WO2022193154A1 - Procédé de commande d'essuie-glace de pare-brise, véhicule automobile et support de stockage lisible par ordinateur - Google Patents
Procédé de commande d'essuie-glace de pare-brise, véhicule automobile et support de stockage lisible par ordinateur Download PDFInfo
- Publication number
- WO2022193154A1 WO2022193154A1 PCT/CN2021/081175 CN2021081175W WO2022193154A1 WO 2022193154 A1 WO2022193154 A1 WO 2022193154A1 CN 2021081175 W CN2021081175 W CN 2021081175W WO 2022193154 A1 WO2022193154 A1 WO 2022193154A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- image
- measurement value
- snow
- rain
- wiper
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 54
- 238000012545 processing Methods 0.000 claims abstract description 23
- 238000005259 measurement Methods 0.000 claims description 184
- 238000001514 detection method Methods 0.000 claims description 62
- 230000000875 corresponding effect Effects 0.000 claims description 20
- 238000012549 training Methods 0.000 claims description 16
- 238000004590 computer program Methods 0.000 claims description 14
- 230000006870 function Effects 0.000 claims description 12
- 230000001276 controlling effect Effects 0.000 claims description 6
- 238000003062 neural network model Methods 0.000 claims description 6
- 230000002596 correlated effect Effects 0.000 claims description 4
- 238000004422 calculation algorithm Methods 0.000 description 7
- 238000013135 deep learning Methods 0.000 description 7
- 238000013507 mapping Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 230000008569 process Effects 0.000 description 4
- 238000004088 simulation Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 239000011521 glass Substances 0.000 description 3
- 238000002372 labelling Methods 0.000 description 3
- SAZUGELZHZOXHB-UHFFFAOYSA-N acecarbromal Chemical compound CCC(Br)(CC)C(=O)NC(=O)NC(C)=O SAZUGELZHZOXHB-UHFFFAOYSA-N 0.000 description 2
- 238000005094 computer simulation Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 238000002310 reflectometry Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000011664 signaling Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60S—SERVICING, CLEANING, REPAIRING, SUPPORTING, LIFTING, OR MANOEUVRING OF VEHICLES, NOT OTHERWISE PROVIDED FOR
- B60S1/00—Cleaning of vehicles
- B60S1/02—Cleaning windscreens, windows or optical devices
- B60S1/04—Wipers or the like, e.g. scrapers
- B60S1/06—Wipers or the like, e.g. scrapers characterised by the drive
- B60S1/08—Wipers or the like, e.g. scrapers characterised by the drive electrically driven
Definitions
- FIG. 1 is a schematic diagram of a scene for implementing the wiper control method provided by the embodiment of the present application
- FIG. 2 is a schematic flowchart of steps of a wiper control method provided by an embodiment of the present application
- first sample data is obtained, where the first sample data includes a rain image and a real rain-free image corresponding to the rain image; the rain image is input to a generator in a preset generation network, and a prediction is output.
- the predicted rain-free image and the real rain-free image are input into the judger in the preset generation network, and the classification result is obtained; according to the classification result and the similarity between the rain-free image output by the generator and the real rain-free image degree, determine the loss value of the preset generation network, if the loss value is greater than the preset loss value, update the parameters of the preset generation network, and then repeat the above process until the calculated loss value is less than or equal to the preset loss value, thus
- the first target generation network can be obtained.
- the field of view of the image acquisition device covers the windshield of the car, so that the image acquisition device can acquire an image including the windshield, and then the amount of rain or snow on the windshield can be determined based on the acquired image.
- the windshield may include the front windshield and the rear windshield of the car, and both the front windshield and the rear windshield of the car may be provided with wipers.
- the field of view of the image capture device can cover the entire windshield of the car, or it can not cover the entire windshield of the car, but cover the area that the windshield wiper on the car can wipe off. , which is not specifically limited in the embodiments of the present application.
