An edge-computing-based distributed storage method and system for vehicle-mounted map data

Abstract

The application provides a kind of based on edge computing's vehicle-mounted map data distributed storage method and system, it is related to intelligent transportation and edge computing technical field, the application is by first obtaining vehicle-mounted map data source and hierarchical processing, separate out the basic layer data containing basic road network and the detail layer data containing lane line, traffic sign;Again, road side edge computing unit and supporting communication unit are deployed, the effective value of communication is evaluated by physical layer processor, and the effective signal coverage area is defined by optimizing parameter;Subsequently, in combination with edge computing unit position, coverage area and basic road network information, the detail layer data is dynamically sliced, and the sliced data is distributedly stored in the optimal node to form a storage network;Finally, when vehicle enters coverage area, relevant map information is obtained and distributed based on optimization parameter, which can realize distributed storage of vehicle-mounted map data and efficiently provide relevant map information for vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent transportation and edge computing, and particularly relates to a vehicle-mounted map data distributed storage method and system based on edge computing. BACKGROUND

[0002] In the intelligent transportation system, automatic driving vehicles need real-time and accurate map data support to realize path planning, environment perception and safe driving functions. In order to ensure that vehicles can efficiently obtain the required map data, a data storage method capable of realizing distributed storage and fast response is needed to reduce data transmission delay and improve data availability and reliability.

[0003] At present, some schemes use centralized servers to store vehicle-mounted map data. All vehicle-mounted map data is stored in one or several large data center servers, and vehicles communicate with the server through the network, send a request to the server when map data is needed, and the server transmits the corresponding data to the vehicle.

[0004] However, the centralized server storage scheme has many problems. On the one hand, the data transmission distance is far, which will cause high delay, especially when the vehicle is driving at high speed, it may not be able to obtain the latest map data in time, affecting the safety and reliability of automatic driving. On the other hand, the centralized server faces a large access pressure, when a large number of vehicles request data at the same time, the server is easy to be congested or even crashed, causing data service interruption. SUMMARY

[0005] The purpose of the present application is to provide a vehicle-mounted map data distributed storage method and system based on edge computing to solve the problems of high transmission delay, easy congestion and crash, and not conducive to data update and maintenance in the prior art.

[0006] To solve the above technical problems, in a first aspect, the present application provides a vehicle-mounted map data distributed storage method based on edge computing, comprising:

[0007] Obtaining a vehicle-mounted map data source, and performing layered processing on the vehicle-mounted map data source to separate out basic layer data containing basic road network information and detail layer data containing lane line and traffic sign fine information;

[0008] Deploying a roadside edge computing unit and a matching roadside communication unit, monitoring and evaluating the communication effective value and communication connection effective value of the roadside communication unit through a physical layer processor, and adjusting and optimizing the communication quality parameters according to the evaluation results to dynamically define the effective signal coverage area of the roadside communication unit;

[0009] According to the physical distribution position of each roadside edge computing unit and the effective signal coverage area of the communication unit matched therewith, in combination with the basic road network information provided by the basic layer data, the lane line and traffic sign fine information in the detail layer data is subjected to dynamic logical slicing processing, and the sliced vehicle-mounted map data is distributed and stored on the optimal roadside edge computing unit corresponding node to form a distributed storage network.

[0010] When the vehicle enters the effective signal coverage area of the roadside communication unit, the map detail slice and the basic road network information related to the current position of the vehicle are acquired from the distributed storage network based on the optimized communication quality parameters, and the map detail slice and the basic road network information are distributed to the vehicle.

[0011] Optionally, according to the physical distribution position of each roadside edge computing unit and the effective signal coverage area of the communication unit matched therewith, in combination with the basic road network information provided by the basic layer data, the lane line and traffic sign fine information in the detail layer data is subjected to dynamic logical slicing processing, and the sliced vehicle-mounted map data is distributed and stored on the optimal roadside edge computing unit corresponding node to form a distributed storage network, comprising:

[0012] The physical distribution position of each roadside edge computing unit in the geographical space is determined, and the effective signal coverage area of each communication unit is acquired.

[0013] According to the basic road network information provided by the basic layer data, the key elements in the detail layer data that need to be processed are identified, and the key elements include lane line and traffic sign fine information.

[0014] According to the physical distribution position and the effective signal coverage area, the key elements are logically divided to form preliminary data segments.

[0015] By analyzing the correlation of the preliminary data segments at different positions, further segment adjustment is performed so that each segment contains the most relevant lane line and traffic sign information.

[0016] An optimal storage node is selected for each data segment, and the storage capacity, signal reliability and physical distance of the storage node are comprehensively considered, and the adjusted data segment is distributed to the corresponding roadside edge computing unit to construct a distributed storage network.

[0017] Optionally, according to the physical distribution position and the effective signal coverage area, the key elements are logically divided to form preliminary data segments, comprising:

[0018] Based on the physical distribution location, determine the spatial relationship between each roadside edge computing unit, and at the same time, based on the effective signal coverage area, demarcate the signal area boundary of each communication unit;

[0019] Combined with the spatial relationship and the signal area boundary, establish a location-signal association mapping, and according to the association mapping, group the key elements according to the signal area to which they belong;

[0020] Perform segmentation operation on the key elements in each group, generate data blocks, and adjust the segmentation granularity of the data blocks according to the element attributes and distribution density;

[0021] By iteratively optimizing the segmentation boundary of the data block, the element correlation degree inside each segmentation fragment is maximized and the overlap between fragments is minimized, and the preliminary data fragment is obtained.

