of continuous edge courses of contours of structures - Google Patents

Driving track course determining method for motor vehicle, involves identifying structures limiting driving tracks based on length, contrast, direction and three dimensional position of continuous edge courses of contours of structures Download PDF

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Publication number
DE102010020688A1
DE102010020688A1 DE201010020688 DE102010020688A DE102010020688A1 DE 102010020688 A1 DE102010020688 A1 DE 102010020688A1 DE 201010020688 DE201010020688 DE 201010020688 DE 102010020688 A DE102010020688 A DE 102010020688A DE 102010020688 A1 DE102010020688 A1 DE 102010020688A1
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Prior art keywords
structures
lane
contours
vehicle
dimensional
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DE201010020688
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German (de)
Inventor
Uwe Dr.-Ing. Franke
Carsten Dr. Knöppel
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Daimler AG
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Daimler AG
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Priority to DE201010020688 priority Critical patent/DE102010020688A1/en
Publication of DE102010020688A1 publication Critical patent/DE102010020688A1/en
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/00791Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
    • G06K9/00798Recognition of lanes or road borders, e.g. of lane markings, or recognition of driver's driving pattern in relation to lanes perceived from the vehicle; Analysis of car trajectory relative to detected road
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/02Estimation 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
    • B60W40/06Road conditions
    • B60W40/072Curvature of the road
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/02Estimation 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
    • B60W40/06Road conditions
    • B60W40/076Slope angle of the road
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W2420/00Indexing codes relating to the type of sensors based on the principle of their operation
    • B60W2420/42Image sensing, e.g. optical camera

Abstract

The method involves recording structures (S1-S5) limiting a lane (FB) and/or driving tracks (FS1-FS3) by an image recording unit, and detecting contours of the structures for detecting the structures in images recorded by the image recording unit. Length, contrast, direction and three dimensional position of continuous edge courses (K) of the contours are determined, and the structures are identified based on the length, contrast, direction and the three dimensional position. The contours are evaluated depending on a model supported filter.

