CN115097487A - Vehicle environment information generation method and device, electronic device and storage medium - Google Patents

Vehicle environment information generation method and device, electronic device and storage medium Download PDF

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Publication number
CN115097487A
CN115097487A CN202210827360.3A CN202210827360A CN115097487A CN 115097487 A CN115097487 A CN 115097487A CN 202210827360 A CN202210827360 A CN 202210827360A CN 115097487 A CN115097487 A CN 115097487A
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Prior art keywords
point cloud
information
cloud information
meets
coordinate
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Chinese (zh)
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黄城
任凡
文滔
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Chongqing Changan Automobile Co Ltd
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Chongqing Changan Automobile Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/487—Extracting wanted echo signals, e.g. pulse detection
    • G01S7/4876—Extracting wanted echo signals, e.g. pulse detection by removing unwanted signals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/491—Details of non-pulse systems
    • G01S7/493—Extracting wanted echo signals

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Electromagnetism (AREA)
  • Traffic Control Systems (AREA)

Abstract

The present application relates to the field of vehicle technologies, and in particular, to a method, an apparatus, an electronic device, and a storage medium for generating environmental information of a vehicle, where the method includes: scanning a target environment position based on a laser radar, and obtaining original point cloud information according to a scanning result; carrying out down-sampling processing on the original point cloud information to obtain filtered point cloud information; and cutting the filtered point cloud information by combining with the road structure size information to obtain target point cloud information, and generating real-time environment information according to the target point cloud information. Therefore, the problems of redundant point cloud data, low effective area extraction efficiency, poor real-time performance and the like existing in data processing of the laser radar are solved, the requirement of completely keeping key space structure information such as barriers and the like while effectively removing redundant point cloud information can be met, environmental information can be accurately obtained in real time in an actual driving scene, and timely and effective input is provided for decision planning.

