EP2862123A1 - Method for displaying a vehicle environment - Google Patents
Method for displaying a vehicle environmentInfo
- Publication number
- EP2862123A1 EP2862123A1 EP13727037.7A EP13727037A EP2862123A1 EP 2862123 A1 EP2862123 A1 EP 2862123A1 EP 13727037 A EP13727037 A EP 13727037A EP 2862123 A1 EP2862123 A1 EP 2862123A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- probability
- resolution level
- grid
- grid cells
- value
- 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.)
- Ceased
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 230000007613 environmental effect Effects 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 3
- 238000013507 mapping Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 description 4
- 238000013459 approach Methods 0.000 description 2
- 241000282941 Rangifer tarandus Species 0.000 description 1
- 235000013405 beer Nutrition 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Classifications
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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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/97—Determining parameters from multiple pictures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
-
- 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
-
- 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
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
- H04N23/951—Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
-
- 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
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
-
- 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
- Quadtrees in two-dimensional space and octtrees in three-dimensional space which are based on a recursive subdivision of an area into quarters, are known here. This is illustrated by way of example in FIG. 1a.
- a tree-like data structure For storing the data (probability values) a tree-like data structure can be used, this is illustrated by way of example in FIG. 1b.
- the environment model can process and provide environment data in various resolution levels. This object is achieved by the features of independent claim 1.
- An ⁇ An advantageous use of the method according ⁇ invention is given in the further independent claims.
- the inventive method comprises imaging a vehicle surrounding environment in a model with at least two resolu ⁇ sungsebenen.
- the environment model is configured as a Probability ⁇ grid having a plurality of grid cells.
- a different spatial resolution In a high resolution level a predetermined region is displayed in the field by a higher At ⁇ number of lattice cells than in a low resolution level.
- the method is provided for a vehicle that includes at least one sensor system for environment detection and at least one driver assistance system.
- the sensor system, the environment information for the environment model for Availability checked ⁇ supply and function of the driver assistance system is based on the so-created environment model.
- Data from at least two Git ⁇ terzellen at a high resolution level are summarized and stored in a grid cell at a lower resolu ⁇ sungsrase.
- a processing of the data in various levels of resolution can be performed.
- three resolution levels (a, b, c) are shown as a tree structure by way of example.
- (coarser resolution) for applications that do not require high resolution calculation time can be saved by processing Informa ⁇ functions on lower level.
- a plurality of higher resolution cells eg resolution level c in FIG. 1b
- a simple average for the proces ⁇ processing of probabilities would lead, when used in an environment model for a driver assistance system to an incorrect result, as the following example illustrates: If the detected occupancy of a cell of 100% and three unoccupied cells (0%) sublattice is a be ⁇ interpretation of 25% as the average value would give it, incorrect because an occupancy is given on the combined surface still 100%.
- the inventive method provides that, taken together for a ⁇ men charged of at least two grid cells at a high resolution level, the value one of the at least two grid cells and is stored in a grid cell on a lower resolution level.
- the at least two lattice cells contained on a high resolution level a probability value that indicates an occupancy plausibility ⁇ friendliness.
- the document probability indicates whether the corresponding area in the real world is occupied by obstacles, for example, and thus can not be traversed by a vehicle.
- the maximum value of the grid cells at a high resolution level is entered into a grid cell at a lower resolution level. In Figure 2, this process is exemplified for summarizing four cells.
- the area in the lower left of the trokeitsgit ⁇ ters includes four cells, one of which is marked as occupied by a black color and has the maximum document International ⁇ probability of the four cells.
- the four ⁇ tel is summarized in a lower resolution level is set ⁇ , the entire area is now colored black and is therefore marked busy or carries the maximum evidence probability ⁇ of the four individual cells from Fig. 2a.
- a re ⁇ italic division into quarters (level, Quadtree) or eighths (Spatial, Octtree) and any other divisions are possible.
- m is a name
- the grid cells contain the at least two grid cells on a high resolution level only a single probability value, which indicates an occupancy probability.
- At least two grid cells contain at a high resolution level a probability value indicating a probability space ⁇ .
- the free space probability indicates whether the corresponding area in the real world is free and thus passable for a vehicle.
- the grid cells contain the at least two grid cells on a high Resolution level only a single probability value indicating a free space probability.
- At least two probability values are stored in the at least two grid cells at a high level of resolution, namely a probability value that indicates an occupancy probability, and a probability value indicating a free ⁇ space probability.