[0022] Optionally, deploy roadside edge computing units and supporting roadside communication units, monitor and evaluate the communication effective value and communication connection effective value of the roadside communication unit through the physical layer processor, and adjust and optimize the communication quality parameter according to the evaluation result, to dynamically define the effective signal coverage area of the roadside communication unit, including:

[0023] Deploy roadside edge computing units and supporting roadside communication units, physically connect the roadside edge computing units with the roadside communication units, and establish a data interaction channel;

[0024] Segment and analyze the signals received by the roadside communication unit through the physical layer processor, extract the communication effectiveness indicators therefrom, and perform multiple calculations on each of the communication effectiveness indicators to generate a communication effective value;

[0025] Continuously monitor the integrity information of the communication connection through the data interaction channel, extract the connection state characteristics, and generate a communication connection effective value according to the connection state characteristics;

[0026] Jointly evaluate the communication effective value and the communication connection effective value, and adjust and optimize the communication quality parameter according to the joint evaluation result;

[0027] By dynamically adjusting the communication quality parameter, reconfigure the signal output characteristics of the roadside communication unit, and gradually limit and update the effective signal coverage area of the roadside communication unit in combination with the real-time changes of the signal environment, until the optimized signal range definition is achieved.

[0028] Optionally, segment and analyze the signals received by the roadside communication unit through the physical layer processor, extract the communication effectiveness indicators therefrom, and perform multiple calculations on each of the communication effectiveness indicators to generate a communication effective value, including:

[0029] The continuous signal stream received by the roadside communication unit is divided into multiple signal segments at fixed time intervals, and each signal segment is independently analyzed by a physical layer processor to obtain a set of communication characteristic parameters for each signal segment;

[0030] Signal strength data and data transmission rate data are obtained for each signal segment from the set of communication characteristic parameters, and based on the signal strength data and the data transmission rate data, signal stability values and data transmission success rate values per unit time are calculated;

[0031] The signal stability values and the data transmission success rate values are respectively subjected to weighting operations, and the weighted results are fused according to a predetermined proportion to obtain a comprehensive score, and a communication effective value is calculated based on the comprehensive score.

[0032] Optionally, when the vehicle enters the effective signal coverage area of the roadside communication unit, the map detail slice and the basic road network information related to the current position of the vehicle are obtained from the distributed storage network based on the optimized communication quality parameters, and the map detail slice and the basic road network information are distributed to the vehicle, including:

[0033] The roadside communication unit continuously monitors the change in signal strength of vehicles in the area, and determines that the vehicle enters the effective signal coverage area when the signal strength exceeds a predetermined threshold;

[0034] Based on the current position coordinates of the vehicle, the map detail slice and the basic road network information corresponding to the position in the distributed storage network are queried;

[0035] According to the optimized communication quality parameters, a stable data transmission channel is established, and the queried map detail slice and basic road network information are segmented and packaged;

[0036] Through the data transmission channel, the packaged information is sent to the receiving module of the vehicle, ensuring that the vehicle can obtain the required navigation information in real time when entering a new area, realizing the continuity and accuracy of vehicle navigation.

[0037] Optionally, the vehicle-mounted map data source is obtained, and the vehicle-mounted map data source is subjected to hierarchical processing to separate the basic layer data containing basic road network information and the detail layer data containing lane line and traffic sign fine information, including:

[0038] The vehicle-mounted map data source is obtained, and the road network related information is extracted from the vehicle-mounted map data source. The road network related information is analyzed by data to identify the basic structure elements, and the basic structure elements are combined into basic layer data;

[0039] Synchronously identify information elements related to lane lines and traffic signs from the vehicle-mounted map data source, further analyze the information elements in detail, and form detail layer data;

[0040] Perform information screening on the preliminarily formed basic layer data and the detail layer data, eliminate redundant information, and ensure the accuracy of the data levels;

[0041] Through data reconstruction, integrate the screened information into the corresponding levels, and complete the separation and construction of the basic layer data and the detail layer data.

[0042] In a second aspect, the application provides a vehicle-mounted map data distributed storage system based on edge computing, comprising:

[0043] A hierarchical module is configured to obtain a vehicle-mounted map data source and perform hierarchical processing on the vehicle-mounted map data source to separate basic layer data containing basic road network information and detail layer data containing lane line and traffic sign detailed information;

[0044] An adjustment module is configured to deploy a roadside edge computing unit and a matching roadside communication unit, monitor and evaluate the communication effective value and the communication connection effective value of the roadside communication unit through a physical layer processor, and adjust and optimize the communication quality parameter according to the evaluation result to dynamically define the effective signal coverage area of the roadside communication unit;

[0045] A slicing module is configured to perform dynamic logical slicing processing on the lane line and traffic sign detailed information in the detail layer data according to the physical distribution position of each roadside edge computing unit and the effective signal coverage area of the matching communication unit thereof, in combination with the basic road network information provided by the basic layer data, and store the sliced vehicle-mounted map data in the optimal roadside edge computing unit corresponding node to form a distributed storage network;

[0046] A distribution module is configured to, when a vehicle enters the effective signal coverage area of the roadside communication unit, acquire a map detail slice and basic road network information related to the current position of the vehicle from the distributed storage network based on the optimized communication quality parameter, and distribute the map detail slice and the basic road network information to the vehicle.

