Lane positioning system and method based on vehicle-infrastructure collaborative awareness

Abstract

The invention relates to the technical field of intelligent traffic, in particular to a lane positioning system and method for vehicle-road collaborative awareness, which comprises a data collection module, a data transmission module, a storage library module, a central processing module and an instruction output module, and is characterized in that the data collection module is in control connection with the data transmission module, and the data transmission module is in control connection with a preprocessing module; the automatic driving module assists the vehicle in automatic driving according to the positioned data, the system and the automatic driving function are linked, and convenience and reliability are achieved; the system runs safely and stably in the system normal monitoring module, and an offset correction system is used in the lane offset correction module to correct lane offset, so that lane offset early warning and automatic correction are realized, and potential safety hazards are eliminated; after offset correction in the repeated positioning module, confirmation is carried out again, and result elimination early warning is fed back in the system feedback module; the system locates a lane by means of a sensor and a camera, can be used in a place which cannot be covered by a positioning system, and has very high environmental adaptability.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and specifically to a lane positioning system and method for vehicle-road collaborative perception. Background Art

[0002] At present, the lane positioning system of vehicle-road cooperative perception is very popular in automobile applications and has become the preferred option for many people; the lane positioning system of vehicle-road cooperative perception vehicle-road cooperative technology can monitor key information such as road conditions, traffic flow, weather changes in real time, and transmit this data to the vehicle in a timely manner, helping drivers to predict risks in advance and avoid accidents; through vehicle-road collaboration, traffic management departments can grasp traffic conditions more accurately and realize intelligent control of traffic signals; but the current lane positioning system of vehicle-road cooperative perception still has very obvious defects: first, there is no linkage with the field of autonomous driving; second, the lane positioning system of vehicle-road cooperative perception lacks lane deviation warning and automatic correction, which poses a safety hazard; the lane positioning system of vehicle-road cooperative perception cannot be used in some places that the navigation positioning system cannot cover, and it relies too much on navigation positioning; therefore, it is necessary to design a lane positioning system and method for vehicle-road cooperative perception. Summary of the Invention

[0003] The purpose of the present invention is to provide a lane positioning system and method for vehicle-road collaborative perception, so as to solve the technical problem in the prior art that the lane positioning system for vehicle-road collaborative perception is too dependent on navigation positioning.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a lane positioning system for vehicle-road cooperative perception, comprising: a data collection module, the data collection module being controllably connected to a data transmission module, the data transmission module being controllably connected to a preprocessing module, the preprocessing module being controllably connected to a central processing module, the central processing module being controllably connected to an instruction output module and a storage library module; The instruction output module includes an instruction receiving module, which is connected to the central processing module, and the instruction receiving module is respectively connected to the automatic driving module and the lane deviation correction module, the automatic driving module is connected to the system normal detection module, and the lane deviation correction module is sequentially connected to the repeated positioning module and the system feedback module.

[0005] Preferably, the preprocessing module includes: A data receiving module, used for receiving data from the data transmission module; A numerical processing module is used to obtain numerical data of the data in the data receiving module; Data cleaning module, used for data cleaning of numerical data; A graphics processing module, used for acquiring the graphics data from the data receiving module; Denoising algorithm module, used to perform denoising on graphic data; A data format conversion module is used to convert the denoised graphic data and cleaned numerical data to obtain numerical data and graphic data in a unified format; A data standardization module is used to standardize numerical data and graphic data in a unified format to obtain standardized numerical data and graphic data; A data fusion module is used to fuse standardized numerical data and graphic data to obtain fused data; The feature extraction module is used to extract feature information related to lane positioning from the fused data and transmit the feature information and fused data to the central processing module.

[0006] Preferably, the central processing module includes: The lane positioning algorithm module is used to receive the data transmitted by the preprocessing module and use the lane positioning algorithm to detect the lane line and determine the current lane position of the vehicle; The lane positioning result module is used to obtain the lane position determined by the lane positioning algorithm module and output the lane position; The lane departure warning module is used to determine whether the lane has been crossed based on the lane position, generate instructions based on the judgment result, transmit the instructions to the instruction receiving module, and transmit the judgment result to the storage module.

[0007] Preferably, the data collection module includes: Device deployment module, used to deploy sensors and cameras; The device initialization module is used to initialize the deployed sensors and cameras; The vehicle data acquisition module is used to obtain the graphic data around the vehicle in real time and transmit the graphic data to the data transmission module; The roadside data acquisition module is used to obtain numerical data of current road and traffic conditions in real time and transmit the numerical data to the data transmission module.