Description

  • The invention relates to a method for determining a lane course for a vehicle, in which by means of at least one image capture unit, a roadway and / or a lane delimiting structures are detected.
  • In the DE 10 2004 052 127 A1 A method for tracking a road-bound vehicle is described using a camera arranged at a defined position on the vehicle and an image processing unit for processing the images taken with the camera. For realizing the tracking permanent markers and temporary markers in the construction site and / or danger area, which limit the lanes of the road, detected and evaluated and in an evaluation of the relative position of the vehicle with respect to the detected permanent markers a control signal for the lateral guidance Derived from the vehicle. A control signal for the lateral guidance of the vehicle is derived from the relative position of the vehicle with respect to a marking pattern of permanent and temporary markings.
  • From the DE 103 11 240 A1 For example, a method and an apparatus for tracking a vehicle are known, wherein a distinction is made between temporary and permanent markings on the road. The distinction between the temporary and permanent markings is based on different colors, line types and other detected by a panoramic device in the vicinity of the vehicle boundaries, such as beacons, cones or the like. The all-round viewing device includes video cameras, radars and is coupled to a navigation device.
  • Furthermore, from the DE 10 2004 057 296 A1 a driving assistance device for warning a driver of a motor vehicle from an imminent departure from the lane or leaving the lane known. The driver assistance device comprises at least one imaging sensor and an evaluation device connected thereto for detecting lane edge markings and / or lane markings and / or lane edges in the region detected by the imaging sensor. A warning device is coupled to the evaluation device, in which at least one distance sensor is additionally connected to the evaluation device, with which the distance to objects raised in relation to the road surface in the region of the roadway edge, in particular a structural boundary of the roadway edge, can be determined. Information as to whether it is a raised object is obtained from a distance profile determined by means of the distance sensor and / or from an altitude estimation carried out by means of a height-estimating sensor in the region of the roadway edge.
  • The invention has for its object to provide a method for determining a lane course for a vehicle.
  • The object is achieved by a method having the features specified in claim 1.
  • Advantageous embodiments of the invention are the subject of the dependent claims.
  • In the method for determining a lane course for a vehicle, structures defining a lane and / or lane are detected by means of at least one image capture unit. These structures are, in particular, lane and lane markings as well as road edges.
  • According to the invention, contours of the structures are detected for detecting the structures in images acquired by means of the image acquisition unit, wherein a length, a contrast, a direction and a three-dimensional position of continuous edge profiles of the contours are determined.
  • Due to the determination of the continuous edge profiles of the contours and their three-dimensional positions, an unambiguous lane course determination is possible even in the case of ambiguous structures delimiting the roadway and / or the lane. It is also possible due to the determination of the contours and their three-dimensional positions and gradients to determine the lane course in the absence of lane and / or lane markings, as well as the road surface raised objects, such as curbs, crash barriers, concrete walls, or reduced from the road surface Objects, such as trenches, drainage channels or green spaces, are detectable and identifiable. Thus, a robust, unambiguous and reliable lane estimation is feasible in both clear and confusing areas and situations on highways, highways, in construction sites and in particular in transitions to construction sites sections.
  • The determined lane course is used in particular for operation of a driver assistance device, by means of which a driver of the vehicle is assisted in a transverse guidance thereof or by means of which an automatic lateral guidance of the vehicle takes place.
  • Embodiments of the invention are explained in more detail below with reference to drawings.
  • Showing:
  • 1 1 schematically shows a device for determining a lane course for a vehicle,
  • 2 FIG. 2 schematically shows a first environmental situation on a roadway in front of the vehicle with different structures delimiting the roadway and several lanes, FIG.
  • 3 2 schematically shows a second environmental situation on a roadway in front of the vehicle with various structures delimiting the roadway and several lanes;
  • 4 schematically a third environmental situation on a roadway in front of the vehicle with different the road surface and several lanes limiting structures, and
  • 5 schematically a fourth environmental situation on a roadway in front of the vehicle with different the road surface and several lanes limiting structures.
  • Corresponding parts are provided in all figures with the same reference numerals.
  • 1 shows a device 1 for determining a lane course for a vehicle, not shown, which is suitable for carrying out the method according to the invention.
  • The device 1 includes an image capture unit 1.1 and an evaluation unit 1.2 , The image capture unit 1.1 is located on or in the vehicle and detects an environment located in front of the vehicle. The image capture unit 1.1 is formed in the illustrated embodiment as a so-called stereo camera and includes two cameras 1.1.1 . 1.1.2 on the basis of which images B1, B2 of the surroundings of the vehicle are detected.
  • The pictures B1, B2 are used to evaluate the evaluation unit 1.2 supplied on the basis of which they are processed stereoscopically such that a so-called disparity image or an image is formed with depth information, which three-dimensional information by means of the cameras 1.1.1 . 1.1.2 represents the detected environment of the vehicle.