[0047] In a third aspect, the application provides an electronic device, comprising:

[0048] A memory is configured to store a computer program;

[0049] A processor is configured to execute the computer program to implement the steps of the vehicle-mounted map data distributed storage method based on edge computing according to the first aspect.

[0050] In a fourth aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program, when executed by a processor, enables the steps of the vehicle-mounted map data distributed storage method based on edge computing according to the first aspect.

[0051] The vehicle-mounted map data distributed storage method based on edge computing provided by the present application can realize classified management of vehicle-mounted map data by obtaining a vehicle-mounted map data source and performing hierarchical processing to separate basic layer data of basic road network information and detail layer data of lane line and traffic sign fine information, lay a foundation for subsequent targeted storage and distribution, and avoid inefficient calling caused by mixed storage of data; the roadside edge computing unit and the matching communication unit are deployed, the communication effective value and the connection effective value are monitored and evaluated by means of the physical layer processor, the communication quality parameter is adjusted and optimized to dynamically define the effective signal coverage area, the roadside communication performance can be optimized in real time, the communication quality is stable, the communication range is accurately defined, and support is provided for data transmission reliability and coverage accuracy; in combination with the roadside edge computing unit position, the effective coverage area of the matching communication unit and the basic layer road network information, the detail layer data is dynamically logically sliced, the sliced data is distributed and stored in the optimal node to form a storage network, efficient fragmentation and reasonable storage of map detail data can be realized, redundancy is reduced, storage utilization is improved, data storage and use scenarios are matched, and conditions are created for fast retrieval; when a vehicle enters an effective signal coverage area, the map detail slice and the basic road network information related to the current position of the vehicle are obtained and distributed from the distributed storage network based on the optimized communication quality parameter, the vehicle can accurately obtain the required map information, transmission delay is reduced, real-time performance and accuracy of vehicle-mounted map services are improved, and driving use requirements are met. BRIEF DESCRIPTION OF DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the drawings needed in the embodiment or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0053] Figure 1 A flowchart of a vehicle-mounted map data distributed storage method based on edge computing provided by an embodiment of the present application is shown in the figure;

[0054] Figure 2 A specific implementation flowchart of a vehicle-mounted map data distributed storage method based on edge computing provided by an embodiment of the present application is shown in the figure;

[0055] Figure 3A scene diagram of a vehicle-mounted map data distributed storage method based on edge computing provided by an embodiment of the present application;

[0056] Figure 4 A structural schematic diagram of a vehicle-mounted map data distributed storage system based on edge computing provided by an embodiment of the present application. DETAILED DESCRIPTION

[0057] At present, the demand for real-time and accurate map data by autonomous vehicles is extremely urgent. However, the existing centralized server storage vehicle-mounted map data scheme has many drawbacks. The long data transmission distance leads to high delay, and it is difficult for vehicles to quickly obtain the latest map data when driving at high speed, which seriously affects the safety and reliability of autonomous driving. Moreover, the centralized server bears huge access pressure, and when a large number of vehicles request data at the same time, congestion and even collapse are likely to occur, causing data service interruption. In addition, the centralized storage data updating and maintenance efficiency is low, and the entire server needs to be operated, which cannot meet the frequent demand for map data updating.

[0058] To solve the above problems, the present application provides a vehicle-mounted map data distributed storage method based on edge computing. The method first performs hierarchical processing on the vehicle-mounted map data source, separating the basic layer data and the detail layer data. Then, the roadside edge computing unit and the matching communication unit are deployed, the communication quality parameters are optimized by monitoring and evaluating the communication situation, and the effective signal coverage area is dynamically defined. Then, the detail layer data is sliced in combination with the position and coverage area of the roadside unit, and is distributed stored on the optimal node to form a network. When the vehicle enters the effective signal coverage area, it can obtain the related map data based on the optimized parameters. This scheme stores data in the roadside edge computing unit, greatly shortens the data transmission distance and reduces the delay; distributed storage also reduces the access pressure of a single server, avoiding congestion and collapse; at the same time, data updating only needs to be operated on the corresponding node, improving the updating and maintenance efficiency, and effectively solving the problems existing in the centralized storage scheme.

[0059] In order for those skilled in the art to better understand the present application, the present application will be further described in detail below in combination with the drawings and specific embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0060] The core of the present application is to provide a vehicle-mounted map data distributed storage method based on edge computing, and a flowchart of a specific embodiment thereof is shown in Figure 1 The method comprises:

[0061] S101, acquire a vehicle-mounted map data source, and perform hierarchical processing on the vehicle-mounted map data source to separate out basic layer data containing basic road network information and detail layer data containing lane line and traffic sign detailed information;

[0062] Optionally, step S101 can specifically include the following steps:

[0063] S1011, acquire a vehicle-mounted map data source, extract road network related information from the vehicle-mounted map data source, identify basic structure elements by data parsing the road network related information, and combine the basic structure elements into basic layer data;

[0064] S1012, simultaneously identify information elements related to lane lines and traffic signs from the vehicle-mounted map data source, further analyze the information elements to form detail layer data;

[0065] S1013, perform information screening on the preliminary formed basic layer data and detail layer data, eliminate redundant information, and ensure the accuracy of the data levels;

[0066] S1014, integrate the screened information into the corresponding levels by data reconstruction, complete the separation and construction of the basic layer data and the detail layer data.