- the maximum occupancy probability value and the free space value associated with the maximum value grid cell are entered at a high resolution level into a grid cell at a lower resolution level.
- a summary in the case that a plurality of grid ⁇ cells of the probability lattice contains a value for a reflected power of a radar or lidar or ultrasonic ⁇ sensors provided so that the minimum value of the grid cells at a high level of resolution in a grid cell is entered at a lower resolution level.
- a plurality of lattice cells of the probability lattice contain a value provided by a camera sensor system, which indicates a height or a height gradient for this space segment.
- the minimum value of the grid cells or the maximum value of the grid cells at a high resolution level is entered into a grid cell at a lower resolution level.
- the value is stored in a grid cell at a lower resolution level in the form of a reference to that grid cell of a high resolution level whose value is to be adopted. By way of example, this is shown in FIG. There, the bolded paths indicate a reference to a cell at a higher resolution level.
- a low-resolution sensor A (FIG. 2 b) is fused to a high-resolution sensor B (FIG. 2 a).
- the low-resolution information from sensor A is fused with the relevant information of the high-resolution sensor B.
- the tree structure for storing the data with reference to the relevant cells can be used in particular in a network with several subscribers for efficient data transmission.
- a source sends the tree up to the highest resolution level to all receiving subscribers.
- the receiving participants reconstruct the tree up to the required resolution level, higher-level planes are ignored, for example. This can be saved in the participants who are not the maximum resolution level Need Beer ⁇ term, memory and processing time.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Mechanical Engineering (AREA)
- Mathematical Physics (AREA)
- Transportation (AREA)
- Automation & Control Theory (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computing Systems (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
- Image Processing (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE102012105332A DE102012105332A1 (en) | 2012-06-19 | 2012-06-19 | Method for displaying a vehicle environment |
PCT/DE2013/100156 WO2013189482A1 (en) | 2012-06-19 | 2013-04-30 | Method for displaying a vehicle environment |
Publications (1)
Publication Number | Publication Date |
---|---|
EP2862123A1 true EP2862123A1 (en) | 2015-04-22 |
Family
ID=48576674
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP13727037.7A Ceased EP2862123A1 (en) | 2012-06-19 | 2013-04-30 | Method for displaying a vehicle environment |
Country Status (5)
Country | Link |
---|---|
US (1) | US9607229B2 (en) |
EP (1) | EP2862123A1 (en) |
JP (1) | JP2015521767A (en) |
DE (2) | DE102012105332A1 (en) |
WO (1) | WO2013189482A1 (en) |
Families Citing this family (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE102013207904A1 (en) * | 2013-04-30 | 2014-10-30 | Bayerische Motoren Werke Aktiengesellschaft | Provide an efficient environment map for a vehicle |
EP3048023B1 (en) * | 2015-01-23 | 2018-11-28 | Honda Research Institute Europe GmbH | Method for assisting a driver in driving an ego vehicle and corresponding driver assistance system |
DE102015212771A1 (en) * | 2015-07-08 | 2017-01-12 | Bayerische Motoren Werke Aktiengesellschaft | Device for detecting partially concealed moving objects for an environment detection system of a motor vehicle |
US9796390B2 (en) * | 2016-02-29 | 2017-10-24 | Faraday&Future Inc. | Vehicle sensing grid having dynamic sensing cell size |
EP3229172A1 (en) | 2016-04-04 | 2017-10-11 | Conti Temic microelectronic GmbH | Driver assistance system with variable image resolution |
FR3052275A1 (en) | 2016-06-03 | 2017-12-08 | Commissariat Energie Atomique | METHOD AND SYSTEM FOR DETERMINING CELLS CROSSED BY A MEASURING OR VISUALIZATION AXIS |
DE102016215249B4 (en) * | 2016-08-16 | 2022-03-31 | Volkswagen Aktiengesellschaft | Method and device for supporting a driver assistance system in a motor vehicle |
