WO2023019509A1 - 基于环境匹配的车辆定位方法、装置、车辆及存储介质 - Google Patents
基于环境匹配的车辆定位方法、装置、车辆及存储介质 Download PDFInfo
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
- G06F16/51—Indexing; Data structures therefor; Storage structures
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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- G06N3/04—Architecture, e.g. interconnection topology
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- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
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- 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
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- 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
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
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- G06T2207/30248—Vehicle exterior or interior
- G06T2207/30252—Vehicle exterior; Vicinity of vehicle
- G06T2207/30256—Lane; Road marking
Definitions
- the present invention relates to the technical field of automatic driving, in particular to a vehicle positioning method, device, vehicle and storage medium based on environment matching.
- inertial navigation is used for position estimation, so that high-precision positioning can be achieved in different directions; another way is to use laser, vision and other single sensors or multi-sensor fusion (vision, laser, mmWave, etc.) for map collection, and use the mapping tool chain for simultaneous positioning and mapping (Simultaneous Localization And Mapping, SLAM), when the automatic driving system is running on the road, it uses sensors to perform feature matching to achieve high-precision positioning.
- SLAM Simultaneous Localization And Mapping
- the high-precision map (Map for Highly Automated Driving, HAD Map) requires map collection.
- the map collection team is full-time to collect or update map information.
- the main purpose of the present invention is to provide a vehicle positioning method, device, vehicle and storage medium based on environment matching, aiming at solving the technical problem of how to improve the vehicle positioning accuracy under different environmental conditions.
- the present invention provides a vehicle positioning method based on environment matching, the method includes the following steps:
- the current position information of the vehicle to be positioned is determined according to the target environment affecting road image.
- the step of finding the environment-affected road image set matching the current environment data it may further include:
- the basic road images are respectively injected according to the environmental impact feature information corresponding to different environmental impacts, so as to generate environmental impact road image sets under different environmental impacts.
- the step of acquiring a road image set in a preset environment mode, and performing environmental impact removal processing on the road image set to obtain a basic road image set includes:
- the step of injecting the basic road image according to the environmental impact feature information corresponding to different environmental impacts to generate the environmental impact road image sets under different environmental impacts includes:
- the environmental composite factors are respectively injected into the basic road images to generate environmental impact road image sets under different environmental influences.
- the step of respectively injecting the environmental composite factors into the basic road image to generate an environmental impact road image set under different environmental influences includes:
- the road component elements in the basic road image set are respectively rendered according to the environmental composite factors, so as to generate environmental impact road image sets under different environmental influences.
- the step of searching for an environment-impacted road image set matching the current environment data includes:
- the step of determining the current location information of the vehicle to be positioned according to the target environment affecting the road image includes:
- the current location information of the vehicle to be positioned is determined according to the historical GPS positioning information and the location information corresponding to the target environment-affected road image.
- the present invention also proposes a vehicle positioning device based on environment matching, and the vehicle positioning device based on environment matching includes:
- the data acquisition module is used to acquire the current environmental data of the location of the vehicle to be positioned and the current road image;
- An image set search module configured to search for an image set of environmental impact roads matching the current environmental data
- An image matching module configured to match the current road image with the environmental impact road images in the environmental impact road image set to obtain a target environmental impact road image matched with the current road image
- a vehicle positioning module configured to determine the current position information of the vehicle to be positioned according to the target environment affecting road image.
- the present invention also proposes a vehicle, the vehicle includes: a memory, a processor, and a vehicle positioning program based on environment matching that is stored in the memory and can run on the processor.
- the vehicle positioning program based on environment matching is configured to realize the steps of the above-mentioned vehicle positioning method based on environment matching.
- the present invention also proposes a storage medium, on which a vehicle positioning program based on environment matching is stored, and when the vehicle positioning program based on environment matching is executed by a processor, the above-mentioned The steps of the vehicle localization method based on environment matching.
- the current environment data and the current road image of the location of the vehicle to be positioned are obtained, the environment-influenced road image set matching the current environment data is searched, and the current road image and the environment-influenced road image set are combined
- the environment-affected road images are respectively matched to obtain a target environment-affected road image matched with the current road image, and the current position information of the vehicle to be positioned is determined according to the target environment-affected road image.