Description

Vehicle environment information generation method and device, electronic device and storage medium
Technical Field
The present disclosure relates to the field of vehicle technologies, and in particular, to a method and an apparatus for generating environmental information of a vehicle, an electronic device, and a storage medium.
Background
Environmental perception is the first link of automatic driving, and laser radar is the first choice hardware of environmental perception scheme as important automatic driving car environmental perception sensor always. Because the laser radar point cloud information is rich but the data volume is large, how to complete the high-efficiency processing of the point cloud under the premise of ensuring that the environmental information contained in the original point cloud is not influenced is very important.
In the related art, the advantages of the laser radar in the aspects of data acquisition and environmental adaptability are gradually highlighted, and a plurality of environment perception schemes based on the laser radar are provided, for example, ground and obstacle segmentation is carried out on three-dimensional laser radar data by utilizing a local concave-convex criterion, so that a better effect can be obtained.
However, the data processing of the laser radar has the problems of redundant point cloud data, low extraction efficiency of effective areas, long calculation time, low instantaneity and the like.
Disclosure of Invention
The application provides a vehicle environment information generation method and device, electronic equipment and a storage medium, aims to solve the problems of redundant point cloud data, low effective area extraction efficiency, poor real-time performance and the like existing in data processing of a laser radar, can meet the requirement that key space structure information such as obstacles and the like is completely reserved while redundant point cloud information is effectively removed, can accurately obtain environment information in real time in an actual driving scene, and provides timely and effective input for decision planning.
An embodiment of a first aspect of the present application provides a method for generating environmental information of a vehicle, including the following steps: scanning the position of a target environment based on a laser radar, and obtaining original point cloud information according to a scanning result; carrying out down-sampling processing on the original point cloud information to obtain filtered point cloud information; and cutting the filtering point cloud information by combining with the road structure size information to obtain target point cloud information, and generating real-time environment information according to the target point cloud information.
According to the technical means, the problems that redundant point cloud data exist in data processing of the laser radar, effective area extraction efficiency is low, real-time performance is poor and the like can be solved, the condition that key space structure information such as barriers and the like is completely reserved while redundant point cloud information is effectively removed can be met, environmental information can be accurately obtained in real time in an actual driving scene, and timely and effective input is provided for decision planning.
Optionally, in some embodiments, the clipping the filtered point cloud information in combination with the road structure size information to obtain target point cloud information includes: judging whether the coordinate information of the point cloud data in the filtered point cloud information meets a preset condition or not; and if the coordinate information meets the preset condition, obtaining the target point cloud information according to the point cloud data meeting the preset condition.
According to the technical means, the original point cloud is down-sampled based on the voxelization grid method, and point cloud cutting is performed by combining the road structure size, so that the data volume is reduced, and the algorithm efficiency is improved.
Optionally, in some embodiments, the determining whether the coordinate information of the point cloud data in the filtered point cloud information satisfies a preset condition includes: judging whether the abscissa of the point cloud data in the filtered point cloud information meets the condition of a transverse threshold; judging whether the vertical coordinate of the point cloud data in the filtered point cloud information meets a vertical threshold condition or not, and judging whether the height value of the point cloud data in the filtered point cloud information meets a height threshold condition or not; and if the horizontal coordinate meets the horizontal threshold condition, the vertical coordinate meets the vertical threshold condition and the height value meets the height threshold condition, judging that the coordinate information of the point cloud data in the filtered point cloud information meets the preset condition.
According to the technical means, redundant point cloud data can be reduced while the shape characteristics and the spatial structure information contained in the original point cloud are guaranteed, the calculation efficiency is improved, and the method and the device have important significance for improving the efficiency of an environment perception link of an automatic driving vehicle and providing key information for driving behavior decision.
Optionally, in some embodiments, the method for generating environmental information of a vehicle further includes: and if the horizontal coordinate does not meet the horizontal threshold condition, or the vertical coordinate does not meet the longitudinal threshold condition, or the height value does not meet the height threshold condition, judging that the coordinate information of the point cloud data in the filtered point cloud information does not meet the preset condition.
According to the technical means, redundant point cloud data can be reduced through the preset threshold value, the calculation efficiency is improved, and the method and the device have important significance for improving the efficiency of the environment perception link of the automatic driving vehicle and providing key information for driving behavior decision.
Optionally, in some embodiments, the downsampling the original point cloud information includes: and filtering the original point cloud information through a preset three-dimensional voxel grid to obtain the filtered point cloud information.
According to the technical means, the original point cloud is down-sampled based on the voxelization grid method, and point cloud cutting is performed by combining the road structure size, so that the data volume is reduced, and the algorithm efficiency is improved.
An embodiment of a second aspect of the present application provides an environmental information generating apparatus for a vehicle, including: the acquisition module is used for scanning the position of a target environment based on a laser radar and obtaining original point cloud information according to a scanning result; the processing module is used for carrying out down-sampling processing on the original point cloud information to obtain filtered point cloud information; and the generating module is used for cutting the filtering point cloud information by combining with the road structure size information to obtain target point cloud information and generating real-time environment information according to the target point cloud information.