[0008] Preferably, it also includes an equipment maintenance module, which includes a regular maintenance module, which is respectively connected to a fault repair module and a special maintenance module; the fault repair module and the special maintenance module are both connected to a feedback execution module; the regular maintenance module and the feedback execution module are connected to the central processing module.

[0009] A second aspect of the present invention provides a lane positioning method for vehicle-road collaborative perception, which is implemented based on any of the lane positioning systems described above and includes the following steps: The data collection module acquires the graphic data around the vehicle and the numerical data of the current road and traffic conditions in real time, and transmits them to the preprocessing module through the data transmission module for preprocessing to obtain feature information and fusion data; The central processing module determines the vehicle's current lane position based on the feature information and fused data, and determines whether it has crossed the lane line based on the lane position. The judgment result is transmitted to the storage module for storage and generates instructions based on the judgment result. The autonomous driving module performs autonomous driving based on feature information and fusion data, and the lane deviation correction module corrects lane deviation according to instructions generated by the central processing module.

[0010] Preferably, the data collection module includes: a device deployment module, a device initialization module, a vehicle data collection module, and a roadside data collection module. The data collection module acquires graphical data around the vehicle and numerical data of current road and traffic conditions in real time, specifically including: The vehicle data acquisition module acquires the graphic data around the vehicle in real time, and the roadside data acquisition module acquires the numerical data of the current road and traffic conditions in real time. The graphic data and numerical data are transmitted to the data transmission module.

[0011] Preferably, the preprocessing module includes: a data receiving module, a numerical processing module, a graphic processing module, a data cleaning module, a denoising algorithm module and a data format conversion module, and the preprocessing to obtain feature information and fusion data includes: The data receiving module receives data from the data transmission module. The numerical processing module and the graphic processing module classify the data in the data receiving module and then receive numerical data and graphic data respectively. The data cleaning module cleans the numerical data output by the numerical processing module. The denoising algorithm module denoises the graphic data output by the graphic processing module. The data format conversion module converts the denoised graphic data and the cleaned numerical data to obtain numerical data and graphic data in a unified format. The data standardization module standardizes the numerical data and graphic data in a unified format to obtain standardized numerical data and graphic data. The data fusion module fuses the standardized numerical data and graphic data to obtain fused data. The feature extraction module extracts feature information related to lane positioning from the fused data and transmits the feature information and fused data to the central processing module.

[0012] Preferably, it also includes equipment maintenance steps, specifically, regularly maintaining equipment in the regular maintenance module in the equipment maintenance module, repairing faulty equipment in the fault repair module, performing special maintenance on equipment in the special maintenance module, and reporting maintenance status to the central processing module in the feedback execution module.

[0013] A third aspect of the present invention provides an automobile, characterized in that it includes a lane positioning system for vehicle-road collaborative perception as described in any one of the above.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: The lane positioning system of vehicle-road cooperative perception disclosed in the present application receives instructions in the instruction receiving module, performs automatic driving according to the positioning data in the automatic driving module, can be linked with the automatic driving function, and is convenient and reliable; the system runs safely and smoothly in the system normal monitoring module, and uses the offset correction system to correct the lane offset in the lane offset correction module to achieve lane offset warning and automatic correction, eliminating safety hazards; the offset correction is confirmed again in the repeated positioning module, and the results are fed back in the system feedback module to eliminate the warning; the system relies on sensors and cameras to locate lanes, and can be used in places that the positioning system cannot cover, with very high environmental adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which constitute part of this application, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings: Figure 1 Schematic diagram of the system architecture of the present invention; Figure 2 Schematic diagram of the architecture of the data collection module in the present invention; Figure 3 Schematic diagram of the architecture of the pre-processing module in the present invention; Figure 4 Schematic diagram of the central processing module of the present invention; Figure 5 Schematic diagram of the architecture of the instruction output module in the present invention; Figure 6 This is a schematic diagram of the architecture of the device maintenance module in the present invention; Figure 7 Flowchart of a method according to an embodiment of the present invention.