- the vehicle positioning is carried out by using high-precision maps made under sunny daytime conditions, ignoring the positioning errors caused by weather and time periods.
- the environmental impact road image set, and the current road image where the vehicle to be positioned is located is matched with the environmental impact road image in the environmental impact road image set, and the target environmental impact road image matched with the current road image is obtained , and then determine the current location information of the vehicle to be positioned according to the target environmental impact road image to fully consider the mapping effects caused by different environmental factors, reduce the positioning error caused by environmental interference, and improve the positioning accuracy of the vehicle under different environmental conditions .
- Fig. 1 is a schematic structural diagram of a vehicle in a hardware operating environment involved in the solution of an embodiment of the present invention
- FIG. 2 is a schematic flowchart of the first embodiment of the vehicle positioning method based on environment matching in the present invention
- FIG. 3 is a schematic flowchart of a second embodiment of the vehicle positioning method based on environment matching in the present invention
- FIG. 4 is a schematic diagram of dual positioning involved in the second embodiment of the vehicle positioning method based on environment matching in the present invention
- FIG. 5 is a schematic flowchart of a third embodiment of the vehicle positioning method based on environment matching in the present invention.
- Fig. 6 is a structural block diagram of the first embodiment of the vehicle positioning device based on environment matching according to the present invention.
- FIG. 1 is a schematic diagram of the vehicle structure of the hardware operating environment involved in the solution of the embodiment of the present invention.
- the vehicle may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), communication bus 1002, user interface 1003, network interface 1004, memory 1005.
- a processor 1001 such as a central processing unit (Central Processing Unit, CPU)
- communication bus 1002 is used to realize connection and communication between these components.
- the user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.
- the network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (WIreless-FIdelity, WI-FI) interface).
- WIreless-FIdelity WI-FI
- Memory 1005 can be a high-speed random access memory (Random Access Memory, RAM), can also be a stable non-volatile memory (Non-Volatile Memory, NVM), such as disk storage.
- RAM Random Access Memory
- NVM Non-Volatile Memory
- the memory 1005 may also be a storage device independent of the aforementioned processor 1001 .
- FIG. 1 does not constitute a limitation to the vehicle, and may include more or less components than those shown in the illustration, or combine some components, or arrange different components.
- the memory 1005 as a storage medium may include an operating system, a data storage module, a network communication module, a user interface module, and a vehicle positioning program based on environment matching.
- the network interface 1004 is mainly used for data communication with the network server;
- the user interface 1003 is mainly used for data interaction with the user;
- the processor 1001 and the memory 1005 in the vehicle of the present invention can be arranged in the vehicle , the vehicle uses the processor 1001 to invoke the environment matching-based vehicle positioning program stored in the memory 1005, and executes the environment matching-based vehicle positioning method provided by the embodiment of the present invention.
- FIG. 2 is a schematic flowchart of a first embodiment of the vehicle positioning method based on environment matching in the present invention.
- the vehicle positioning method based on environment matching includes the following steps:
- Step S10 Obtain the current environment data and the current road image of the location of the vehicle to be positioned;
- the execution subject of this embodiment may be the processor 1001 mentioned above. etc.) to collect the current road image where the vehicle to be positioned is located, wherein the current road image can be understood as the image corresponding to the road where the vehicle to be positioned is currently located. is the image corresponding to the area where the vehicle to be positioned is currently located, where the size of the area can be set according to actual needs, which is not limited in this embodiment.
- the current environmental data of the location of the vehicle to be positioned can also be obtained, the current environmental data includes current weather data and current time period data, which can be obtained through
- the current weather data reflects the current weather conditions of the location of the vehicle to be positioned, such as sunny, cloudy, rainy, snowy, foggy, etc.
- the current time period data reflects the current time period of the location of the vehicle to be positioned , such as early morning, noon, evening, late night, etc.