  • Alternatively, the image capture unit 1.1 formed in a manner not shown as a so-called 3D camera, based on which the environment of the vehicle is also detected three-dimensionally.
  • In a further embodiment, not shown, the image acquisition unit 1.1 formed as a 2D camera, based on which the environment of the vehicle is detected two-dimensionally. In addition, at least one further detection unit for three-dimensional detection of the environment is then provided. The further detection unit comprises a stereo camera, a laser sensor and / or a radar sensor, wherein based on the further detection unit three-dimensional positions of in 2 illustrated objects O1 to O3, such as vehicles, and / or in the 2 to 5 Structures S1 to S20 shown in detail can be detected.
  • Structures S1 to S20 are roadway boundaries that include road markings, lane markings, roadway edges, structural boundaries, and / or elevated and / or lowered objects from a roadway surface. Underlaid objects are curbs, crash barriers, concrete barriers, bollards, beacons, structures, trees, shrubs, tunnel walls and similar objects. Descent objects are drainage channels, ditches and other drainage structures in the 2 to 4 roadway FB shown in detail. Also can be detected and identifiable as lane boundaries grass areas, so-called green strips and summer roads.
  • For evaluation of an environmental situation shown on the images B1, B2 includes the evaluation 1.2 an extraction unit 1.2.1 on the basis of which out of the acquired images B1, B2 contours of the structures S1 to S20 are extracted or detected. During the extraction of the contours, continuous edge courses K are recorded within the images B1, B2. The continuous edge courses K have a minimum length, a predetermined value of a contrast and a defined slope, ie a defined direction within the images B1, B2.
  • The length, the contrast and the direction of the continuous edge courses K are determined by means of an assignment unit 1.2.2 determined. Furthermore, three-dimensional positions POS of the respective edge course K are determined. The three-dimensional positions POS are thereby obtained from the disparity image or the image with the depth information as so-called world coordinates of a world coordinate system and the assignment unit 1.2.2 fed. By means of the allocation unit 1.2.2 newly detected contours in the form of the edge courses K are assigned to contours already tracked in time, ie to edge profiles K already tracked over time.
  • The determined three-dimensional positions POS are additionally the extraction unit 1.2.1 supplied, so that new contours in the form of continuous edge curves K are easy and effective extractable from the images B1, B2.
  • In an embodiment, not shown, in which the image capture unit 1.1 is formed as a 2D camera, the extraction of the contours of the structures S1 to S20 from captured images B1, B2 without supplying the three-dimensional positions in the extraction unit 1.2.1 ,
  • The evaluation unit 1.2 further comprises a track progress detection unit 1.2.3 , which performs the temporal tracking of the contours. In the case of this so-called "tracking", newly detected contours in the form of the edge courses K are also assigned to contours already tracked over time, ie to edge profiles K already tracked over time.
  • Timing and evaluation are based on model-based filtering. For this purpose, the track progression determination unit comprises 1.2.3 one or more filters designed as Kalman filters, particle filters, IMM filters (IMM = Interacting Multiple Model) and / or on the so-called Ransac algorithm-based filter, wherein the filter is used for a parameter estimation with a model-based temporal filtering , During the temporal tracking of the contours, the detected three-dimensional position POS of the associated edge course K is additionally guided as a state variable. Thus, in addition to the markings, structures or objects raised or lowered by the roadway FB can also be used to determine the course of the track.
  • As a result of the temporal tracking of the contours, the trace tracking unit is used 1.2.3 the lane course is determined, whereby all structures S1 to S20 located on the roadway FB in front of the vehicle are taken into account in the determination of the lane course.
  • Furthermore, the evaluation unit comprises 1.2 a track evaluation unit 1.2.4 , on the basis of which a generation of track parameters PAR on the basis of the determined track course takes place. The lane tracking parameters PAR describe a lane to be traveled by the vehicle on the lane FB, which lane is predetermined by the lane course ahead of the vehicle.
  • In the track evaluation performed, the contours tracked in time, i. H. the edge courses K, examined for a relevance to a current driving situation of the vehicle based on the position, the direction and the course of the contours. Based on the length, the contrast, the direction and the three-dimensional positions is determined how the respective structure S1 to S20 is formed so that it is identifiable. The identification of the respective structure S1 to S20 is effected in particular by comparing the structures S1 to S20 with model data stored in the evaluation unit.
  • Furthermore, a quality of the contours is determined and the detected contours and thus the detected structures S1 to S20 are evaluated with respect to the current driving situation of the vehicle. In other words, it is determined which relevance the detected structures S1 to S20 have with respect to a current driving situation of the vehicle and, depending on the relevance, it is determined how strongly and whether the detected structures S1 to S20 are taken into account in the determination of the lane course. Thus, as structures S1 to S20, differently colored markings, so-called tar joints, shadows, structures raised from the road surface and lowered and structures and objects running in one plane can be distinguished.