[0016] Figure: 1. Data collection module; 2. Data transmission module; 3. Preprocessing module; 4. Repository module; 5. Central processing module; 6. Command output module; 7. Equipment maintenance module; 101. Equipment deployment module; 102. Equipment initialization module; 103. Vehicle data acquisition module; 104. Roadside data acquisition module; 301. Data receiving module; 302. Numerical processing module; 303. Graphics processing module; 304. Data cleaning module; 305. Denoising algorithm module; 306. Data format conversion module; 307 , data standardization module; 308, data fusion module; 309, feature extraction module; 501, lane positioning algorithm module; 502, lane positioning result module; 503, lane departure warning module; 601, command receiving module; 602, automatic driving module; 603, lane departure correction module; 604, system normal monitoring module; 605, repeated positioning module; 606, system feedback module; 701, regular maintenance module; 702, fault repair module; 703, special maintenance module; 704, feedback execution module. DETAILED DESCRIPTION

[0017] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that, unless there is a conflict, the embodiments and features in the embodiments of the present application can be combined with each other.

[0018] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise indicated, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit the exemplary embodiments according to the present invention.

[0019] The present application discloses a lane positioning system for vehicle-road cooperative perception, characterized by comprising: a data collection module 1, the data collection module 1 being controlled and connected to a data transmission module 2, the data transmission module 2 being controlled and connected to a preprocessing module 3, the preprocessing module 3 being controlled and connected to a central processing module 5, the central processing module 5 being controlled and connected to an instruction output module 6 and a storage library module 4 respectively; The command output module 6 includes a command receiving module 601, which is connected to the central processing module 5 and is respectively connected to the automatic driving module 602 and the lane deviation correction module 603. The automatic driving module 602 is connected to the system normal detection module 604, and the lane deviation correction module 603 is sequentially connected to the repeated positioning module 605 and the system feedback module 606. The command receiving module receives commands, and the automatic driving module performs automatic driving based on the positioning data. It can be linked with the automatic driving function, which is convenient and reliable. The system operates safely and smoothly in the system normal monitoring module. In the lane deviation correction module, the deviation correction system is used to correct lane deviation, achieving lane deviation warning and automatic correction, eliminating safety hazards. After the deviation correction, it is reconfirmed in the repeated positioning module, and the feedback result is fed back to the system feedback module to eliminate the warning. The system relies on sensors and cameras to locate lanes, and can be used in areas where the positioning system cannot cover, with very high environmental adaptability.

[0020] A data receiving module 301 is used to receive data from the data transmission module 2; The numerical processing module 302 is used to obtain numerical data of the data in the data receiving module 301; A data cleaning module 304 is used to clean the numerical data; The graphics processing module 303 is used to obtain the graphics data from the data receiving module 301; De-noising algorithm module 305, used for performing denoising processing on graphic data; The data format conversion module 306 is used to convert the denoised graphic data and the cleaned numerical data to obtain numerical data and graphic data in a unified format; A data standardization module 307 is used to perform standardization processing on the numerical data and graphic data in a unified format to obtain standardized numerical data and graphic data; The data fusion module 308 is used to fuse the standardized numerical data and graphic data to obtain fused data; The feature extraction module 309 is used to extract feature information related to lane positioning from the fused data, and transmit the feature information and the fused data to the central processing module 5 .

[0021] In some embodiments, the central processing module 5 includes: a lane positioning algorithm module 501, a lane positioning result module 502 and a lane departure warning module 503; the lane positioning algorithm module 501 controls the connection to the lane positioning result module 502, and the lane positioning result module 502 controls the connection to the lane departure warning module 503.

[0022] Lane positioning algorithm module 501, used to receive data transmitted by pre-processing module 3, and use lane positioning algorithm to detect lane lines and determine the current lane position of the vehicle; The lane positioning result module 502 is used to obtain the lane position determined by the lane positioning algorithm module 501 and output the lane position; The lane departure warning module 503 is used to determine whether the lane has been crossed according to the lane position, and generate an instruction based on the judgment result, transmit the instruction to the instruction receiving module 601, and transmit the judgment result to the storage module 4.

[0023] In some embodiments, the data collection module 1 includes: a device deployment module 101, a device initialization module 102, a vehicle data collection module 103 and a roadside data collection module 104, the device deployment module 101 controls the connection to the device initialization module 102, and the device initialization module 102 controls the connection to the vehicle data collection module 103; Device deployment module 101, for deploying sensors and cameras; The device initialization module 102 is used to initialize the deployed sensors and cameras; The vehicle data acquisition module 103 is used to obtain the graphic data around the vehicle in real time and transmit the graphic data to the data transmission module 2; The roadside data collection module 104 is used to obtain numerical data of current road and traffic conditions in real time and transmit the numerical data to the data transmission module 2.