[0067] In the above steps, the vehicle-mounted map data source refers to a data set containing various geographic information such as roads and traffic facilities; the basic road network information refers to basic framework data constituting a road network, including the direction of a road, connection relationship, main road name, etc.; the basic layer data is combined by basic structure elements and is used to reflect the overall framework of a road network; the lane line and traffic sign detailed information refers to detailed information such as lane dividing lines, guide arrows, speed limit signs, prohibition signs, etc. on a road; the detail layer data is formed by detailed analysis of information elements related to lane lines and traffic signs and is used to show the detailed features of a road; the basic structure element is an element constituting a road basic framework identified from road network related information; the information element refers to various data units related to lane lines and traffic signs; and the redundant information refers to information that is repeated or unnecessary in the basic layer data and the detail layer data.

[0068] In the embodiments of the present application, first, the vehicle-mounted map data source is acquired through step S1011, road network related information is extracted from the data source, and the road network related information is processed through data analysis technology to identify basic structural elements such as the starting point and ending point of a road, the position of an intersection, and the like. Finally, the basic structural elements are combined into basic layer data according to certain logic, for example, the direction of all roads and connection points and the like of road network related information are extracted from the vehicle-mounted map data source of a certain area, the connection point of the main road A and the secondary road B, the starting point and ending point of the main road A and the like of basic structural elements are identified through analysis, and these elements are combined to form the basic layer data reflecting the overall road framework of the area.

[0069] Secondly, information elements related to lane lines and traffic signs, such as the type of lane lines, the pattern and text of traffic signs and the like, are identified from the vehicle-mounted map data source through step S1012 by using image recognition technology and the like, and then the information elements are further analyzed in detail to determine their specific meanings and attributes to form detailed layer data, for example, while the road network related information of the above-mentioned area is extracted, the double solid yellow line on the main road A and the speed limit 60 km / h sign on the secondary road B and the like of information elements are identified, the attribute of the double solid yellow line indicating prohibition of crossing is analyzed, the speed limit value and the like of information of the speed limit sign are analyzed, and the detailed layer data of the road of the area is formed.

[0070] Then, the information screening is performed on the basic layer data and the detailed layer data preliminarily formed by using data cleaning technology through step S1013, the repeated contents such as the same intersection information repeatedly recorded in the basic layer data are removed, and the contents meaningless to reflect the characteristics of the road are removed, so as to ensure that the basic layer data only contains road basic framework information and the detailed layer data only contains fine information of lane lines and traffic signs, and the accuracy of the data level is ensured, for example, in the above-mentioned basic layer data preliminarily formed, the connection point information of the main road A and the secondary road B is recorded twice, one of the repeated information is removed, and the building identification information irrelevant to the road is also removed in the detailed layer data.

[0071] Finally, the data reconstruction is performed on the screened information by using data integration technology through step S1014, the information belonging to the basic road framework is integrated into the basic layer data, and the fine information belonging to the lane lines and traffic signs is integrated into the detailed layer data, so as to complete the separation and construction of the basic layer data and the detailed layer data, for example, the direction of the main road A, the connection relationship with other roads and the like of information determined after screening are integrated into the basic layer data, the position of the double solid yellow line, the specific parameters of the speed limit sign and the like of information are integrated into the detailed layer data, and the separation and construction of the two are realized.

[0072] In practical applications, a certain vehicle navigation technology company undertook the B city intelligent transportation project, and needed to process the vehicle map data of the city in layers to support subsequent distributed storage. The project team first collected the vehicle map data source of the whole B city through professional surveying and mapping equipment. The data source contains geographic information of more than 2000 roads, image data and corresponding coordinate information of more than 5000 traffic signs. In step S1011, the team uses a geographic information system (GIS) tool to extract road network related information from the data source, identifies the centerline trajectory of each road, the latitude and longitude of the intersection, the road grade and other basic structural elements through analysis algorithm, integrates the framework information of the main road and the secondary road respectively, and forms the basic layer data covering the whole B city. In step S1012, a convolutional neural network based image recognition model is used to identify lane lines, traffic signs and other information elements from the road images in the data source, and the type, length and coordinate range of each lane line, the meaning and installation position of each traffic sign are analyzed in detail to form the detail layer data of the corresponding road section. After entering step S1013, the team uses a data cleaning tool to filter the two layers of data, and removes 32 repeated intersection records in the basic layer and 15 commercial advertising identification information mixed in the detail layer, to ensure data purity. Finally, in step S1014, the basic layer data is divided into modules according to the level of "ring line-main road-secondary road-branch road" by using a data reconstruction tool, and the detail layer data is divided into units according to each 1 kilometer road section, and the effective information is integrated respectively, and the separation and construction of the basic layer data and the detail layer data of the vehicle map of B city are completed in 3 days, which makes data preparation for subsequent deployment of distributed storage of roadside edge computing unit.

[0073] In the overall scheme of the above step S101, through multi-link fine data processing, the conversion of vehicle map data from original data source to layered structured data is realized, which not only ensures the clear presentation of road framework in basic layer data and the accurate reflection of road identification in detail layer data, but also improves the data quality by removing redundant information, provides layered data support for subsequent distributed storage based on edge computing, so that subsequent data storage can be deployed according to the characteristics of different level data, and also lays a data foundation for vehicle to obtain accurate map information in the future.