  • In an embodiment not shown, the device 1 coupled with a driver assistance system of the vehicle, by means of which a driver of the vehicle in a transverse guide and / or longitudinal guidance thereof is supported or by means of which an automatic transverse and / or longitudinal guidance of the vehicle takes place.
  • In the 2 to 5 various environmental situations are shown on a roadway FB ahead of the vehicle with various structures S1 to S20 delimiting the roadway FB and several lanes.
  • 2 shows a front of the vehicle roadway FB with three lanes FS1, FS2, FS3. A left lane FS1 is bounded on the left by a solid lane marking, which as a structure S2 from the image acquisition unit 1.1 is detected. This structure S2 points into that of the image acquisition unit 1.1 captured images B1, B2 two mutually parallel and the structure S2 on both sides bounding edge curves K on. On the basis of the three-dimensional position POS of the structure S2, its length, the contrast and the direction, the structure S2 of the track evaluation unit 1.2.4 identified as solid lane marking.
  • On the left side next to the structure S2, parallel to the traffic lane FS1, there is a concrete protection wall, which acts as the structure S1 of the image acquisition unit 1.1 is detected. The structure S1 becomes due to their contour, ie due to their edge courses K, the three-dimensional positions POS, which are raised from the road surface, their length, the contrast and the direction of the track evaluation unit 1.2.4 identified as a concrete protective wall.
  • Between the lanes FS1 and FS2 and the lanes FS2 and FS3 are each interrupted lane markings, which from the image acquisition unit 1.1 as the structures S3 and S4 are detected. Furthermore, the third lane FS3 is bounded on the right side by a further concrete protective wall, which is detected as structure S5. On the basis of the respective edge profiles K belonging to the structures S3 to S5 and their three-dimensional positions POS, these are obtained from the track evaluation unit 1.2.4 identified.
  • On the basis of all identified structures S1 to S5 on and next to the traffic lanes FS1 to FS3, the traffic lane course for the own vehicle is determined.
  • Also, by means of the image capture unit 1.1 Objects O1 to O3 recorded on the lanes FS2 and FS3 and by means of the evaluation unit 1.2 recognized as vehicles.
  • Together with the ascertained lane course of the vehicle, it is also possible to determine whether the objects O1 to O3 are obstacles for the own vehicle, wherein an automatic lateral guidance function is provided as a function of the determined lane course and the objects O1 to O3 present on the lanes FS1 to FS3 and / or longitudinal guidance on the roadway FB is possible.
  • 3 shows a lane FB with three lanes FS1 to FS3 according to 2 , For simplicity, the objects O1 to O3 are not shown. In contrast to 2 the first lane FS1 is bounded on the left side by a safety barrier or so-called guardrail. This guardrail, like all other structures S1 to S20, is characterized by specific edge courses K, so that the structure S1 is identified by the track evaluation unit because of its edge courses K and its three-dimensional positions POS 1.2.4 is identified as a safety barrier.
  • In 4 is shown in front of the vehicle lane FB with three traffic lanes FS1, FS2, FS3 and a traffic-locked lane FS4.
  • The roadway FB is bordered in each case by a concrete protection wall, wherein the concrete protection walls as the structures S6 and S12 of the image acquisition unit 1.1 be recorded. Due to the edge courses K of the structures S6 and S12 and their three-dimensional positions POS, these are identified as concrete protection walls.
  • The problem with the illustrated situation is that between the lanes FS1 and FS2 and the lanes FS2 and FS3 each two interrupted lane markings are directly adjacent to each other and thus have no clear regulatory content. Due to the edge courses K of the lane markings, which are detected as the structures S8 to S11 in the images B1, B2, the structures S8 to S11 are identified. On the basis of the course, its direction, the length and the three-dimensional position POS, it is possible by means of the track evaluation unit 1.2.4 determining that the lane extends between the structures S9 and S10.
  • 5 shows a front of the vehicle roadway FB with two lanes FS1, FS2 in the area of a transition to a construction site on a highway. In the exemplary embodiment illustrated, the roadway FB is delimited at the edge by in each case one guard rail, the guard rails being detected as the structures S19, S20.
  • Due to the transition region to the construction site, two solid lane markings or lane markings run alongside each other on the left side of the first lane FS1, which are detected as structure S13 and structure S14. Even between the first lane FS1 and the second lane FS2 run through lane markings or lane markings side by side, which are detected as structure S15 and structure S16. The lane markings run side by side between the lanes FS1 and FS2 in order to generate an enlarged safety area for objects O1 to O3 located on the lane FB in the transition area.
  • Based on the edge course K and the three-dimensional positions POS of the structures S13 to S16, these are from the tracking unit 1.2.4 identified as solid lanes or lane markings. In conjunction with the direction and the course of the edge courses K, ie the direction and the course of the lane markings, the track evaluation unit determines 1.2.4 in that the lane for the own vehicle runs between the structures S14 and S15.
  • LIST OF REFERENCE NUMBERS
  • 1
    contraption
    1.1
    Image capture unit
    1.1.1
    camera
    1.1.2
    camera
    1.2
    evaluation
    1.2.1
    extraction unit
    1.2.2
    allocation unit
    1.2.3
    Track history determination unit
    1.2.4
    Track assessment unit
    B1
    image
    B2
    image
    FB
    roadway
    FS1 to FS4
    lane
    K
    edge course
    O1 to O3
    object
    PAR
    Track the course parameters
    POS
    position
    S1 to S20
    structure
  • QUOTES INCLUDE IN THE DESCRIPTION
  • This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.
  • Cited patent literature
    • DE 102004052127 A1 [0002]
    • DE 10311240 A1 [0003]
    • DE 102004057296 A1 [0004]