[0024] In some embodiments, an equipment maintenance module 7 is also included, and the equipment maintenance module 7 includes a regular maintenance module 701, and the regular maintenance module 701 is respectively connected to a fault repair module 702 and a special maintenance module 703; the fault repair module 702 and the special maintenance module 703 are both connected to a feedback execution module 704; the regular maintenance module 701 and the feedback execution module 704 are connected to the central processing module 5.

[0025] Please see the attached Figure 1 -Attached Figure 6, an embodiment provided by the present invention: a lane positioning system for vehicle-road cooperative perception, including a data collection module 1, a data transmission module 2, a preprocessing module 3, a storage library module 4, a central processing module 5, an instruction output module 6 and a device maintenance module 7, the data collection module 1 controls the connection to the data transmission module 2, the data transmission module 2 controls the connection to the preprocessing module 3, the preprocessing module 3 controls the connection to the central processing module 5, the central processing module 5 controls the connection to the instruction output module 6, the storage library module 4 and the device maintenance module 7; the data collection module 1 is composed of a device deployment module 101, a device initialization module 102, a vehicle data collection module 103 and a roadside data collection module 104, the device deployment module 101 controls the connection to the preprocessing module 3, the preprocessing module 3 controls the connection to the central processing module 5, the central processing module 5 controls the connection to the instruction output module 6, the storage library module 4 and the device maintenance module 7; the data collection module 1 is composed of a device deployment module 101, a device initialization module 102, a vehicle data collection module 103 and a roadside data collection module 104, The device initialization module 102 is connected to the vehicle data acquisition module 103; the device initialization module 102 controls the connection to the roadside data acquisition module 104; the pre-processing module 3 is composed of a data receiving module 301, a numerical processing module 302, a graphic processing module 303, a data cleaning module 304, a denoising algorithm module 305, a data format conversion module 306, a data standardization module 307, a data fusion module 308 and a feature extraction module 309. The data receiving module 301 controls the connection to the numerical processing module 302, the numerical processing module 302 controls the connection to the data cleaning module 304, the data cleaning module 304 controls the connection to the data format conversion module 306, the data format conversion module 307, the data fusion module 308 and the feature extraction module 309. The conversion module 306 controls the connection to the data standardization module 307, the data standardization module 307 controls the connection to the data fusion module 308, and the data fusion module 308 controls the connection to the feature extraction module 309; the data receiving module 301 controls the connection to the graphics processing module 303, the graphics processing module 303 controls the connection to the denoising algorithm module 305, and the denoising algorithm module 305 controls the connection to the data format conversion module 306; the central processing module 5 is composed of a lane positioning algorithm module 501, a lane positioning result module 502 and a lane deviation warning module 503, the lane positioning algorithm module 501 controls the connection to the lane positioning result module 502, and the lane positioning result module 502 controls the connection to the lane deviation warning module 503; the command input The output module 6 is composed of an instruction receiving module 601, an automatic driving module 602, a system normal monitoring module 604, a lane deviation correction module 603, a repeated positioning module 605 and a system feedback module 606. The instruction receiving module 601 controls the connection to the automatic driving module 602, and the automatic driving module 602 controls the connection to the lane deviation correction module 603; the instruction receiving module 601 controls the connection to the system normal monitoring module 604, the system normal monitoring module 604 controls the connection to the repeated positioning module 605, and the repeated positioning module 605 controls the connection to the system feedback module 606; the equipment maintenance module 7 is composed of a regular maintenance module 701, a fault repair module 702, a special maintenance module 703 and a feedback execution module 704.

[0026] This application also discloses a lane positioning method for vehicle-road collaborative perception, comprising the following steps: The data collection module 1 acquires the graphic data around the vehicle and the numerical data of the current road and traffic conditions in real time, and transmits them to the preprocessing module 3 through the data transmission module 2, and performs preprocessing to obtain feature information and fusion data; The central processing module 5 determines the current lane position of the vehicle based on the feature information and fusion data, and determines whether the vehicle has crossed the lane based on the lane position; the judgment result is transmitted to the storage module 4 for storage, and an instruction is generated based on the judgment result; The automatic driving module 602 performs automatic driving based on the feature information and the fused data, and the lane deviation correction module 603 corrects the lane deviation based on the instructions generated by the central processing module 5.