- Step S20 Finding an image set of environment-impacted roads matching the current environment data
- the environmental impact road image set matching the current environmental data can be searched in the preset road image library, wherein the environmental impact road image set can be understood as including
- the environmental impact road image set can be understood as including
- the preset road image library can be It is understood as a database that stores image sets corresponding to different roads (or different areas) under different environmental influences and is updated in real time.
- Step S30 matching the current road image with the environmental impact road images in the environmental impact road image set to obtain a target environmental impact road image matching the current road image;
- Step S40 Determine the current location information of the vehicle to be positioned according to the target environment affecting road image.
- the current road image of the vehicle to be positioned can be combined with the environmental impact of the environmental impact road image set
- the road images are respectively matched to obtain the target environment-affected road image matched with the current road image, and the current position information of the vehicle to be positioned is determined according to the target environment-affected road image.
- the environmental impact road image set draws a corresponding high-precision map through synchronous positioning and mapping technology, and then performs vehicle positioning based on the obtained high-precision map.
- the target environmental impact road image can be corresponding to the high-precision map
- the location information of the vehicle to be positioned is used as the current location information of the vehicle to be positioned. For example, if the location coordinates corresponding to the target environmental impact road image are (a, b, c), then (a, b, c) is used as the location to be positioned The current location information of the vehicle.
- the current environment data and the current road image of the location of the vehicle to be positioned are acquired, an environment-influenced road image set matching the current environment data is searched, and the current road image and the environment-influenced road image are collected together.
- the environment-affected road images are respectively matched to obtain a target environment-affected road image matched with the current road image, and the current position information of the vehicle to be positioned is determined according to the target environment-affected road image.
- the vehicle positioning is performed through high-precision maps made in sunny daytime conditions, ignoring the positioning errors caused by weather and time periods.
- the current environmental data of the location of the vehicle to be positioned is searched.
- the corresponding environmental impact road image set, and the current road image where the vehicle to be positioned is located is matched with the environmental impact road image in the environmental impact road image set, and the target environmental impact road matched with the current road image is obtained image, and then determine the current location information of the vehicle to be positioned according to the target environment impact road image to fully consider the mapping effects caused by different environmental factors, reduce the positioning error caused by environmental interference, and improve the vehicle positioning under different environmental conditions precision.
- FIG. 3 is a schematic flowchart of a second embodiment of the vehicle positioning method based on environment matching in the present invention.
- the method before the step S20, the method further includes:
- Step S01 Obtain a road image set in a preset environment mode, and perform environmental impact removal processing on the road image set to obtain a basic road image set;
- the image recognition result of the road component elements of a certain road is a street lamp on a dimly lit road, Then the corresponding road feature marks are: evening/late night, street lights, and for example, the image recognition result of the road component elements of a certain road is a warning sign covered by snow, then the corresponding road feature marks are: snow, warning sign;
- the road composition elements can be understood as different elements that make up the road, such as road traffic sign elements (such as warning signs, prohibition signs, guide signs, etc.), road traffic marking elements (such as indicator lines, prohibition signs, etc.), Marking lines, warning marking lines, etc.), elements of traffic facilities (such as traffic lights, street lights, anti-collision barriers, etc.), elements of building facilities (such as residences, schools, hospitals, etc.), etc.
- the label correction information input by the user can also be received, and the image feature label can be added/deleted/modified according to the label correction information; or, the road feature label input by the user can be directly received.
- the road image set can be subjected to an environmental impact removal process according to the road feature label to obtain a basic road image set, wherein the environmental impact process can be understood as Carry out corresponding post-effect processing on the road image sets affected by environmental factors according to the different environmental impacts, and obtain the basic road image sets without environmental impacts.
- the corresponding effect processing plug-ins can be selected according to the different environmental impacts , and then perform corresponding post-effect processing on the road image set through different effect processing plug-ins to obtain the basic road image set.
- the mark for identifying the weather in the road feature mark is: snow
- the corresponding effect processing plug-in can also be called in combination with the mark of the identification element category in the feature mark to perform environmental impact removal processing.
- the road feature mark is: evening/late night, street light, then call and evening/late night and street light
- the corresponding effect processing plug-in, or the effect plug-in corresponding to the element category of evening/late night and street lights ie, traffic facility elements
- the road feature is marked as: snow, warning sign, then the call is related to snow and
- the effect processing plug-in corresponding to the warning sign, or the effect plug-in corresponding to the element category to which the snow and warning signs belong ie, road traffic sign elements).