CN109903367B (en) * | 2017-12-07 | 2023-09-22 | 北京京东乾石科技有限公司 | Method, apparatus and computer readable storage medium for constructing map |
CN108319655B (en) * | 2017-12-29 | 2021-05-07 | 百度在线网络技术(北京)有限公司 | Method and device for generating grid map |
JP7195073B2 (en) * | 2018-07-10 | 2022-12-23 | 古野電気株式会社 | graph generator |
EP3654064B1 (en) * | 2018-11-16 | 2021-01-13 | Bayerische Motoren Werke Aktiengesellschaft | Apparatus and method for characterizing an object based on measurement samples from one or more location sensors |
US11625009B2 (en) * | 2020-03-26 | 2023-04-11 | Intel Corporation | Non-uniform occupancy grid manager |
US11931900B2 (en) * | 2020-07-24 | 2024-03-19 | Samsung Electronics Co., Ltd. | Method of predicting occupancy of unseen areas for path planning, associated device, and network training method |
Family Cites Families (15)
Publication number | Priority date | Publication date | Assignee | Title |
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US5006988A (en) * | 1989-04-28 | 1991-04-09 | University Of Michigan | Obstacle-avoiding navigation system |
JP3147541B2 (en) * | 1992-11-06 | 2001-03-19 | 株式会社豊田中央研究所 | Obstacle recognition device for vehicles |
KR960706267A (en) * | 1993-11-15 | 1996-11-08 | 존 엠. 클락 3세 | QUADTREE-STRUCTURED WALSH TRANSFORM CONDING |
US6915015B1 (en) * | 2000-03-21 | 2005-07-05 | Hewlett-Packard Development Company, L.P. | Apparatus for and method for SNR scalable quad-tree bit-plane coding |
US6868420B2 (en) * | 2002-07-31 | 2005-03-15 | Mitsubishi Electric Research Laboratories, Inc. | Method for traversing quadtrees, octrees, and N-dimensional bi-trees |
FR2890774B1 (en) * | 2005-09-09 | 2007-11-16 | Inst Nat Rech Inf Automat | VEHICLE DRIVING ASSISANCE METHOD AND IMPROVED ASSOCIATED DEVICE |
DE102006056835A1 (en) * | 2006-12-01 | 2008-06-05 | Robert Bosch Gmbh | Method for the grid-based processing of sensor signals |
DE102007012458A1 (en) * | 2007-03-15 | 2008-09-18 | Robert Bosch Gmbh | Method for object formation |
DE102009007395B4 (en) * | 2008-03-25 | 2015-11-26 | Volkswagen Ag | Method for map-based environment representation of a vehicle |
JP4615038B2 (en) * | 2008-06-23 | 2011-01-19 | 日立オートモティブシステムズ株式会社 | Image processing device |
DE112010000146A5 (en) * | 2009-05-06 | 2012-06-06 | Conti Temic Microelectronic Gmbh | Method for evaluating sensor data for a motor vehicle |
DE102010006828B4 (en) * | 2010-02-03 | 2021-07-08 | Volkswagen Ag | Method for the automatic creation of a model of the surroundings of a vehicle as well as driver assistance system and vehicle |
DE102010011629A1 (en) * | 2010-03-16 | 2011-01-05 | Daimler Ag | Method for environmental representation of vehicle, involves recording and storing environment data in hierarchical data structures, which are identified in environmental objects |
JP5206752B2 (en) * | 2010-08-30 | 2013-06-12 | 株式会社デンソー | Driving environment recognition device |
DE102011113016A1 (en) * | 2011-09-09 | 2012-03-29 | Daimler Ag | Method for representing environment of vehicle, involves increasing detail information level of hierarchical data structure corresponding to object with high uncertainty than that of other objects identified in environment of vehicle |
-
2012
- 2012-06-19 DE DE102012105332A patent/DE102012105332A1/en not_active Withdrawn
-
2013
- 2013-04-30 WO PCT/DE2013/100156 patent/WO2013189482A1/en active Application Filing
- 2013-04-30 DE DE112013003083.7T patent/DE112013003083A5/en active Pending
- 2013-04-30 US US14/371,113 patent/US9607229B2/en active Active
- 2013-04-30 EP EP13727037.7A patent/EP2862123A1/en not_active Ceased
- 2013-04-30 JP JP2015517608A patent/JP2015521767A/en active Pending
Non-Patent Citations (2)
Title |
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None * |
See also references of WO2013189482A1 * |
Also Published As
Publication number | Publication date |
---|---|
JP2015521767A (en) | 2015-07-30 |
US20150003683A1 (en) | 2015-01-01 |
DE102012105332A1 (en) | 2013-12-19 |
US9607229B2 (en) | 2017-03-28 |
DE112013003083A5 (en) | 2015-04-09 |
WO2013189482A1 (en) | 2013-12-27 |
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