[0074] S102, deploying a roadside edge computing unit and a matching roadside communication unit, monitoring and evaluating the communication effective value and communication connection effective value of the roadside communication unit through a physical layer processor, and adjusting and optimizing the communication quality parameter according to the evaluation result to dynamically define the effective signal coverage area of the roadside communication unit;

[0075] Optionally, step S102 can specifically include the following steps:

[0076] S1021, deploy a roadside edge computing unit and a matching roadside communication unit, physically connect the roadside edge computing unit with the roadside communication unit, and establish a data interaction channel;

[0077] S1022, segmentally analyze the signals received by the roadside communication unit through a physical layer processor, extract communication effectiveness indicators therefrom, and perform multiple calculations on each of the communication effectiveness indicators to generate a communication effectiveness value;

[0078] The step S1022 can specifically include the following process: dividing the continuous signal stream received by the roadside communication unit into multiple signal segments at fixed time intervals, independently analyzing each signal segment through a physical layer processor to obtain a set of communication characteristic parameters for each signal segment; obtaining signal strength data and data transmission rate data for each signal segment from the set of communication characteristic parameters, calculating signal stability value and data transmission success rate value within a unit time based on the signal strength data and the data transmission rate data; performing weighted operation on the signal stability value and the data transmission success rate value respectively, and fusing the weighted results according to a preset proportion to obtain a comprehensive score, and calculating a communication effectiveness value based on the comprehensive score.

[0079] S1023, continuously monitor the integrity information of the communication connection through the data interaction channel, extract connection state features, and generate a communication connection effectiveness value according to the connection state features;

[0080] S1024, jointly evaluate the communication effectiveness value and the communication connection effectiveness value, and adjust and optimize the communication quality parameters according to the joint evaluation result;

[0081] S1025, by dynamically adjusting the communication quality parameters, reconfiguring the signal output characteristics of the roadside communication unit, and combining the real-time changes of the signal environment, gradually limiting and updating the effective signal coverage area of the roadside communication unit until the optimized signal range definition is achieved.

[0082] In the above steps, the roadside edge computing unit is a computing device deployed near the road with data processing and storage capabilities for processing vehicle map related data nearby; the roadside communication unit is a communication device matched with the roadside edge computing unit, responsible for data transmission with the vehicle; the physical layer processor is a hardware module for processing communication physical layer signals and monitoring communication status; the communication effective value is a comprehensive value reflecting the signal transmission quality of the roadside communication unit calculated based on the communication effectiveness index; the communication connection effective value is a value reflecting the connection stability of the roadside communication unit and the vehicle generated based on the communication connection integrity information; the communication quality parameter is a set index affecting the communication effect, including signal transmission power, transmission frequency, etc.; the effective signal coverage area is the geographical range in which the roadside communication unit can stably transmit data; the data interaction channel is the link between the roadside edge computing unit and the roadside communication unit for transmitting data; the signal segment is a segment obtained by dividing the continuous signal stream received by the roadside communication unit according to a fixed time interval; the communication characteristic parameter set is a data combination reflecting the signal characteristics parsed from the signal segment, including signal strength data and data transmission rate data; the signal strength data is a value representing the signal strength; the data transmission rate data is a value representing the data transmission amount per unit time; the signal stability value is a value reflecting the signal strength change amplitude calculated based on the signal strength data; and the data transmission success rate value is a value reflecting the data successful transmission proportion calculated based on the data transmission rate data.

[0083] In the embodiments of the present application, first, the roadside edge computing unit and the matched roadside communication unit are deployed at the designated position near the road in the A area through step S1021, the roadside edge computing unit and the roadside communication unit are physically connected by using a network cable or an optical fiber, a stable data interaction channel is constructed, and it is ensured that the two can transmit data in real time. For example, a set of roadside edge computing unit and roadside communication unit is deployed every 1 kilometer on both sides of the main road C in the A area, the edge computing unit and the communication unit in each set of equipment are connected by using a category 6 network cable, it is tested and confirmed that data can be transmitted between the two without delay, and the establishment of the data interaction channel is completed.

[0084] Secondly, by step S1022, the continuous signal stream received by the roadside communication unit is divided into multiple signal segments by the physical layer processor at a fixed time interval of 1 second, each signal segment is independently analyzed, the communication characteristic parameter set containing signal strength data and data transmission rate data is extracted, the signal stability value in unit time is calculated based on the signal strength data, the data transmission success rate value in unit time is calculated based on the data transmission rate data, the two values are respectively weighted by the weights of 0.6 and 0.4, and the weighted results are added to obtain a comprehensive score, which is the communication effective value. For example, after a roadside communication unit in area A receives the signal transmitted by a vehicle, the physical layer processor divides the signal into 60 signal segments at an interval of 1 second, analyzes the first signal segment to obtain signal strength data of -70 dBm and data transmission rate data of 10 Mbps, calculates the signal stability value corresponding to the signal segment as 0.9, the signal strength fluctuation is small, the data transmission success rate value is 0.95, most of the data is successfully transmitted, the weighted results are calculated by the weights as 0.9*0.6+0.95*0.4=0.92, which is the communication effective value corresponding to the signal segment. The communication effective values of other signal segments are calculated in turn and the average value is taken as the overall communication effective value of the period.