[0027] In some embodiments, the data collection module 1 includes: a device deployment module 101, a device initialization module 102, a vehicle data collection module 103, and a roadside data collection module 104. The data collection module 1 acquires graphical data around the vehicle and numerical data of current road and traffic conditions in real time, specifically including: The vehicle data acquisition module 103 acquires graphic data around the vehicle in real time, and the roadside data acquisition module 104 acquires numerical data of the current road and traffic conditions in real time. The graphic data and numerical data are transmitted to the data transmission module 2.

[0028] In some embodiments, the preprocessing module 3 includes: a data receiving module 301, a numerical processing module 302, a graphic processing module 303, a data cleaning module 304, a denoising algorithm module 305 and a data format conversion module 306. The feature information and fusion data obtained by preprocessing include: The data receiving module 301 receives data from the data transmission module 2. The numerical processing module 302 and the graphic processing module 303 classify the data in the data receiving module 301 and receive the numerical data and graphic data respectively. The data cleaning module 304 cleans the numerical data output by the numerical processing module 302. The denoising algorithm module 305 denoises the graphic data output by the graphic processing module 303. The data format conversion module 306 converts the denoised graphic data and the cleaned numerical data into data formats to obtain numerical data and graphic data in a unified format. The data standardization module 307 standardizes the numerical data and graphic data in a unified format to obtain standardized numerical data and graphic data. The data fusion module 308 fuses the standardized numerical data and graphic data to obtain fused data. The feature extraction module 309 extracts feature information related to lane positioning from the fused data and transmits the feature information and fused data to the central processing module 5.

[0029] In some embodiments, equipment maintenance steps are also included, specifically, regular maintenance of equipment in the regular maintenance module 701 in the equipment maintenance module 7, repair of faulty equipment in the fault repair module 702, special maintenance of equipment in the special maintenance module 703, and reporting of maintenance status to the central processing module 5 in the feedback execution module 704.

[0030] In some embodiments, see the attached Figure 7 A lane positioning method for vehicle-road cooperative perception includes the following steps: step 1, data collection and transmission; step 2, data processing and decision-making; step 3, command output and execution; step 4, equipment maintenance; In step 1 above, sensors and cameras are deployed through the device deployment module 101 in the data collection module 1, the devices are initialized in the device initialization module 102, information about the vehicle's surroundings is collected in real time through the camera in the vehicle data collection module 103, and information about current road and traffic conditions is collected in the roadside data collection module 104; In the above step 2, the collected data are classified in the numerical processing module 302 and the graphic processing module 303, unnecessary values ​​are removed in the data cleaning module 304, and excess noise is removed in the denoising algorithm module 305 to improve the quality and usability of the data. The data from different sources is converted into a unified format in the data format conversion module 306 for subsequent processing and analysis. The data is standardized in the data standardization module 307 so that the data from different sources have the same scale and range. The data from different sensors are fused in the data fusion module 308 to improve the integrity and accuracy of the data. The feature extraction module 309 extracts feature information related to lane positioning from the fused data and transmits the extracted relevant feature information to the lane positioning algorithm module 501 in the central processing module 5. In the lane positioning algorithm module 501, the extracted feature information and the fused data are applied to the lane positioning algorithm, such as edge detection, Hough transform, etc., to detect lane lines to determine the current lane position of the vehicle. The positioning result is output in the lane positioning result module 502. The lane deviation warning module 503 determines whether the lane has been crossed based on the output result. In step three above, the command is received in the command receiving module 601 and transmitted to the autonomous driving module 602 based on the positioning data, which is convenient and reliable. The system operates safely and smoothly in the system normal monitoring module 604. The lane deviation is corrected using the deviation correction system in the lane deviation correction module 603, achieving lane deviation warning and automatic correction, eliminating safety hazards. After the deviation correction, it is confirmed again in the repeated positioning module 605, and the feedback result is fed back in the system feedback module 606 to eliminate the warning. In the above step 4, the equipment is regularly maintained in the regular maintenance module 701 of the equipment maintenance module 7, the faulty equipment is repaired in the fault repair module 702, the equipment is specially maintained in the special maintenance module 703, and the maintenance status is reported to the processing center in the feedback execution module 704.

[0031] The present application also discloses a car, comprising a lane positioning system for vehicle-road collaborative perception as described in any one of the above.

