DE102013020435A1 - Method for recognizing objects e.g. lorry, in vehicle environment, involves performing rough categorization of objects based on volume and parameters, and performing fine categorization of objects based on to be fine-categorized object - Google Patents
Method for recognizing objects e.g. lorry, in vehicle environment, involves performing rough categorization of objects based on volume and parameters, and performing fine categorization of objects based on to be fine-categorized object Download PDFInfo
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- DE102013020435A1 DE102013020435A1 DE201310020435 DE102013020435A DE102013020435A1 DE 102013020435 A1 DE102013020435 A1 DE 102013020435A1 DE 201310020435 DE201310020435 DE 201310020435 DE 102013020435 A DE102013020435 A DE 102013020435A DE 102013020435 A1 DE102013020435 A1 DE 102013020435A1
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
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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
- B60W40/04—Traffic conditions
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/08—Detecting or categorising vehicles
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/10—Recognition assisted with metadata
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/015—Detecting movement of traffic to be counted or controlled with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- Automation & Control Theory (AREA)
- Mathematical Physics (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Traffic Control Systems (AREA)
Abstract
Description
Die Erfindung betrifft Verfahren zum Erkennen von Objekten in einer Fahrzeugumgebung mittels einer Bilderfassungsvorrichtung, wobei bei einer Modellierung der Fahrzeugumgebung eine Kategorisierung der Objekte durchgeführt wird.The invention relates to methods for recognizing objects in a vehicle environment by means of an image capture device, wherein a categorization of the objects is carried out in a modeling of the vehicle environment.
Die Erfindung betrifft weiterhin eine Verwendung der mittels eines solchen Verfahrens durchgeführten Kategorisierung.The invention further relates to a use of the categorization carried out by means of such a method.
Aus dem Stand der Technik sind allgemein Verfahren zum Erkennen von Objekten in einer Fahrzeugumgebung mittels Bilderfassungsvorrichtungen bekannt. Hierbei erfolgt eine Modellierung der Fahrzeugumgebung mittels vordefinierter Kategorien, in welchen die Objekte als Lastkraftwagen, Personenkraftwagen, Zweiräder und Fußgänger kategorisiert bzw. klassifiziert sind.From the prior art, methods for recognizing objects in a vehicle environment by means of image capture devices are generally known. Here, a modeling of the vehicle environment by means of predefined categories in which the objects are categorized or classified as trucks, passenger cars, two-wheelers and pedestrians.
Der Erfindung liegt die Aufgabe zu Grunde, ein gegenüber dem Stand der Technik verbessertes Verfahren zum Erkennen von Objekten in einer Fahrzeugumgebung mittels einer Bilderfassungsvorrichtung und eine Verwendung einer mittels eines solchen Verfahrens durchgeführten Kategorisierung anzugeben.The invention is based on the object to provide a comparison with the prior art improved method for detecting objects in a vehicle environment by means of an image capture device and use of a categorization performed by such a method.
Hinsichtlich des Verfahrens wird die Aufgabe erfindungsgemäß durch die im Anspruch 1 angegebenen Merkmale und hinsichtlich der Verwendung durch die im Anspruch 4 angegebenen Merkmale gelöst.With regard to the method, the object is achieved by the features specified in claim 1 and in terms of the use by the features specified in
Vorteilhafte Ausgestaltungen der Erfindung sind Gegenstand der Unteransprüche.Advantageous embodiments of the invention are the subject of the dependent claims.
In einem Verfahren zum Erkennen von Objekten in einer Fahrzeugumgebung mittels einer Bilderfassungsvorrichtung wird bei einer Modellierung der Fahrzeugumgebung eine Kategorisierung der Objekte durchgeführt.In a method for recognizing objects in a vehicle environment by means of an image capture device, a categorization of the objects is carried out in a modeling of the vehicle environment.
Erfindungsgemäß werden in einem ersten Schritt der Kategorisierung in einer Grobkategorisierung die Objekte anhand von deren Volumen und/oder Bewegungsparameter vorkategorisiert. In einem zweiten Schritt der Kategorisierung werden die Objekte in einer Feinkategorisierung anhand zumindest eines weiteren Objektmerkmals feinkategorisiert.According to the invention, in a first step of the categorization in a coarse categorization, the objects are pre-categorized on the basis of their volume and / or movement parameters. In a second step of the categorization, the objects are finely categorized in a fine categorization on the basis of at least one further object feature.
Durch die Feinkategorisierung bzw. Subkategorisierung ist eine besonders genaue Modellierung der Fahrzeugumgebung realisierbar, wodurch eine Verwendung der durchgeführten Kategorisierung für eine Trajektorieplanung des Fahrzeugs für ein autonomes Fahren möglich ist.By means of the fine categorization or subcategorization, a particularly accurate modeling of the vehicle environment can be realized, whereby it is possible to use the categorization carried out for a trajectory planning of the vehicle for autonomous driving.
Ausführungsbeispiele der Erfindung werden im Folgenden anhand von Zeichnungen näher erläutert.Embodiments of the invention are explained in more detail below with reference to drawings.