[0085] Then, by step S1023, the communication connection information between the roadside communication unit and the passing vehicles is obtained in real time through the established data interaction channel, the integrity of the communication connection is continuously monitored, the connection state characteristics such as whether the connection is interrupted and the connection delay duration are extracted, and the communication connection effective value is generated according to these characteristics by using a statistical analysis algorithm. For example, a roadside communication unit in area A establishes connections with 20 passing vehicles within 10 minutes, and the monitoring finds that the connection of 1 vehicle is interrupted once, the connection of 3 vehicles is delayed by more than 50 ms, and the connections of other vehicles are normal. Based on these connection state characteristics, the communication connection effective value of the period is calculated as 0.88, reflecting that the connection stability of the roadside communication unit is at a good level.

[0086] Then, by step S1024, the communication effective value obtained by step S1022 and the communication connection effective value obtained by step S1023 are input into a preset evaluation model for joint evaluation. If the evaluation result shows that the communication quality does not reach the preset standard, the communication quality parameters of the roadside communication unit are adjusted, such as increasing the signal transmission power or adjusting the transmission frequency. For example, the communication effective value of a roadside communication unit in area A is 0.85, and the communication connection effective value is 0.88. The joint evaluation model determines that the communication quality is lower than the preset standard of 0.9, so the signal transmission power of the communication unit is increased from 15 dBm to 18 dBm, and the transmission frequency is adjusted from 2.4 GHz to 5 GHz to optimize the communication effect.

[0087] Finally, the signal output characteristics of the roadside communication unit are reconfigured according to the adjusted communication quality parameters through step S1025, and the signal environment is monitored in real time by the physical layer processor, such as whether a signal interference source appears in the periphery, and the effective signal coverage area of the roadside communication unit is gradually adjusted and limited according to the monitoring results until the optimized range is determined. For example, after adjusting the communication quality parameters of a certain roadside communication unit in area A, the signal output characteristics become high power and high frequency mode, and monitoring finds that there is no new interference source in the periphery. By testing the signal reception of the test vehicle at different positions, it is determined that the effective signal coverage area of this communication unit is expanded from the original 500 meters to 800 meters, and the data transmission is stable within the range, and the dynamic definition of the effective signal coverage area is completed.

[0088] In practical application, a smart traffic enterprise is responsible for the distributed storage project of vehicle map in area A. When implementing step S102, the roads in area A are surveyed first to determine that 50 sets of roadside edge computing units and supporting roadside communication units are deployed at key positions on main road C, secondary road D and branch road E. Industrial-grade optical fibers are used to connect the edge computing unit and the communication unit of each set of equipment, and the transmission stability of the data interaction channel is tested one by one to ensure that all channels can realize real-time data transmission. Then, the physical layer processor is started to process the signals received by each communication unit, divide the signal segments at an interval of 1 second and analyze the parameters, and calculate that the initial communication effective value of each communication unit is between 0.78 and 0.85. At the same time, the connection state of each communication unit and the vehicle is monitored through the data interaction channel, and the generated communication connection effective value is between 0.82 and 0.88. After inputting the two types of values into the joint evaluation model, it is found that the communication quality of 12 sets of equipment does not meet the preset standard, and the communication quality parameters of these equipment are adjusted by the technical personnel, among which 8 sets of equipment increase the signal transmission power and 4 sets of equipment adjust the transmission frequency. After parameter adjustment, the signal environment is continuously monitored, and the effective signal coverage area of each communication unit is gradually optimized according to the situation of surrounding buildings blocking and other wireless signal interference, etc. Finally, the effective signal coverage area of all roadside communication units in area A can cover all lanes of the corresponding road, and the data transmission success rate and connection stability in the coverage area are significantly improved, laying a communication foundation for subsequent distributed storage of vehicle map data and acquisition of vehicle data.

[0089] In the overall scheme of step S102, the deployment of supporting equipment and the establishment of data interaction channels provide a hardware foundation for communication and calculation; the calculation of communication effective value and communication connection effective value accurately grasps the communication quality and connection stability; the adjustment of communication quality parameters and the dynamic definition of effective signal coverage area optimize the working state of the roadside communication unit, and finally realize the high-quality and high-stability operation of the roadside communication, providing reliable communication guarantee for the subsequent distributed storage of vehicle map data and data interaction between vehicles and roadside equipment, and ensuring that vehicles can stably obtain the required map information within the effective coverage range.

[0090] The specific implementation flowchart of the vehicle map data distributed storage method based on edge computing provided by the embodiments of the present application is shown in Figure 2 as follows, which includes the following contents:

[0091] S103, according to the physical distribution position of each roadside edge computing unit and the effective signal coverage area of the corresponding communication unit, combined with the basic road network information provided by the basic layer data, the lane line and traffic sign fine information in the detail layer data are dynamically logically sliced, and the sliced vehicle map data is distributed stored in the optimal roadside edge computing unit corresponding node to form a distributed storage network;

[0092] Optionally, step S103 can specifically include the following steps:

[0093] S1031, determine the physical distribution position of each roadside edge computing unit in the geographical space, and obtain the effective signal coverage area of each communication unit;

[0094] S1032, according to the basic road network information provided by the basic layer data, identify the key elements in the detail layer data that need to be processed, the key elements including lane line and traffic sign fine information;

[0095] S1033, according to the physical distribution position and the effective signal coverage area, logically divide the key elements to form preliminary data segments;

[0096] The step S1033 can specifically include the following processes: determining the spatial relationship between each roadside edge computing unit based on the physical distribution position, and simultaneously determining the signal area boundary of each communication unit based on the effective signal coverage area; establishing the association mapping of position and signal in combination with the spatial relationship and the signal area boundary, grouping the key elements according to the association mapping according to the signal area to which the key elements belong; performing a segmentation operation on the key elements in each group to generate data blocks, and adjusting the segmentation granularity of the data blocks according to the element attribute and distribution density; and obtaining the preliminary data segments by iteratively optimizing the segmentation boundary of the data blocks, so that the element correlation degree in each segmentation segment is maximized and the overlap between segments is minimized.