[0032] Based on the above, the advantage of the present invention is that when the present invention is used, the sensors and cameras are arranged through the device deployment module 101 in the data collection module 1, the equipment is initialized in the device initialization module 102, the information around the vehicle is collected in real time through the camera in the vehicle data collection module 103, and the information of the current road and traffic conditions is collected in the roadside data collection module 104; the collected data is transmitted to the data receiving module 301 in the preprocessing module 3 through the data transmission module 2, the collected data is classified in the numerical processing module 302 and the graphic processing module 303, the unnecessary values ​​are washed out in the data cleaning module 304, and the noise reduction algorithm module 306 is used to generate the image data. 05 removes excess noise to improve data quality and usability. In the data format conversion module 306, data from different sources are converted into a unified format for subsequent processing and analysis. In the data standardization module 307, data is standardized so that data from different sources have the same scale and range. In the data fusion module 308, data from different sensors are fused to improve data integrity and accuracy. In the feature extraction module 309, feature information related to lane positioning is extracted from the fused data and the extracted relevant feature information is transmitted to the lane positioning algorithm module 501 in the central processing module 5. In the lane positioning algorithm In module 501, the extracted feature information and the fused data are applied to lane positioning algorithms such as edge detection and Hough transform to detect lane lines to determine the current lane position of the vehicle. The positioning result is output in the lane positioning result module 502. The lane deviation warning module 503 determines whether the line is crossed based on the output result. The data result is transmitted to the instruction receiving module 601 in the storage module 4 and the instruction output module 6. The instruction is received in the instruction receiving module 601 and transmitted to the automatic driving module 602 based on the positioning data. It is convenient and reliable. The system runs safely and smoothly in the system normal monitoring module 604. In block 603, the offset correction system is used to correct the lane offset, realize lane offset warning and automatic correction, and eliminate safety hazards; in the repeated positioning module 605, the offset correction is confirmed again, and the feedback result is fed back in the system feedback module 606 to eliminate the warning, and the equipment is regularly maintained in the regular maintenance module 701 of the equipment maintenance module 7, the faulty equipment is repaired in the fault repair module 702, and the equipment is specially maintained in the special maintenance module 703. The maintenance status is reported to the processing center in the feedback execution module 704. The system relies on sensors and cameras to locate the lane, and can be used in places that the positioning system cannot cover, with very high environmental adaptability.

[0033] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware.

[0034] Throughout this specification, references to terms such as "one embodiment," "example," or "specific example" indicate that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A lane positioning system for vehicle-road cooperative perception, characterized by: include: A data collection module (1), the data collection module (1) is controlled and connected to a data transmission module (2), the data transmission module (2) is controlled and connected to a pre-processing module (3), the pre-processing module (3) is controlled and connected to a central processing module (5), and the central processing module (5) is controlled and connected to an instruction output module (6) and a storage library module (4); The command output module (6) includes a command receiving module (601), the command receiving module (601) is connected to the central processing module (5), and the command receiving module (601) is respectively connected to the automatic driving module (602) and the lane deviation correction module (603), the automatic driving module (602) is connected to the system normal detection module (604), and the lane deviation correction module (603) is sequentially connected to the repeated positioning module (605) and the system feedback module (606).

2. The lane positioning system for vehicle-road cooperative perception according to claim 1, characterized in that: The pre-processing module (3) comprises: A data receiving module (301) is used to receive data from the data transmission module (2); A numerical processing module (302) is used to obtain numerical data of the data in the data receiving module (301); A data cleaning module (304) is used to clean the numerical data; A graphics processing module (303) is used to obtain graphic data from the data receiving module (301); A denoising algorithm module (305) is used to perform denoising on the graphic data; A data format conversion module (306) is used to convert the denoised graphic data and the cleaned numerical data to obtain numerical data and graphic data in a unified format; A data standardization module (307) is used to perform standardization processing on numerical data and graphic data in a unified format to obtain standardized numerical data and graphic data; A data fusion module (308) is used to fuse the standardized numerical data and graphic data to obtain fused data; The feature extraction module (309) is used to extract feature information related to lane positioning from the fused data, and transmit the feature information and the fused data to the central processing module (5).

