MX2018000463A - Generacion de datos de sensor simulados para entrenamiento y validacion de modelos de deteccion. - Google Patents
Generacion de datos de sensor simulados para entrenamiento y validacion de modelos de deteccion.Info
- Publication number
- MX2018000463A MX2018000463A MX2018000463A MX2018000463A MX2018000463A MX 2018000463 A MX2018000463 A MX 2018000463A MX 2018000463 A MX2018000463 A MX 2018000463A MX 2018000463 A MX2018000463 A MX 2018000463A MX 2018000463 A MX2018000463 A MX 2018000463A
- Authority
- MX
- Mexico
- Prior art keywords
- scenario
- sensor
- sensor outputs
- validation
- training
- Prior art date
Links
- 238000001514 detection method Methods 0.000 title 1
- 238000010200 validation analysis Methods 0.000 title 1
- 238000010801 machine learning Methods 0.000 abstract 1
- 230000008447 perception Effects 0.000 abstract 1
- 238000013179 statistical model Methods 0.000 abstract 1
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06G—ANALOGUE COMPUTERS
- G06G7/00—Devices in which the computing operation is performed by varying electric or magnetic quantities
- G06G7/48—Analogue computers for specific processes, systems or devices, e.g. simulators
- G06G7/70—Analogue computers for specific processes, systems or devices, e.g. simulators for vehicles, e.g. to determine permissible loading of ships, centre of gravity, necessary fuel
-
- 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
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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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
- G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/29—Graphical models, e.g. Bayesian networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computing arrangements based on specific mathematical models
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computing arrangements based on specific mathematical models
- G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computing arrangements based on specific mathematical models
- G06N7/02—Computing arrangements based on specific mathematical models using fuzzy logic
- G06N7/06—Simulation on general purpose computers
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
-
- 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
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Artificial Intelligence (AREA)
- Data Mining & Analysis (AREA)
- Mathematical Physics (AREA)
- Computing Systems (AREA)
- Geometry (AREA)
- Automation & Control Theory (AREA)
- Medical Informatics (AREA)
- Computer Hardware Design (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Optimization (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Remote Sensing (AREA)
- Algebra (AREA)
- Health & Medical Sciences (AREA)
- Game Theory and Decision Science (AREA)
- Business, Economics & Management (AREA)
- Multimedia (AREA)
- Life Sciences & Earth Sciences (AREA)
- Probability & Statistics with Applications (AREA)
- Mechanical Engineering (AREA)
- Fuzzy Systems (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Biomedical Technology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Transportation (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Traffic Control Systems (AREA)
Abstract
Se define un caso hipotético que incluye modelos de vehículos y un entorno de manejo típico. Se agrega un modelo de un vehículo objeto al caso hipotético y se definen las ubicaciones de sensor en el vehículo objeto. Se simula la percepción del caso hipotético mediante sensores en las ubicaciones de sensores para obtener emisiones de sensor simuladas. Las emisiones de sensor simuladas se anotan para indicar la ubicación de los obstáculos en el caso hipotético. Las emisiones de sensor anotadas pueden entonces ser utilizadas para validar un modelo estadístico o para entrenar un modelo de aprendizaje por máquina. Las emisiones de sensor simuladas se pueden modelar con suficiente detalle para incluir ruido de sensor o pueden incluir ruido agregado artificialmente para simular condiciones de mundo real.
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US15/406,031 US10228693B2 (en) | 2017-01-13 | 2017-01-13 | Generating simulated sensor data for training and validation of detection models |
Publications (1)
Publication Number | Publication Date |
---|---|
MX2018000463A true MX2018000463A (es) | 2018-11-09 |
Family
ID=61190327
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
MX2018000463A MX2018000463A (es) | 2017-01-13 | 2018-01-11 | Generacion de datos de sensor simulados para entrenamiento y validacion de modelos de deteccion. |
Country Status (6)
Country | Link |
---|---|
US (1) | US10228693B2 (es) |
CN (1) | CN108304782A (es) |
DE (1) | DE102018100469A1 (es) |
GB (1) | GB2560412A (es) |
MX (1) | MX2018000463A (es) |
RU (1) | RU2694154C2 (es) |
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2017
- 2017-01-13 US US15/406,031 patent/US10228693B2/en not_active Expired - Fee Related
- 2017-12-27 RU RU2017146151A patent/RU2694154C2/ru active
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2018
- 2018-01-08 CN CN201810014529.7A patent/CN108304782A/zh not_active Withdrawn
- 2018-01-09 GB GB1800312.9A patent/GB2560412A/en not_active Withdrawn
- 2018-01-10 DE DE102018100469.9A patent/DE102018100469A1/de active Pending
- 2018-01-11 MX MX2018000463A patent/MX2018000463A/es unknown
Also Published As
Publication number | Publication date |
---|---|
US10228693B2 (en) | 2019-03-12 |
CN108304782A (zh) | 2018-07-20 |
RU2017146151A (ru) | 2019-06-28 |
GB2560412A (en) | 2018-09-12 |
RU2017146151A3 (es) | 2019-07-17 |
US20180203445A1 (en) | 2018-07-19 |
RU2694154C2 (ru) | 2019-07-09 |
DE102018100469A1 (de) | 2018-07-19 |
GB201800312D0 (en) | 2018-02-21 |
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