[0097] S1034, further adjusting the segments by analyzing the correlation of the preliminary data segments at different positions, so that each segment contains the most relevant lane line and traffic sign information;

[0098] S1035, selecting the optimal storage node for each data segment, comprehensively considering the storage capacity, signal reliability and physical distance of the storage node, and distributing the adjusted data segments to the corresponding roadside edge computing units to construct a distributed storage network.

[0099] In the above steps, the physical distribution position refers to the specific installation coordinates of the roadside edge computing unit in the actual geographical space; the effective signal coverage area refers to the geographical range in which the roadside communication unit can stably transmit data; the basic road network information refers to the road framework data contained in the basic layer data, including road direction, connection relationship, etc.; the detailed layer data refers to a data set containing fine information of lane lines and traffic signs; the dynamic logical slicing processing refers to a processing mode in which the detailed layer data is divided into multiple data segments according to a specific logic; the sliced vehicle-mounted map data refers to independent data segments formed after the dynamic logical slicing processing; the optimal roadside edge computing unit corresponding node refers to an edge computing node that is most suitable for storing a specific data segment, which is selected by comprehensively considering factors such as storage capacity, signal reliability and physical distance; the distributed storage network refers to a network system composed of multiple roadside edge computing unit nodes, which is used for distributed storage of vehicle-mounted map data; the key element refers to fine information of lane lines and traffic signs in the detailed layer data that needs to be processed; the preliminary data segment refers to an initial data block formed after logical division of the key element; the spatial relationship refers to the relative position association of each roadside edge computing unit in the geographical space; the signal area boundary refers to the geographical range limit of the effective signal coverage area; the correlation mapping refers to the corresponding relationship established between the physical distribution position and the signal area boundary; the data block refers to a basic data unit formed after division of the grouped key element; the division granularity refers to the size of the data block and the number of contained elements; the division boundary refers to the limit of dividing the data block; the segment adjustment refers to an optimization operation on the preliminary data segment based on the correlation of the data segment; the storage capacity refers to the capacity size of the data that can be stored by the roadside edge computing unit node; the signal reliability refers to the stability of the signal transmitted by the communication unit matched with the roadside edge computing unit; and the physical distance refers to the geographical distance between the road area corresponding to the data segment and the roadside edge computing unit node.

[0100] In the embodiment of the present application, first, the physical distribution position coordinates of all deployed roadside edge computing units in the A area are obtained by using GPS positioning technology in step S1031, and the effective signal coverage area of each roadside communication unit is detected by a signal testing device, and the geographical range of each area is recorded, for example, 10 sets of roadside edge computing units are deployed on both sides of the main road C in the A area, the coordinates of the first set of units are determined as (X1, Y1), the coordinates of the second set of units are determined as (X2, Y2), and the coordinates of the tenth set of units are determined as (X10, Y10). The effective coverage area of the first set of communication units is a circular area with (X1, Y1) as the center and a radius of 500 meters, the effective coverage area of the second set of communication units is a circular area with (X2, Y2) as the center and a radius of 550 meters, and the coverage areas of all units are recorded in sequence.

[0101] Secondly, in step S1032, basic road network information for area A is extracted from the basic layer data, including the direction and connection of main road C and secondary road D. Based on this information, key elements belonging to main road C and secondary road D, such as double yellow solid lines, lane dividers, and traffic signs such as speed limit signs and no-left-turn signs, are selected from the detailed layer data. For example, the basic road network information determines that main road C runs east-west and starts from the west. Dongzhi Based on this, all key elements such as the three-lane dividing line, the 60 km / h speed limit sign, and the no-U-turn sign within the road segment are located and extracted from the detailed layer data.

[0102] Next, based on the physical distribution of each roadside edge computing unit in step S1033, a spatial analysis algorithm is used to determine the spatial relationships, such as the distance between the first and second sets of units being 800 meters, and the distance between the second and third sets being 900 meters. Simultaneously, the signal area boundaries of each communication unit are delineated according to the effective signal coverage area. Then, the spatial relationships are combined with the signal area boundaries to establish the system where "the first set of units corresponds to the coverage of the main road C starting from the west." to The system uses a correlation mapping, such as "segment" or "segment," to group key elements according to their respective signal regions. Each group of key elements is then segmented using a data segmentation algorithm to generate data blocks. The segmentation granularity is adjusted based on element density; for example, if key elements are densely concentrated in a region, the data blocks are smaller, and if elements are sparse, the blocks are larger. Finally, an iterative optimization algorithm is used to adjust the segmentation boundaries, maximizing the correlation between elements within each data segment and minimizing overlap between segments, thus obtaining preliminary data segments. For example, the segmentation of the main road C from west to east... to The key elements of the segment are divided into two preliminary data segments. Segment 1 contains... to The lane markings and speed limit signs in segment 2. to The lane markings and no-U-turn signs in each segment should be closely related and not overlapped.