- the image acquisition device can be a driving recorder of a car, and no additional hardware needs to be added, which can reduce costs.
- the manner of determining the first weight coefficient of the first measurement value and the second weight coefficient of the second measurement value according to the deviation may be: acquiring a preset mapping relationship between the deviation and the weight coefficient group, and According to the mapping relationship and the deviation between the first measurement value and the second measurement value, a weight coefficient group is obtained, where the weight coefficient group includes a first weight coefficient and a second weight coefficient, and the first weight coefficient is greater than the second weight coefficient.
- the mapping relationship between the preset deviation and the weight coefficient group may be set based on the actual situation, which is not specifically limited in this embodiment of the present application.
- the deviation between the first measurement value and the second measurement value is determined; if the deviation between the first measurement value and the second measurement value is less than or equal to a preset deviation, the first measurement is determined according to the deviation The first weight coefficient of the value and the second weight coefficient of the second measurement value; the multiplication of the first measurement value and the first weight to obtain the first weighted measurement value; the multiplication of the second measurement value and the second weight Operation is performed to obtain a second weighted measurement value; the first weighted measurement value and the second weighted measurement value are summed to obtain a target measurement value.
- the field of view of the image capture device 320 covers the windshield of the car 300 , and the image capture device 320 is used to capture an image including the windshield of the car 300 .
- the image capturing device 320 may include a driving recorder or a camera.
- the loss function of the generator is inversely proportional to the degree of similarity between the rain-free image output by the generator and the real rain-free image
- the loss function of the judger is inversely proportional to the judger's loss function. The correctness of the classification results.
Landscapes
- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
Procédé de commande d'essuie-glace de pare-brise, véhicule automobile et support de stockage lisible par ordinateur, le procédé consistant : à acquérir une première image capturée par un dispositif de capture d'image et à entrer la première image dans un réseau génératif cible pour un traitement de manière à éliminer les gouttes de pluie ou la neige de la première image pour obtenir une seconde image ; à réaliser une soustraction sur la première image et la seconde image sur la base de pixels et à accumuler le résultat de soustraction de chaque pixel de manière à obtenir une première valeur mesurée de chutes de pluie ou de neige sur un pare-brise ; et en fonction de la première valeur mesurée, à commander un essuie-glace pour son fonctionnement, de manière à éliminer l'eau de pluie ou la neige sur le pare-brise. Au moyen du procédé, l'intelligence et la précision de la commande d'essuie-glace de pare-brise peuvent être améliorées.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2021/081175 WO2022193154A1 (fr) | 2021-03-16 | 2021-03-16 | Procédé de commande d'essuie-glace de pare-brise, véhicule automobile et support de stockage lisible par ordinateur |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2021/081175 WO2022193154A1 (fr) | 2021-03-16 | 2021-03-16 | Procédé de commande d'essuie-glace de pare-brise, véhicule automobile et support de stockage lisible par ordinateur |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2022193154A1 true WO2022193154A1 (fr) | 2022-09-22 |