3. The lane positioning system for vehicle-road cooperative perception according to claim 1, characterized in that: The central processing module (5) comprises: A lane positioning algorithm module (501) is used to receive data transmitted by the pre-processing module (3), and use a lane positioning algorithm to detect lane lines and determine the current lane position of the vehicle; a lane positioning result module (502), configured to obtain the lane position determined by the lane positioning algorithm module (501) and output the lane position; The lane deviation warning module (503) is used to determine whether the lane has been crossed based on the lane position, and to generate an instruction based on the determination result, and transmit the instruction to the instruction receiving module (601), and the determination result is transmitted to the storage module (4).

4. The lane positioning system for vehicle-road cooperative perception according to claim 1, characterized in that: The data collection module (1) comprises: A device deployment module (101) is used to deploy sensors and cameras; A device initialization module (102) is used to initialize the deployed sensors and cameras; A vehicle data acquisition module (103) is used to acquire graphic data around the vehicle in real time and transmit the graphic data to the data transmission module (2); The roadside data acquisition module (104) is used to obtain numerical data of current road and traffic conditions in real time, and transmit the numerical data to the data transmission module (2).

5. The lane positioning system for vehicle-road cooperative perception according to claim 1, characterized in that: The device further comprises an equipment maintenance module (7), the equipment maintenance module (7) comprising a regular maintenance module (701), the regular maintenance module (701) being connected to a fault repair module (702) and a special maintenance module (703), respectively; the fault repair module (702) and the special maintenance module (703) being both connected to a feedback execution module (704); and the regular maintenance module (701) and the feedback execution module (704) being connected to the central processing module (5).

6. A lane positioning method for vehicle-road cooperative perception, characterized in that: The lane positioning system according to any one of claims 1 to 5 is implemented, comprising the following steps: The data collection module (1) acquires the graphic data around the vehicle and the numerical data of the current road and traffic conditions in real time, and transmits the data to the preprocessing module (3) through the data transmission module (2) to obtain feature information and fusion data through preprocessing; The central processing module (5) determines the current lane position of the vehicle based on the feature information and the fused data, and determines whether the vehicle has crossed the lane based on the lane position; the judgment result is transmitted to the storage module (4) to store the data, and an instruction is generated based on the judgment result; The automatic driving module (602) performs automatic driving based on the feature information and the fused data, and the lane deviation correction module (603) corrects the lane deviation based on the instruction generated by the central processing module (5).

7. The lane positioning method for vehicle-road cooperative perception according to claim 6 is characterized in that: The data collection module (1) includes: a device deployment module (101), a device initialization module (102), a vehicle data collection module (103) and a roadside data collection module (104). The data collection module (1) acquires graphic data around the vehicle and numerical data of current road and traffic conditions in real time, specifically including: The vehicle data acquisition module (103) acquires graphic data around the vehicle in real time, and the roadside data acquisition module (104) acquires numerical data of the current road and traffic conditions in real time. The graphic data and numerical data are transmitted to the data transmission module (2).

8. The lane positioning method for vehicle-road cooperative perception according to claim 6 is characterized in that: The preprocessing module (3) includes: a data receiving module (301), a numerical processing module (302), a graphic processing module (303), a data cleaning module (304), a denoising algorithm module (305) and a data format conversion module (306). The feature information and fusion data obtained by preprocessing include: The data receiving module (301) receives data from the data transmission module (2), and the numerical processing module (302) and the graphic processing module (303) classify the data in the data receiving module (301) and receive the numerical data and graphic data respectively; the data cleaning module (304) cleans the numerical data output by the numerical processing module (302); the denoising algorithm module (305) denoises the graphic data output by the graphic processing module (303); the data format conversion module (306) converts the denoised graphic data and the cleaned numerical data into data formats to obtain numerical data and graphic data in a unified format; the data standardization module (307) standardizes the numerical data and graphic data in a unified format to obtain standardized numerical data and graphic data; the data fusion module (308) fuses the standardized numerical data and graphic data to obtain fused data; the feature extraction module (309) extracts feature information related to lane positioning in the fused data and transmits the feature information and the fused data to the central processing module (5).

9. The lane positioning method for vehicle-road cooperative perception according to claim 6, characterized in that: The system also includes equipment maintenance steps, specifically, regularly maintaining equipment in a regular maintenance module (701) in the equipment maintenance module (7), repairing faulty equipment in a fault repair module (702), performing special maintenance on equipment in a special maintenance module (703), and reporting the maintenance status to the central processing module (5) in a feedback execution module (704).

10. An automobile, characterized in that: A lane positioning system with vehicle-road collaborative perception comprising the vehicle-road collaborative perception system as described in any one of claims 1 to 5.

Images