Optionally, in some embodiments, the generating module further includes: the judging module is used for judging whether the coordinate information of the point cloud data in the filtering point cloud information meets a preset condition or not; and the judging module is used for judging whether the coordinate information meets the preset condition or not, and obtaining the target point cloud information according to the point cloud data meeting the preset condition.
Optionally, in some embodiments, the determining module further includes: the first judgment unit is used for judging whether the abscissa of the point cloud data in the filtered point cloud information meets the condition of a transverse threshold value; the second judging unit is used for judging whether the vertical coordinate of the point cloud data in the filtered point cloud information meets a vertical threshold condition or not; the third judgment unit is used for judging whether the height value of the point cloud data in the filtered point cloud information meets the height threshold value condition or not; a first determination unit, configured to determine that the coordinate information of the point cloud data in the filtered point cloud information satisfies the preset condition if the abscissa satisfies the transverse threshold condition, the ordinate satisfies the longitudinal threshold condition, and the height value satisfies the height threshold condition.
Optionally, in some embodiments, the above-mentioned environmental information generating apparatus for a vehicle further includes:
a second determining unit, configured to determine that the coordinate information of the point cloud data in the filtered point cloud information does not satisfy the preset condition if the abscissa does not satisfy the transverse threshold condition, or the ordinate does not satisfy the longitudinal threshold condition, or the height value does not satisfy the height threshold condition.
Optionally, in some embodiments, the processing module includes: and the filtering unit is used for filtering the original point cloud information through a preset three-dimensional voxel grid to obtain the filtered point cloud information.
An embodiment of a third aspect of the present application provides an electronic device, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the environmental information generating method of the vehicle as described in the above embodiments.
A fourth aspect of the present application provides a computer-readable storage medium having stored thereon a computer program, which is executed by a processor, for implementing the environmental information generation method of a vehicle as described in the above embodiments.
Therefore, based on analysis of an environment perception target, the original point cloud data is firstly sampled by a voxelization grid method, then point cloud cutting is carried out by taking the structure size of a common road as a reference to obtain an interested area, point cloud information irrelevant to the concerned target is removed, the point cloud information is further reduced, and finally the data acquired by a radar after the down sampling and cutting are segmented by a RANdom SAmple Consensus (RANSAC) algorithm, so that the separation of the point cloud information of the road surface from a marker and an obstacle with elevation information is realized, the algorithm performance is further improved on the premise of providing accurate perception information for decision planning of autonomous driving behaviors of vehicles, and the calculation time is shortened. Therefore, the problems of redundant point cloud data, low effective area extraction efficiency, poor real-time performance and the like in data processing of the laser radar are solved, the requirement of completely retaining key space structure information such as obstacles and the like while effectively removing redundant point cloud information can be met, environmental information can be accurately obtained in real time in an actual driving scene, and timely and effective input is provided for decision planning.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The foregoing and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a flowchart of an environmental information generation method of a vehicle according to an embodiment of the present application;
FIG. 2 is a schematic diagram illustrating an overall architecture of a method for generating environmental information of a vehicle according to an embodiment of the present application;
FIG. 3 is a flow chart of a method for generating environmental information of a vehicle according to an embodiment of the present application;
fig. 4 is a block diagram schematically illustrating an environment information generating apparatus of a vehicle according to an embodiment of the present application;
fig. 5 is a schematic diagram of an electronic device provided according to an embodiment of the present application.
The system comprises 10-a vehicle environment information generation device, 100-an acquisition module, 200-a processing module and 300-a generation module.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative and intended to explain the present application and should not be construed as limiting the present application.
A method, an apparatus, an electronic device, and a storage medium for generating environmental information of a vehicle according to an embodiment of the present application are described below with reference to the drawings. Aiming at the problems of redundant point cloud data, low effective area extraction efficiency, poor real-time performance and the like of data processing of a laser radar in the background technology, the application provides a vehicle environment information generation method, in the method, original point cloud data is firstly down-sampled by a voxelization grid method based on analysis of an environment perception target, then point cloud cutting is carried out by taking the general road structure size as a reference to obtain an interested area, point cloud information irrelevant to a concerned target is removed, point cloud information is further reduced, finally down-sampled and cut data collected by the radar are segmented by a random sampling consistency algorithm, separation of pavement point cloud information and a marker with elevation information and an obstacle is realized, and the algorithm performance is further improved on the premise of providing accurate perception information for autonomous driving behavior decision planning of a vehicle, the calculation time length is reduced. Therefore, the problems of redundant point cloud data, low effective area extraction efficiency, poor real-time performance and the like in data processing of the laser radar are solved, the requirement of completely retaining key space structure information such as obstacles and the like while effectively removing redundant point cloud information can be met, environmental information can be accurately obtained in real time in an actual driving scene, and timely and effective input is provided for decision planning.
Specifically, fig. 1 is a schematic flowchart of a method for generating environmental information of a vehicle according to an embodiment of the present application.
As shown in fig. 1, the environmental information generating method of a vehicle includes the steps of:
in step S101, a target environment position is scanned based on the laser radar, and original point cloud information is obtained according to a scanning result.
The laser radar can be a multi-line laser radar and is used for collecting original point cloud information in an actual driving scene.
Specifically, the laser radar can be scanned after being installed and calibrated, and point cloud information can be obtained according to a scanning result.