- the corresponding basic high-precision map can also be drawn through synchronous positioning and mapping technology according to the basic road image set, and then the vehicle can be initially positioned based on the obtained basic high-precision map.
- the environmental impact road image set draws corresponding high-precision maps through simultaneous positioning and mapping technology, and then performs dual positioning based on the obtained basic high-precision maps and high-precision maps to further improve vehicle positioning accuracy and user safety.
- Step S02 Perform injection processing on the basic road images according to the environmental impact feature information corresponding to different environmental impacts, so as to generate environmental impact road image sets under different environmental impacts.
- the weather impact factors and time period impact factors in the environmental feature information corresponding to different environmental impacts can be obtained, wherein the weather impact factors It can be understood as the corresponding image influencing factors under different weather conditions, such as rain, wind, snow, fog, sand, etc., and the time period influencing factors can be understood as corresponding image influencing factors under different periods, such as temperature and humidity, light brightness, etc. , and then, combine the weather influencing factors and time period influencing factors according to the preset combination rules to obtain different environmental composite factors, the preset combination rules can be set according to actual needs, for example, each weather The impact factor is combined with the impact factor of each period, which is not limited in this embodiment.
- the corresponding effect processing plug-ins can be matched according to the environmental compounding factors, and the The effect processing plug-in injects the environmental compounding factors into the basic road image respectively to generate environmental impact road image sets under different environmental influences.
- the environmental compounding factor is a combination of snow and light brightness
- the matching effect processing The plug-in may process the plug-in for effects corresponding to snow and evening/late night.
- the road component elements in the basic road image set can also be obtained, and the basic roads can be calculated according to the environmental composite factors
- the road component elements in the image set are rendered to generate an environmental impact road image set under different environmental impacts.
- the corresponding effect processing plug-in can be matched according to the environmental composite factor, and the road component elements in the basic road image set are respectively rendered through the effect processing plug-in to generate different environmental effects.
- Environmental impact road image set in order to improve the accuracy of the obtained environment-influenced road image sets under different environmental influences, the corresponding effect processing plug-ins can also be matched in combination with road component elements.
- the environmental composite factor is a combination of snow and low light brightness
- the road component elements For anti-collision barriers call the effect processing plug-ins corresponding to snow, evening/late night and anti-collision barriers, and render the anti-collision barriers through the effect processing plug-ins; or call snow, evening/ An effect plug-in corresponding to the element category to which the anti-collision guardrail belongs (that is, the traffic facility element), and renders the anti-collision guardrail through the effect processing plug-in.
- road component elements in the basic road image set are traversed to obtain environmental impact road image sets under different environmental influences.
- a corresponding high-precision map can be drawn through synchronous positioning and mapping technology based on the environmental impact road image set, and then vehicle positioning can be performed based on the obtained high-precision map.
- FIG. 4 is a schematic diagram of dual positioning involved in the second embodiment of the vehicle positioning method based on environment matching in the present invention.
- the environmental impact stripping that is, the above-mentioned environmental impact removal process
- the basic road image set draws the corresponding basic high-precision map through synchronous positioning and mapping technology, and then performs environmental impact injection on the basic high-precision map (that is, the above-mentioned environmental impact feature information corresponding to different environmental impacts is respectively applied to all Based on the above basic road image for injection processing), to generate the environmental impact road image set under different environmental influences, and based on the environmental impact road image set, the corresponding high-precision map is drawn through synchronous positioning and mapping technology, and then combined with the matched current environment
- the high-precision map under the influence and the basic high-precision map perform real-time dual positioning to further improve the vehicle positioning accuracy and the user's riding safety.
- the road image set in the preset environment mode is obtained, and the environmental impact removal process is performed on the road image set to obtain the basic road image set, and the environmental impact characteristic information corresponding to different environmental impacts is respectively processed.
- the base road image is injected to generate a set of environment-affected road images under different environmental influences.