Family
ID=83321779
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/CN2021/081175 WO2022193154A1 (fr) | 2021-03-16 | 2021-03-16 | Procédé de commande d'essuie-glace de pare-brise, véhicule automobile et support de stockage lisible par ordinateur |
Country Status (1)
| Country | Link |
|---|---|
| WO (1) | WO2022193154A1 (fr) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103376243A (zh) * | 2012-04-18 | 2013-10-30 | 原相科技股份有限公司 | 雨刷控制装置、光学雨滴检测装置及其检测方法 |
| US20150310304A1 (en) * | 2010-03-04 | 2015-10-29 | Valeo Schalter Und Sensoren Gmbh | Method of raindrop detection on a vehicle windscreen and driving assistance device |
| CN108528395A (zh) * | 2018-04-08 | 2018-09-14 | 广州大学 | 一种基于图像识别的车辆智能雨刮控制方法及系统 |
| CN108556795A (zh) * | 2018-04-08 | 2018-09-21 | 广州大学 | 一种车辆智能电控设备集成控制方法及系统 |
| CN109760635A (zh) * | 2019-01-08 | 2019-05-17 | 同济大学 | 一种基于gan网络的线控雨刷控制系统 |
-
2021
- 2021-03-16 WO PCT/CN2021/081175 patent/WO2022193154A1/fr active Application Filing
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150310304A1 (en) * | 2010-03-04 | 2015-10-29 | Valeo Schalter Und Sensoren Gmbh | Method of raindrop detection on a vehicle windscreen and driving assistance device |
| CN103376243A (zh) * | 2012-04-18 | 2013-10-30 | 原相科技股份有限公司 | 雨刷控制装置、光学雨滴检测装置及其检测方法 |
| CN108528395A (zh) * | 2018-04-08 | 2018-09-14 | 广州大学 | 一种基于图像识别的车辆智能雨刮控制方法及系统 |
| CN108556795A (zh) * | 2018-04-08 | 2018-09-21 | 广州大学 | 一种车辆智能电控设备集成控制方法及系统 |
| CN109760635A (zh) * | 2019-01-08 | 2019-05-17 | 同济大学 | 一种基于gan网络的线控雨刷控制系统 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110988912B (zh) | 自动驾驶车辆的道路目标与距离检测方法、系统、装置 | |
| US10817731B2 (en) | Image-based pedestrian detection | |
| CN108571974B (zh) | 使用摄像机的车辆定位 | |
| CN112665556B (zh) | 使用被动和主动测量生成场景的三维地图 | |
| US10891518B1 (en) | Auto labeler | |
| CN108270970B (zh) | 一种图像采集控制方法及装置、图像采集系统 | |
| Negru et al. | Image based fog detection and visibility estimation for driving assistance systems | |
| US11565659B2 (en) | Raindrop recognition device, vehicular control apparatus, method of training model, and trained model | |
| US20150220791A1 (en) | Automatic training of a parked vehicle detector for large deployment | |
| Joubert et al. | Pothole tagging system | |
| CN110852274A (zh) | 一种基于图像识别的智能雨量感知方法及装置 | |
| CN109934108B (zh) | 一种多目标多种类的车辆检测和测距系统及实现方法 | |
| EP3824623A1 (fr) | Techniques d'évaluation de caméra pour véhicules autonomes | |
| CN111652060A (zh) | 一种基于激光雷达的限高预警方法、装置、电子设备及存储介质 | |
| RU2769921C2 (ru) | Способы и системы для автоматизированного определения присутствия объектов | |
| CN111967396A (zh) | 障碍物检测的处理方法、装置、设备及存储介质 | |
| CN114910927A (zh) | 使用单色成像的基于事件的车辆姿态估计 | |
| WO2022193154A1 (fr) | Procédé de commande d'essuie-glace de pare-brise, véhicule automobile et support de stockage lisible par ordinateur | |
| CN210822158U (zh) | 机动车雨刷自动控制系统 | |
| CN111596090A (zh) | 车辆行驶速度的测量方法、装置、车辆和介质 | |
| CN211498390U (zh) | 一种车载冰面识别追踪系统 | |
| CN111739332B (zh) | 一种停车场管理系统 | |
| EP3336748B1 (fr) | Detection de fortes pluies en mesurant temporallement le flou de contours | |
| CN110660113A (zh) | 特征地图的建立方法、装置、采集设备和存储介质 | |
| CN114519732A (zh) | 一种基于红外双目结构光的道路检测方法与系统 |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| 121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 21930750 Country of ref document: EP Kind code of ref document: A1 |
|
| NENP | Non-entry into the national phase |
Ref country code: DE |
|
| 122 | Ep: pct application non-entry in european phase |
Ref document number: 21930750 Country of ref document: EP Kind code of ref document: A1 |