Claims (6)

  1. Method for determining a lane course for a vehicle, in which by means of at least one image capture unit ( 1.1 ) a lane (FB) and / or a lane (FS1 to FS4) limiting structures (S1 to S20) are detected, characterized in that for detecting the structures (S1 to S20) in by means of the image capture unit ( 1.1 ) detected images (B1, B2) contours of the structures (S1 to S20) are detected, wherein a length, a contrast, a direction and a three-dimensional position (POS) continuous edge curves (K) of the contours are determined.
  2. A method according to claim 1, characterized in that on the basis of the length, the contrast, the direction and the three-dimensional positions (POS), the structures (S1 to S20) are identified.
  3. A method according to claim 1 or 2, characterized in that the contours are evaluated in terms of time based on a model-based filtering.
  4. Method according to one of the preceding claims, characterized in that based on a temporal tracking of the contours of the lane course is determined.
  5. Method according to one of the preceding claims, characterized in that a relevance of the contours with respect to a current driving situation of the vehicle on the basis of the three-dimensional position (POS), the direction and a course of the edge curves (K) is determined.
  6. Method according to one of the preceding claims, characterized in that a quality of the contours is determined based on a current driving situation of the vehicle.
DE201010020688 2010-05-15 2010-05-15 Driving track course determining method for motor vehicle, involves identifying structures limiting driving tracks based on length, contrast, direction and three dimensional position of continuous edge courses of contours of structures Withdrawn DE102010020688A1 (en)

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Application Number Priority Date Filing Date Title
DE201010020688 DE102010020688A1 (en) 2010-05-15 2010-05-15 Driving track course determining method for motor vehicle, involves identifying structures limiting driving tracks based on length, contrast, direction and three dimensional position of continuous edge courses of contours of structures

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DE201010020688 DE102010020688A1 (en) 2010-05-15 2010-05-15 Driving track course determining method for motor vehicle, involves identifying structures limiting driving tracks based on length, contrast, direction and three dimensional position of continuous edge courses of contours of structures

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Cited By (11)

* Cited by examiner, † Cited by third party
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EP2431917A1 (en) * 2010-09-21 2012-03-21 Mobileye Technologies Limited Barrier and guardrail detection using a single camera
WO2013091620A1 (en) * 2011-12-20 2013-06-27 Conti Temic Microelectronic Gmbh Determining a vertical profile of a vehicle environment by means of a 3d camera
DE102011122310A1 (en) 2011-12-23 2015-06-18 Daimler Ag Method and device for recognizing lane markings
DE102014209796A1 (en) 2014-05-22 2015-11-26 Hella Kgaa Hueck & Co. Method for controlling a cornering light
DE102016011789A1 (en) 2016-09-30 2017-03-02 Daimler Ag Method for determining a lane course
US9679204B2 (en) 2012-02-10 2017-06-13 Conti Temic Microelectronic Gmbh Determining the characteristics of a road surface by means of a 3D camera
DE102017001814A1 (en) 2017-02-27 2017-10-19 Daimler Ag Method for detecting lane markings
DE102016211730A1 (en) * 2016-06-29 2018-01-04 Continental Teves Ag & Co. Ohg Method for predicting a lane course of a roadway
DE102017007766A1 (en) 2017-08-16 2018-02-22 Daimler Ag Method for detecting a lane course
US9959595B2 (en) 2010-09-21 2018-05-01 Mobileye Vision Technologies Ltd. Dense structure from motion
US10289920B2 (en) 2013-11-15 2019-05-14 Continental Teves Ag & Co. Ohg Method and device for determining a roadway state by means of a vehicle camera system