- the basic road image set is obtained by performing environmental impact removal processing on the road image set in the preset environmental mode, and then injecting the basic road image according to the environmental impact feature information corresponding to different environmental impacts to generate different environmental impacts.
- the environmental impact road image set under different environmental impacts in order to improve the accuracy of the obtained environmental impact road image sets under different environmental impacts and the accuracy of the subsequent high-precision maps drawn based on the environmental impact road image sets under different environmental impacts, further, also improve The accuracy of vehicle positioning based on the obtained high-precision map is improved.
- FIG. 5 is a schematic flowchart of a third embodiment of the vehicle positioning method based on environment matching in the present invention.
- the step S20 includes:
- Step S201 Obtain the historical GPS positioning information of the vehicle to be positioned, and determine the corresponding image set of the region according to the historical GPS positioning information;
- Step S202 Searching for an image set of environment-affected roads matching the current environment data in the image set of the region to which it belongs.
- the historical GPS positioning information of the vehicle to be positioned can be obtained first, and the corresponding regional image set is determined according to the historical GPS positioning information.
- the environment-influenced road image set matched with the current environment data. It is easy to understand that during the driving process of the vehicle, there will be situations where it is difficult to locate the vehicle due to weak GPS signals.
- the historical GPS positioning information can be obtained, and the corresponding image set of the corresponding area can be determined according to the historical GPS positioning information.
- the region image set can be understood as different image sets stored in the preset road image library according to different divisions of the region, and the preset road image library can be understood as a real-time updated store with different roads (or different regions) in different areas.
- the area size can be set according to actual requirements, which is not limited in this embodiment.
- what is acquired in this embodiment is not limited to the historical GPS positioning information of the vehicle to be positioned, and may also be inertial navigation positioning information, etc., which is not limited in this embodiment.
- step S40 includes:
- Step S401 Determine the current location information of the vehicle to be positioned according to the historical GPS positioning information and the location information corresponding to the target environment-affected road image.
- the GPS positioning information at the current moment can also be predicted according to the historical GPS positioning information, and then the location information corresponding to the road image can be affected according to the predicted GPS positioning information at the current moment and the target environment Determine the current location information of the vehicle to be positioned.
- the preset error rate is less than or equal to the preset error rate, and when it is less than or equal to the preset error, set the weight corresponding to the GPS positioning information at the current moment of the prediction and the position information corresponding to the target environment affecting the road image in different scenarios , and then determine the current location information of the vehicle to be positioned according to the two and their corresponding weights, wherein the preset error rate can be set according to actual needs, which is not limited in this embodiment.
- a corresponding high-precision map can be drawn through synchronous positioning and mapping technology according to the set of environmental impact road images, and then the corresponding position information of the target environmental impact road image in the high-precision map can be obtained, and Determine the current position information of the vehicle to be positioned according to the corresponding position information of the target environment-affected road image in the high-precision map and the predicted GPS positioning information at the current moment, for example, the target environment-affected road image corresponds to
- the position coordinates are (a, b, c)
- the corresponding weight is 0.7
- the predicted GPS positioning information at the current moment is (d, e, f)
- the corresponding weight is 0.3
- the current position information of the vehicle to be positioned can be is (0.7a+0.3d, 0.7b+0.3e, 0.7c+0.3f).
- the historical GPS positioning information of the vehicle to be positioned is obtained, and the corresponding image set of the area to which it belongs is determined according to the historical GPS positioning information, and the environmental impact road matching the current environmental data is searched in the image set of the belonging area image set.
- the current location information of the vehicle to be positioned is determined according to the historical GPS positioning information and the location information corresponding to the target environmental impact road image.
- the current location information of the vehicle to be positioned is determined by combining the historical GPS positioning information of the vehicle to be positioned and the location information corresponding to the target environment impact road image, so as to reduce the vehicle positioning error as much as possible and improve the positioning accuracy of the vehicle at the same time , providing double protection for vehicle positioning and improving the safety of users.
- the embodiment of the present invention also proposes a storage medium, on which a vehicle positioning program based on environment matching is stored.
- a vehicle positioning program based on environment matching is executed by a processor, the above-mentioned environment-based Steps of a matching vehicle location method.