Dabei zeigen:Showing:
Einander entsprechende Teile sind in allen Figuren mit den gleichen Bezugszeichen versehen.Corresponding parts are provided in all figures with the same reference numerals.
In
Das Fahrzeug
In den erfassten Bildern erfolgt in einem ersten Verfahrensschritt S1 eine Detektion von in der Fahrzeugumgebung befindlichen Objekten
Diese Grobkategorisierung oder Vorkategorisierung erfolgt anhand von einem Volumen und/oder Bewegungsparametern der Objekte
Anschließend wird in einem dritten Verfahrensschritt S3 eine Feinkategorisierung der Objekte
Aus dieser Feinkategorisierung resultierende Daten werden gemeinsam mit Daten weiterer Sensoren
Anhand der Ergebnisse dieser Fusion wird zur Modellierung der Fahrzeugumgebung in einem fünften Verfahrensschritt S5 eine Situationsanalyse durchgeführt, anhand welcher wiederum in einem sechsten Verfahrensschritt S6 unter Berücksichtigung weiterer Umgebungsdaten UD, wie beispielsweise Umwelteinflüsse, insbesondere Wetterdaten, und Daten über eine befahrene Straße, insbesondere Straßentypen, beispielsweise ”Autobahn”, ”Innenstadt”, ”Landstraße” usw., eine Trajektorieplanung für das Fahrzeug
Anhand von in der Trajektorieplanung ermittelten Trajektoriedaten TD wird zur Realisierung des autonomen Fahrens eine Aktuatorik
In den
Aus diesem Grund werden die Objekte
Dabei wird das Objekt
Auch das Objekt
Das Objekt
Das Objekt
Das Objekt
Das Objekt
Das Objekt
Das Objekt
Das Objekt
Anhand der Feinkategorisierung ist es möglich, einen autonomen Überholvorgang des Fahrzeugs
Weiterhin sind in nicht näher dargestellter Weise beispielsweise beim Fahren in Innenstädten unterschiedliche Reaktionen und damit Trajektorieplanungen sowie Geschwindigkeitsverläufe anhand der Subkategorisierung von detektierten Fußgängern möglich.Furthermore, in a manner not shown in detail, for example when driving in inner cities different reactions and thus trajectory planning and speed profiles based on the subcategorization of detected pedestrians possible.
BezugszeichenlisteLIST OF REFERENCE NUMBERS
- 11
- Fahrzeugvehicle
- 22
- BilderfassungsvorrichtungImage capture device
- 33
- Sensorsensor
- 44
- Aktuatorikactuators
- 01 bis 0901 to 09
- Objektobject
- S1 bis S6S1 to S6
- Verfahrensschrittstep
- TDTD
- Trajektoriedatentrajectory data
- UDUD
- UmgebungsdatenEnvironmental data
Claims (4)
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DE201310020435 DE102013020435A1 (en) | 2013-12-06 | 2013-12-06 | Method for recognizing objects e.g. lorry, in vehicle environment, involves performing rough categorization of objects based on volume and parameters, and performing fine categorization of objects based on to be fine-categorized object |
Applications Claiming Priority (1)
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DE201310020435 DE102013020435A1 (en) | 2013-12-06 | 2013-12-06 | Method for recognizing objects e.g. lorry, in vehicle environment, involves performing rough categorization of objects based on volume and parameters, and performing fine categorization of objects based on to be fine-categorized object |
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DE102013020435A1 true DE102013020435A1 (en) | 2014-06-18 |
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DE201310020435 Withdrawn DE102013020435A1 (en) | 2013-12-06 | 2013-12-06 | Method for recognizing objects e.g. lorry, in vehicle environment, involves performing rough categorization of objects based on volume and parameters, and performing fine categorization of objects based on to be fine-categorized object |
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Cited By (12)
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CN105404294A (en) * | 2014-09-10 | 2016-03-16 | 大众汽车有限公司 | Modifying Autonomous Vehicle Driving By Recognizing Vehicle Characteristics |
DE102016001253A1 (en) | 2016-02-04 | 2016-09-15 | Daimler Ag | Method for operating a vehicle |
US10071732B2 (en) | 2017-01-17 | 2018-09-11 | Ford Global Technologies, Llc | Windshield stone impact response |
CN109002830A (en) * | 2017-06-06 | 2018-12-14 | 罗伯特·博世有限公司 | The for motor vehicle method and apparatus for object of classification |
DE102018212171A1 (en) | 2017-07-25 | 2019-01-31 | Ford Global Technologies, Llc | Method and device for detecting road users in the vicinity of a vehicle |
WO2018229552A3 (en) * | 2017-06-14 | 2019-02-21 | Mobileye Vision Technologies Ltd. | Fusion framework of navigation information for autonomous navigation |