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10311240A1 (en) 2003-03-14 2004-09-30 Robert Bosch Gmbh Road lane tracking system has permanent and temporary markings in different colors that are automatically identified
DE102004052127A1 (en) 2004-10-27 2006-05-04 Hella Kgaa Hueck & Co. Method for tracking a road-bound vehicle
DE102004057296A1 (en) 2004-11-26 2006-06-08 Daimlerchrysler Ag Lane departure warning with distinction between lane markings and the construction boundary of the lane

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE10311240A1 (en) 2003-03-14 2004-09-30 Robert Bosch Gmbh Road lane tracking system has permanent and temporary markings in different colors that are automatically identified
DE102004052127A1 (en) 2004-10-27 2006-05-04 Hella Kgaa Hueck & Co. Method for tracking a road-bound vehicle
DE102004057296A1 (en) 2004-11-26 2006-06-08 Daimlerchrysler Ag Lane departure warning with distinction between lane markings and the construction boundary of the lane

Cited By (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2431917A1 (en) * 2010-09-21 2012-03-21 Mobileye Technologies Limited Barrier and guardrail detection using a single camera
US10445595B2 (en) 2010-09-21 2019-10-15 Mobileye Vision Technologies Ltd. Barrier and guardrail detection using a single camera
US10115027B2 (en) 2010-09-21 2018-10-30 Mibileye Vision Technologies Ltd. Barrier and guardrail detection using a single camera
US10078788B2 (en) 2010-09-21 2018-09-18 Mobileye Vision Technologies Ltd. Barrier and guardrail detection using a single camera
US9280711B2 (en) 2010-09-21 2016-03-08 Mobileye Vision Technologies Ltd. Barrier and guardrail detection using a single camera
US9959595B2 (en) 2010-09-21 2018-05-01 Mobileye Vision Technologies Ltd. Dense structure from motion
EP3301612A1 (en) * 2010-09-21 2018-04-04 Mobileye Vision Technologies Ltd. Barrier and guardrail detection using a single camera
US10685424B2 (en) 2010-09-21 2020-06-16 Mobileye Vision Technologies Ltd. Dense structure from motion
WO2013091620A1 (en) * 2011-12-20 2013-06-27 Conti Temic Microelectronic Gmbh Determining a vertical profile of a vehicle environment by means of a 3d camera
DE102011122310A1 (en) 2011-12-23 2015-06-18 Daimler Ag Method and device for recognizing lane markings
US9679204B2 (en) 2012-02-10 2017-06-13 Conti Temic Microelectronic Gmbh Determining the characteristics of a road surface by means of a 3D camera
US10289920B2 (en) 2013-11-15 2019-05-14 Continental Teves Ag & Co. Ohg Method and device for determining a roadway state by means of a vehicle camera system
DE102014209796A1 (en) 2014-05-22 2015-11-26 Hella Kgaa Hueck & Co. Method for controlling a cornering light
DE102016211730A1 (en) * 2016-06-29 2018-01-04 Continental Teves Ag & Co. Ohg Method for predicting a lane course of a roadway
DE102016011789A1 (en) 2016-09-30 2017-03-02 Daimler Ag Method for determining a lane course
DE102017001814A1 (en) 2017-02-27 2017-10-19 Daimler Ag Method for detecting lane markings
DE102017007766A1 (en) 2017-08-16 2018-02-22 Daimler Ag Method for detecting a lane course

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