- FIG. 6 is a structural block diagram of the first embodiment of the vehicle positioning device based on environment matching according to the present invention.
- the vehicle positioning device based on environment matching proposed by the embodiment of the present invention includes:
- the data acquisition module 10 is used to acquire the current environment data and the current road image of the position of the vehicle to be positioned;
- An image set search module 20 configured to search for an environment-affected road image set matching the current environment data
- An image matching module 30, configured to match the current road image with the environment-affected road images in the environment-affected road image set to obtain a target environment-affected road image matched with the current road image;
- the vehicle positioning module 40 is configured to determine the current position information of the vehicle to be positioned according to the target environment affecting road image.
- the current environment data and the current road image of the location of the vehicle to be positioned are acquired, an environment-influenced road image set matching the current environment data is searched, and the current road image and the environment-influenced road image are collected together.
- the environment-affected road images are respectively matched to obtain a target environment-affected road image matched with the current road image, and the current position information of the vehicle to be positioned is determined according to the target environment-affected road image.
- the vehicle positioning is performed through high-precision maps made in sunny daytime conditions, ignoring the positioning errors caused by weather and time periods.
- the current environmental data of the location of the vehicle to be positioned is searched.
- the corresponding environmental impact road image set, and the current road image where the vehicle to be positioned is located is matched with the environmental impact road image in the environmental impact road image set, and the target environmental impact road matched with the current road image is obtained image, and then determine the current location information of the vehicle to be positioned according to the target environment impact road image to fully consider the mapping effects caused by different environmental factors, reduce the positioning error caused by environmental interference, and improve the vehicle positioning under different environmental conditions precision.
- a second embodiment of the vehicle positioning device based on environment matching in the present invention is proposed.
- the data acquisition module 10 is further configured to acquire a road image set in a preset environment mode, and perform environmental impact removal processing on the road image set to obtain a basic road image set;
- the data acquisition module 10 is further configured to perform injection processing on the basic road images according to the environmental impact characteristic information corresponding to different environmental impacts, so as to generate environmental impact road image sets under different environmental impacts.
- the data acquisition module 10 is also used to respectively acquire road image sets under different weather and different time periods, and perform image recognition and feature marks on the road image sets to obtain road feature marks;
- the data acquisition module 10 is further configured to perform environmental impact removal processing on the road image set according to the road feature mark, so as to obtain a basic road image set.
- the data acquisition module 10 is also used to acquire weather impact factors and period impact factors in the environmental feature information corresponding to different environmental impacts;
- the data acquisition module 10 is also used to combine the weather influencing factors and time period influencing factors according to preset combination rules to obtain different environmental composite factors;
- the data acquisition module 10 is further configured to respectively inject the environmental composite factors into the basic road images to generate environmental impact road image sets under different environmental influences.
- the data acquisition module 10 is also used to acquire road component elements in the basic road image set;
- the data acquisition module 10 is further configured to respectively render the road component elements in the basic road image set according to the environmental composite factors, so as to generate environmental impact road image sets under different environmental influences.
- the image set search module 20 is also used to obtain the historical GPS positioning information of the vehicle to be positioned, and determine the corresponding image set of the region according to the historical GPS positioning information;
- the image set search module 20 is further configured to search for an image set of environment-affected roads matching the current environment data in the image set of the region to which it belongs.
- the vehicle positioning module 40 is further configured to determine the current position information of the vehicle to be positioned according to the historical GPS positioning information and the position information corresponding to the target environmental impact road image.