WO2019180506A3 (en) * | 2018-03-20 | 2020-04-09 | Mobileye Vision Technologies Ltd. | Systems and methods for navigating a vehicle |
US20200202168A1 (en) * | 2018-12-21 | 2020-06-25 | Waymo Llc | Neural networks for coarse- and fine-object classifications |
DE102017117397B4 (en) | 2017-08-01 | 2022-02-17 | Phoenix Contact Gmbh & Co. Kg | Measuring signal device for a physical variable |
US11535242B2 (en) | 2017-12-19 | 2022-12-27 | Volkswagen Aktiengesellschaft | Method for detecting at least one object present on a motor vehicle, control device, and motor vehicle |
US11932277B2 (en) | 2018-08-14 | 2024-03-19 | Mobileye Vision Technologies Ltd. | Navigation with a safe longitudinal distance |
CN109002830B (en) * | 2017-06-06 | 2024-04-30 | 罗伯特·博世有限公司 | Method and device for classifying objects for vehicles |
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2013
- 2013-12-06 DE DE201310020435 patent/DE102013020435A1/en not_active Withdrawn
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EP2995519A1 (en) * | 2014-09-10 | 2016-03-16 | Volkswagen Aktiengesellschaft | Modifying autonomous vehicle driving by recognizing vehicle characteristics |
US9731713B2 (en) | 2014-09-10 | 2017-08-15 | Volkswagen Ag | Modifying autonomous vehicle driving by recognizing vehicle characteristics |
CN105404294A (en) * | 2014-09-10 | 2016-03-16 | 大众汽车有限公司 | Modifying Autonomous Vehicle Driving By Recognizing Vehicle Characteristics |
DE102016001253A1 (en) | 2016-02-04 | 2016-09-15 | Daimler Ag | Method for operating a vehicle |
US10071732B2 (en) | 2017-01-17 | 2018-09-11 | Ford Global Technologies, Llc | Windshield stone impact response |
GB2560421A (en) * | 2017-01-17 | 2018-09-12 | Ford Global Tech Llc | Windshield stone impact response |
CN109002830B (en) * | 2017-06-06 | 2024-04-30 | 罗伯特·博世有限公司 | Method and device for classifying objects for vehicles |
CN109002830A (en) * | 2017-06-06 | 2018-12-14 | 罗伯特·博世有限公司 | The for motor vehicle method and apparatus for object of classification |
WO2018229552A3 (en) * | 2017-06-14 | 2019-02-21 | Mobileye Vision Technologies Ltd. | Fusion framework of navigation information for autonomous navigation |
US11698263B2 (en) | 2017-06-14 | 2023-07-11 | Mobileye Vision Technologies Ltd. | Safety and comfort constraints for navigation |
US11561542B2 (en) | 2017-06-14 | 2023-01-24 | Mobileye Vision Technologies Ltd. | Safety and comfort constraints for navigation |
US10976741B2 (en) | 2017-06-14 | 2021-04-13 | Mobileye Vision Technologies Ltd. | Safety and comfort constraints for navigation |
DE102018212171B4 (en) | 2017-07-25 | 2023-08-24 | Ford Global Technologies, Llc | Method and device for detecting road users in the vicinity of a vehicle |
US10831194B2 (en) | 2017-07-25 | 2020-11-10 | Ford Global Technologies, Llc | Method and device that recognizes road users in an environment of a vehicle |
DE102018212171A1 (en) | 2017-07-25 | 2019-01-31 | Ford Global Technologies, Llc | Method and device for detecting road users in the vicinity of a vehicle |
DE102017117397B4 (en) | 2017-08-01 | 2022-02-17 | Phoenix Contact Gmbh & Co. Kg | Measuring signal device for a physical variable |
US11535242B2 (en) | 2017-12-19 | 2022-12-27 | Volkswagen Aktiengesellschaft | Method for detecting at least one object present on a motor vehicle, control device, and motor vehicle |
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WO2019180506A3 (en) * | 2018-03-20 | 2020-04-09 | Mobileye Vision Technologies Ltd. | Systems and methods for navigating a vehicle |
US11427192B2 (en) | 2018-03-20 | 2022-08-30 | Mobileye Vision Technologies Ltd. | Systems and methods for navigating a vehicle |
EP3636507A1 (en) * | 2018-03-20 | 2020-04-15 | Mobileye Vision Technologies Ltd. | Comfort responsibility sensitivity safety model |
US11731617B2 (en) | 2018-03-20 | 2023-08-22 | Mobileye Vision Technologies Ltd. | Systems and methods for navigating a vehicle |
EP3828049A1 (en) * | 2018-03-20 | 2021-06-02 | Mobileye Vision Technologies Ltd. | Comfort responsibility sensitivity safety model |
US11932277B2 (en) | 2018-08-14 | 2024-03-19 | Mobileye Vision Technologies Ltd. | Navigation with a safe longitudinal distance |
US20200202168A1 (en) * | 2018-12-21 | 2020-06-25 | Waymo Llc | Neural networks for coarse- and fine-object classifications |
US10867210B2 (en) * | 2018-12-21 | 2020-12-15 | Waymo Llc | Neural networks for coarse- and fine-object classifications |
US20220374650A1 (en) * | 2018-12-21 | 2022-11-24 | Waymo Llc | Neural networks for coarse- and fine-object classifications |
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