In step S102, down-sampling processing is performed on the original point cloud information to obtain filtered point cloud information.
Optionally, in some embodiments, the down-sampling processing is performed on the original point cloud information, and includes: and filtering the original point cloud information through a preset three-dimensional voxel grid to obtain filtered point cloud information.
The downsampling processing can be based on filtering of original point cloud data collected by the laser radar based on a voxelization grid processing method.
Specifically, after the original point cloud information is obtained through laser radar scanning, voxel down-sampling is performed on the original point cloud information, namely the original point cloud information is filtered through a three-dimensional voxel grid, so that filtered point cloud information is obtained, and the point cloud density is reduced.
In step S103, the filtered point cloud information is clipped according to the road structure size information to obtain target point cloud information, and real-time environment information is generated according to the target point cloud information.
It can be understood that the point cloud information after the density is reduced is cut by combining with the general road structure size information, only the point cloud information in the region of interest with reference value is reserved, and redundant point cloud data on two sides of the road are deleted, so that the calculation amount can be reduced, and the algorithm efficiency is improved.
Optionally, in some embodiments, clipping the filtered point cloud information in combination with the road structure size information to obtain target point cloud information includes: judging whether the coordinate information of the point cloud data in the filtered point cloud information meets a preset condition or not; and if the coordinate information meets the preset condition, obtaining target point cloud information according to the point cloud data meeting the preset condition.
Optionally, in some embodiments, the determining whether the coordinate information of the point cloud data in the filtered point cloud information satisfies a preset condition includes: judging whether the abscissa of the point cloud data in the filtered point cloud information meets the transverse threshold condition; judging whether the vertical coordinate of the point cloud data in the filtered point cloud information meets a vertical threshold condition or not, and judging whether the height value of the point cloud data in the filtered point cloud information meets a height threshold condition or not; and if the horizontal coordinate meets the horizontal threshold condition, the vertical coordinate meets the vertical threshold condition and the height value meets the height threshold condition, judging that the coordinate information of the point cloud data in the filtered point cloud information meets the preset condition.
Optionally, in some embodiments, the method for generating environmental information of a vehicle further includes: and if the horizontal coordinate does not meet the horizontal threshold condition, or the vertical coordinate does not meet the vertical threshold condition, or the height value does not meet the height threshold condition, judging that the coordinate information of the point cloud data in the filtered point cloud information does not meet the preset condition.
Specifically, in the embodiment of the application, it is determined, in combination with road structure size information, whether an abscissa, an ordinate, and a height value of a specific point included in filtered point cloud information are within a specified horizontal threshold range, a specified longitudinal threshold range, and a specified height threshold range of an area of interest, if so, target point cloud information is retained, otherwise, point cloud information is removed, so that clipped point cloud information is obtained, and a random sampling consistency algorithm (RANSAC) is used to identify a road point cloud on the basis of given point cloud information, so as to implement segmentation of road information, and only obstacle information with height in a lane is retained.
In order to enable those skilled in the art to further understand the method for generating environmental information of a vehicle according to the embodiment of the present application, the following detailed description is provided with reference to specific embodiments.
As shown in fig. 2, fig. 2 is an overall architecture diagram of an environmental information generation method for a vehicle according to an embodiment of the present application, including: the system comprises a laser radar (1), a down-sampling module (2), a point cloud cutting module (3) and a road surface point cloud segmentation module (4).
The down-sampling module (2) carries out voxel down-sampling on original point cloud information acquired by the laser radar (1), meanwhile, the point cloud cutting module (3) further carries out point cloud cutting according to the road structure size on a processing result of the down-sampling module (2) to obtain effective point cloud data with reduced calculated amount, then the road surface point cloud segmentation module (4) further removes road surface point clouds which do not participate in obstacle clustering based on the point cloud information obtained by processing, and the further simplified point cloud data are used as the input of target identification.
Fig. 3 is a flowchart of a method for generating environmental information of a vehicle according to an embodiment of the present application.
S301, scanning to obtain original point cloud information after the laser radar is installed and calibrated.
S302, the down-sampling module carries out voxel down-sampling on the collected point cloud information, three-dimensional voxel grid processing is carried out to obtain filtered point cloud, and the density of the point cloud is reduced.
And S303, the point cloud cutting module cuts the point cloud information with the reduced density by combining with the general road structure size information, only the point cloud information in the region of interest with the reference value is reserved, redundant point cloud data on two sides of the road are deleted, the calculated amount is reduced, and the algorithm efficiency is improved.
S304, judging whether the transverse coordinate is in the transverse threshold range of the region of interest, if so, executing the step S305, otherwise, skipping to execute the step S308.
S305, judging whether the longitudinal coordinate is in the range of the longitudinal threshold of the region of interest, if so, executing the step S306, otherwise, skipping to execute the step S308.
S306, judging whether the height value is in the threshold range of the height value of the region of interest, if so, executing the step S307, otherwise, skipping to execute the step S308.
And S307, the road surface segmentation module identifies the road surface point cloud on the basis of the point cloud information given by the point cloud cutting module through a random sampling consistency algorithm, so that the road surface information is segmented, and only the high obstacle information in the lane is reserved.