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Abstract
Description
Claims (10)
- 一种基于环境匹配的车辆定位方法,其特征在于,所述基于环境匹配的车辆定位方法包括以下步骤:获取待定位车辆所处位置的当前环境数据以及当前道路图像;查找与所述当前环境数据匹配的环境影响道路图像集;将所述当前道路图像与所述环境影响道路图像集中的环境影响道路图像分别进行匹配,获得与所述当前道路图像匹配的目标环境影响道路图像;根据所述目标环境影响道路图像确定所述待定位车辆的当前位置信息。
- 如权利要求1所述的基于环境匹配的车辆定位方法,其特征在于,所述查找与所述当前环境数据匹配的环境影响道路图像集的步骤之前,还包括:获取预设环境模式下的道路图像集,并对所述道路图像集进行环境影响去除处理,以获得基础道路图像集;根据不同环境影响对应的环境影响特征信息分别对所述基础道路图像进行注入处理,以生成不同环境影响下的环境影响道路图像集。
- 如权利要求2所述的基于环境匹配的车辆定位方法,其特征在于,所述获取预设环境模式下的道路图像集,并对所述道路图像集进行环境影响去除处理,以获得基础道路图像集的步骤,包括:分别获取不同天气和不同时段下的道路图像集,并对所述道路图像集进行图像识别以及特征标记,获得道路特征标记;根据所述道路特征标记对所述道路图像集进行环境影响去除处理,以获得基础道路图像集。
- 如权利要求2所述的基于环境匹配的车辆定位方法,其特征在于,所述根据不同环境影响对应的环境影响特征信息分别对所述基础道路图像进行注入处理,以生成不同环境影响下的环境影响道路图像集的步骤,包括:获取不同环境影响对应的环境特征信息中的天气影响因子和时段影响因子;将所述天气影响因子和时段影响因子按照预设组合规则进行组合,以获得不同的环境复合因子;将所述环境复合因子分别注入至所述基础道路图像,以生成不同环境影响下的环境影响道路图像集。
- 如权利要求4所述的基于环境匹配的车辆定位方法,其特征在于,所述将所述环境复合因子分别注入至所述基础道路图像,以生成不同环境影响下的环境影响道路图像集的步骤,包括:获取所述基础道路图像集中的道路组成元素;根据所述环境复合因子分别对所述基础道路图像集中的所述道路组成元素进行渲染,以生成不同环境影响下的环境影响道路图像集。
- 如权利要求1~5中任一项所述的基于环境匹配的车辆定位方法,其特征在于,所述查找与所述当前环境数据匹配的环境影响道路图像集的步骤,包括:获取待定位车辆的历史GPS定位信息,并根据所述历史GPS定位信息确定对应的所属区域图像集;在所述所属区域图像集中查找与所述当前环境数据匹配的环境影响道路图像集。
- 如权利要求6所述的基于环境匹配的车辆定位方法,其特征在于,所述根据所述目标环境影响道路图像确定所述待定位车辆的当前位置信息的步骤,包括:根据所述历史GPS定位信息和所述目标环境影响道路图像对应的位置信息确定所述待定位车辆的当前位置信息。
- 一种基于环境匹配的车辆定位装置,其特征在于,所述基于环境匹配的车辆定位装置包括:数据获取模块,用于获取待定位车辆所处位置的当前环境数据以及当前道路图像;图像集查找模块,用于查找与所述当前环境数据匹配的环境影响道路图像集;图像匹配模块,用于将所述当前道路图像与所述环境影响道路图像集中的环境影响道路图像分别进行匹配,获得与所述当前道路图像匹配的目标环境影响道路图像;车辆定位模块,用于根据所述目标环境影响道路图像确定所述待定位车辆的当前位置信息。
- 一种车辆,其特征在于,所述车辆包括:存储器、处理器及存储在所述存储器上并可在所述处理器上运行的基于环境匹配的车辆定位程序,所述基于环境匹配的车辆定位程序配置为实现如权利要求1至7中任一项所述的基于环境匹配的车辆定位方法的步骤。
- 一种存储介质,其特征在于,所述存储介质上存储有基于环境匹配的车辆定位程序,所述基于环境匹配的车辆定位程序被处理器执行时实现如权利要求1至7中任一项所述的基于环境匹配的车辆定位方法的步骤。
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PCT/CN2021/113515 WO2023019509A1 (zh) | 2021-08-19 | 2021-08-19 | 基于环境匹配的车辆定位方法、装置、车辆及存储介质 |
EP21953755.2A EP4375856A1 (en) | 2021-08-19 | 2021-08-19 | Environment matching-based vehicle localization method and apparatus, vehicle, and storage medium |
KR1020247003644A KR20240064620A (ko) | 2021-08-19 | 2021-08-19 | 환경 매칭 기반의 차량 위치 측정 방법, 장치, 차량 및 저장 매체 |
CN202180097566.9A CN117256009A (zh) | 2021-08-19 | 2021-08-19 | 基于环境匹配的车辆定位方法、装置、车辆及存储介质 |
US18/429,828 US20240169743A1 (en) | 2021-08-19 | 2024-02-01 | Vehicle positioning method and device based on environment matching, vehicle and storage medium |
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Publication number | Priority date | Publication date | Assignee | Title |
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CN116958084A (zh) * | 2023-07-20 | 2023-10-27 | 上海韦地科技集团有限公司 | 基于核工业大数据的图像智能感知***及方法 |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2574958A1 (en) * | 2011-09-28 | 2013-04-03 | Honda Research Institute Europe GmbH | Road-terrain detection method and system for driver assistance systems |
US20150142248A1 (en) * | 2013-11-20 | 2015-05-21 | Electronics And Telecommunications Research Institute | Apparatus and method for providing location and heading information of autonomous driving vehicle on road within housing complex |
WO2016177372A1 (de) * | 2015-05-06 | 2016-11-10 | Continental Teves Ag & Co. Ohg | Verfahren und vorrichtung zur erkennung und bewertung von umwelteinflüssen und fahrbahnzustandsinformationen im fahrzeugumfeld |
CN107024216A (zh) * | 2017-03-14 | 2017-08-08 | 重庆邮电大学 | 引入全景地图的智能车辆融合定位***及方法 |
CN109446973A (zh) * | 2018-10-24 | 2019-03-08 | 中车株洲电力机车研究所有限公司 | 一种基于深度神经网络图像识别的车辆定位方法 |
CN110657812A (zh) * | 2018-06-29 | 2020-01-07 | 比亚迪股份有限公司 | 车辆定位方法、装置及车辆 |
CN111351493A (zh) * | 2018-12-24 | 2020-06-30 | 上海欧菲智能车联科技有限公司 | 一种定位方法和*** |
CN111508258A (zh) * | 2020-04-17 | 2020-08-07 | 北京三快在线科技有限公司 | 一种定位方法及装置 |
-
2021
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- 2021-08-19 CN CN202180097566.9A patent/CN117256009A/zh active Pending
- 2021-08-19 KR KR1020247003644A patent/KR20240064620A/ko unknown
- 2021-08-19 EP EP21953755.2A patent/EP4375856A1/en active Pending
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Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2574958A1 (en) * | 2011-09-28 | 2013-04-03 | Honda Research Institute Europe GmbH | Road-terrain detection method and system for driver assistance systems |
US20150142248A1 (en) * | 2013-11-20 | 2015-05-21 | Electronics And Telecommunications Research Institute | Apparatus and method for providing location and heading information of autonomous driving vehicle on road within housing complex |
WO2016177372A1 (de) * | 2015-05-06 | 2016-11-10 | Continental Teves Ag & Co. Ohg | Verfahren und vorrichtung zur erkennung und bewertung von umwelteinflüssen und fahrbahnzustandsinformationen im fahrzeugumfeld |
CN107024216A (zh) * | 2017-03-14 | 2017-08-08 | 重庆邮电大学 | 引入全景地图的智能车辆融合定位***及方法 |
CN110657812A (zh) * | 2018-06-29 | 2020-01-07 | 比亚迪股份有限公司 | 车辆定位方法、装置及车辆 |
CN109446973A (zh) * | 2018-10-24 | 2019-03-08 | 中车株洲电力机车研究所有限公司 | 一种基于深度神经网络图像识别的车辆定位方法 |
CN111351493A (zh) * | 2018-12-24 | 2020-06-30 | 上海欧菲智能车联科技有限公司 | 一种定位方法和*** |
CN111508258A (zh) * | 2020-04-17 | 2020-08-07 | 北京三快在线科技有限公司 | 一种定位方法及装置 |
Cited By (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116958084A (zh) * | 2023-07-20 | 2023-10-27 | 上海韦地科技集团有限公司 | 基于核工业大数据的图像智能感知***及方法 |
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