According to the method for generating the environmental information of the vehicle, based on analysis of an environmental perception target, original point cloud data are firstly subjected to down-sampling through a voxelization grid method, then point cloud cutting is carried out on the basis of the structure size of a general road to obtain an area of interest, point cloud information irrelevant to a target of interest is removed, the point cloud information is further reduced, finally, the data acquired by a radar after down-sampling and cutting are segmented through a random sampling consistency algorithm, separation of the point cloud information of the road surface and a marker and an obstacle with elevation information is achieved, algorithm performance is further improved on the premise that accurate perception information is provided for autonomous driving behavior decision planning of the vehicle, and calculation duration is reduced. Therefore, the problems of redundant point cloud data, low effective area extraction efficiency, poor real-time performance and the like existing in data processing of the laser radar are solved, the requirement of completely keeping key space structure information such as barriers and the like while effectively removing redundant point cloud information can be met, environmental information can be accurately obtained in real time in an actual driving scene, and timely and effective input is provided for decision planning.
Next, an environmental information generation device of a vehicle proposed according to an embodiment of the present application is described with reference to the drawings.
Fig. 4 is a block diagram schematically illustrating an environmental information generating apparatus of a vehicle according to an embodiment of the present application.
As shown in fig. 4, the environmental information generation device 10 for a vehicle includes: an acquisition module 100, a processing module 200 and a generation module 300.
The acquisition module 100 scans the environmental position of a target based on a laser radar and obtains original point cloud information according to a scanning result; the processing module 200 is configured to perform downsampling processing on the original point cloud information to obtain filtered point cloud information; and a generating module 300, configured to crop the filtered point cloud information in combination with the road structure size information to obtain target point cloud information, and generate real-time environment information according to the target point cloud information.
Optionally, in some embodiments, the generating module 300 further includes: the judging module is used for judging whether the coordinate information of the point cloud data in the filtered point cloud information meets a preset condition or not; and the judging module is used for judging whether the coordinate information meets the preset condition or not, and obtaining target point cloud information according to the point cloud data meeting the preset condition.
Optionally, in some embodiments, the determining module further includes: the first judgment unit is used for judging whether the horizontal coordinate of the point cloud data in the filtered point cloud information meets the horizontal threshold condition; the second judgment unit is used for judging whether the vertical coordinate of the point cloud data in the filtered point cloud information meets the vertical threshold condition or not; the third judgment unit is used for judging whether the height value of the point cloud data in the filtered point cloud information meets the height threshold value condition or not; the first judging unit is used for judging that the coordinate information of the point cloud data in the filtered point cloud information meets the preset condition if the horizontal coordinate meets the horizontal threshold condition, the vertical coordinate meets the vertical threshold condition and the height value meets the height threshold condition.
Optionally, in some embodiments, the above-mentioned environment information generating apparatus 10 of a vehicle further includes:
and the second judgment unit is used for judging that the coordinate information of the point cloud data in the filtered point cloud information does not meet the preset condition if the horizontal coordinate does not meet the horizontal threshold condition, or the vertical coordinate does not meet the vertical threshold condition, or the height value does not meet the height threshold condition.
Optionally, in some embodiments, the processing module 200 includes: and the filtering unit is used for filtering the original point cloud information through a preset three-dimensional voxel grid to obtain filtered point cloud information.
It should be noted that the foregoing explanation of the embodiment of the method for generating environmental information of a vehicle is also applicable to the apparatus for generating environmental information of a vehicle according to this embodiment, and will not be repeated herein.
According to the vehicle environment information generation device provided by the embodiment of the application, original point cloud data are firstly subjected to down-sampling through a voxelization grid method based on analysis of an environment perception target, then point cloud cutting is carried out on the basis of the structure size of a general road to obtain an interested area, point cloud information irrelevant to a concerned target is removed, the point cloud information is further reduced, finally, the data acquired by a radar after down-sampling and cutting are segmented through a random sampling consistency algorithm, separation of road surface point cloud information and a marker with elevation information and an obstacle is realized, the algorithm performance is further improved on the premise of providing accurate perception information for autonomous driving behavior decision planning of a vehicle, and the calculation time length is reduced. Therefore, the problems of redundant point cloud data, low effective area extraction efficiency, poor real-time performance and the like in data processing of the laser radar are solved, the requirement of completely retaining key space structure information such as obstacles and the like while effectively removing redundant point cloud information can be met, environmental information can be accurately obtained in real time in an actual driving scene, and timely and effective input is provided for decision planning.
Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
a memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.
The processor 502 implements the environmental information generation method of the vehicle provided in the above-described embodiments when executing the program.
Further, the electronic device further includes:
a communication interface 503 for communication between the memory 501 and the processor 502.
A memory 501 for storing computer programs that can be run on the processor 502.
The memory 501 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
If the memory 501, the processor 502 and the communication interface 503 are implemented independently, the communication interface 503, the memory 501 and the processor 502 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
Optionally, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a chip, the memory 501, the processor 502, and the communication interface 503 may complete communication with each other through an internal interface.
The processor 502 may be a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement embodiments of the present Application.
Embodiments of the present application also provide a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the environmental information generation method of the vehicle as above.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of implementing the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.

Claims (10)

1. A method of generating environmental information of a vehicle, characterized by comprising the steps of:
scanning a target environment position based on a laser radar, and obtaining original point cloud information according to a scanning result;
carrying out down-sampling processing on the original point cloud information to obtain filtered point cloud information; and
and cutting the filtering point cloud information by combining with the road structure size information to obtain target point cloud information, and generating real-time environment information according to the target point cloud information.
2. The method of claim 1, wherein the cropping the filtered point cloud information in combination with road structure size information to obtain target point cloud information comprises:
judging whether the coordinate information of the point cloud data in the filtered point cloud information meets a preset condition or not;
and if the coordinate information meets the preset condition, obtaining the target point cloud information according to the point cloud data meeting the preset condition.
3. The method of claim 2, wherein the determining whether the coordinate information of the point cloud data in the filtered point cloud information satisfies a preset condition comprises:
judging whether the abscissa of the point cloud data in the filtered point cloud information meets the condition of a transverse threshold;
judging whether the vertical coordinate of the point cloud data in the filtering point cloud information meets the vertical threshold condition or not;
judging whether the height value of the point cloud data in the filtering point cloud information meets a height threshold condition or not;
and if the horizontal coordinate meets the horizontal threshold condition, the vertical coordinate meets the vertical threshold condition and the height value meets the height threshold condition, judging that the coordinate information of the point cloud data in the filtered point cloud information meets the preset condition.
4. The method of claim 3, further comprising:
and if the horizontal coordinate does not meet the horizontal threshold condition, or the vertical coordinate does not meet the longitudinal threshold condition, or the height value does not meet the height threshold condition, judging that the coordinate information of the point cloud data in the filtered point cloud information does not meet the preset condition.
5. The method of claim 1, wherein the down-sampling the original point cloud information comprises:
and filtering the original point cloud information through a preset three-dimensional voxel grid to obtain the filtered point cloud information.
6. An environmental information generation device for a vehicle, comprising:
the acquisition module is used for scanning the position of a target environment based on a laser radar and obtaining original point cloud information according to a scanning result;
the processing module is used for carrying out downsampling processing on the original point cloud information to obtain filtered point cloud information; and
and the generating module is used for cutting the filtering point cloud information by combining with the road structure size information to obtain target point cloud information and generating real-time environment information according to the target point cloud information.
7. The apparatus of claim 6, wherein the generating module further comprises:
the judging module is used for judging whether the coordinate information of the point cloud data in the filtered point cloud information meets a preset condition or not;
and the judging module is used for judging that the target point cloud information is obtained according to the point cloud data meeting the preset condition if the coordinate information meets the preset condition.
8. The apparatus of claim 7, wherein the determining module further comprises:
the first judgment unit is used for judging whether the horizontal coordinate of the point cloud data in the filtered point cloud information meets the horizontal threshold condition;
the second judging unit is used for judging whether the vertical coordinate of the point cloud data in the filtered point cloud information meets the vertical threshold condition or not;
the third judgment unit is used for judging whether the height value of the point cloud data in the filtered point cloud information meets the height threshold value condition or not;
and the judging unit is used for judging that the coordinate information of the point cloud data in the filtered point cloud information meets the preset condition if the horizontal coordinate meets the horizontal threshold condition, the vertical coordinate meets the vertical threshold condition and the height value meets the height threshold condition.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the environmental information generation method of a vehicle according to any one of claims 1 to 5.
10. A computer-readable storage medium on which a computer program is stored, characterized in that the program is executed by a processor for implementing the environmental information generation method of a vehicle according to any one of claims 1 to 5.
CN202210827360.3A 2022-07-13 2022-07-13 Vehicle environment information generation method and device, electronic device and storage medium Pending CN115097487A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202210827360.3A CN115097487A (en) 2022-07-13 2022-07-13 Vehicle environment information generation method and device, electronic device and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202210827360.3A CN115097487A (en) 2022-07-13 2022-07-13 Vehicle environment information generation method and device, electronic device and storage medium

Publications (1)

Publication Number Publication Date
CN115097487A true CN115097487A (en) 2022-09-23

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Country Status (1)

Country Link
CN (1) CN115097487A (en)

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