[0103] Then, in step S1034, a data association analysis algorithm is used to analyze the correlation between each preliminary data segment. For example, it is determined whether the left-turn directional arrow sign in a certain preliminary data segment is highly correlated with the left-turn lane line in the adjacent segment. If they are correlated, they are adjusted to the same data segment so that each segment contains the most relevant lane line and traffic sign information. For example, if it is found that the no-U-turn sign in preliminary data segment 2 is highly correlated with a certain lane line in segment 1, the no-U-turn sign is adjusted to segment 1. At the same time, the remaining elements in segment 2 are integrated with another adjacent segment to complete the segment adjustment.

[0104] Finally, for each adjusted data segment, the multi-factor evaluation model is used to comprehensively analyze the remaining storage space size of the storage capacity of each roadside edge computing unit node, the signal reliability (the number of signal interruptions in the past 30 days), and the physical distance (the straight-line distance between the corresponding road of the data segment and the node), and the optimal storage node is selected to store the data segment. After all data segments are allocated, a distributed storage network is constructed. For example, the distance between the corresponding road of segment 1 and the first set of edge computing unit nodes is 200 meters, the remaining storage space of the node is sufficient (500 GB), and the number of signal interruptions is one per month. Segment 1 is stored in the first set of nodes. Segment 2 is stored in the second set of nodes, which is the most suitable for the corresponding road. All segment storage is completed in sequence to form a distributed storage network for vehicle map data in region A.

[0105] In practical applications, a smart traffic technology company promotes a distributed storage project for vehicle-mounted maps in area A. When implementing step S103, the company first collects the physical distribution locations of 30 roadside edge computing units in the area using professional positioning equipment, and simultaneously tests the effective signal coverage area of each roadside communication unit using a signal analyzer to draw a geographical distribution map containing the locations and coverage of all units. Subsequently, the company extracts the road network framework of area A from the pre-processed base layer data, clearly defines the orientation and connection relationship of trunk road C, secondary trunk road D, and branch road E, and accordingly filters out key elements such as lane line types, traffic sign locations, and meanings of each road in the detail layer data, a total of over 1200 key elements. Next, based on the spatial locations and communication coverage of the edge computing units, the company establishes the association between locations and signals, divides the key elements into 30 groups according to the coverage area, each corresponding to the coverage of a set of edge computing units, and uses an adaptive segmentation algorithm to segment each group of key elements, adjusting the segmentation granularity according to the element density. The trunk road segments with dense elements are divided into data blocks containing 50-80 elements per segment, while the branch road segments with sparse elements are divided into data blocks containing 20-30 elements per segment. Through 5 rounds of iterative optimization of the segmentation boundaries, the company obtains 150 preliminary data segments. Subsequently, the company analyzes the relevance of each preliminary data segment using a data correlation model and finds that there are 28 segments with cross-segment element associations. The company adjusts and merges or splits these segments, and finally obtains 135 optimized data segments with strong relevance. Finally, the company constructs a multi-dimensional evaluation index system, evaluates and selects the optimal storage node from the 30 edge computing nodes for each data segment. For example, in the middle section of trunk road C, a data segment is determined to be the optimal node because the 8th edge computing node is only 180 meters away from the road segment, has a remaining storage capacity of 600 GB, and has had zero signal interruptions for nearly 3 months. The segment is stored in the 8th node. After all 135 data segments are allocated to the optimal nodes for storage, the distributed storage network for vehicle-mounted map data in area A is formally established. When subsequent vehicles enter the area, they can quickly obtain the required map data from the nearest node.

[0106] In the overall scheme of step S103, the accurate determination of the locations and communication coverage of the edge computing units provides a spatial basis for data slicing. The filtering of key elements and dynamic logical slicing achieve the reasonable segmentation of map detail data. The adjustment of data segments based on relevance improves the internal relevance of the data segments. The selection of optimal nodes for data storage and the construction of a distributed network achieve efficient decentralized storage of vehicle-mounted map data. The overall scheme ensures that the data storage locations are highly adaptable to actual use scenarios, providing storage support for the fast and stable acquisition of map data by subsequent vehicles, while also improving the flexibility and reliability of data storage and avoiding the risks of single-node storage.

[0107] S104, when the vehicle enters the effective signal coverage area of the roadside communication unit, obtaining the map detail slice and the basic road network information related to the current position of the vehicle from the distributed storage network based on the optimized communication quality parameters, and distributing the map detail slice and the basic road network information to the vehicle.

[0108] Optionally, step S104 can specifically include the following steps:

[0109] S1041, continuously monitoring the change of signal strength of the vehicle in the area by the roadside communication unit, and determining that the vehicle enters the effective signal coverage area when the signal strength exceeds a preset threshold value;

[0110] S1042, querying the map detail slice and the basic road network information of the corresponding position in the distributed storage network based on the current position coordinates of the vehicle;

[0111] S1043, establishing a stable data transmission channel according to the optimized communication quality parameters, and segmenting and packaging the queried map detail slice and basic road network information;

[0112] S1045, sending the packaged information to the receiving module of the vehicle through the data transmission channel, ensuring that the vehicle can obtain the required navigation information in time when entering a new area, and realizing the continuity and accuracy of vehicle navigation.

[0113] In the above steps, the effective signal coverage area is the geographical range in which the roadside communication unit can stably transmit data; the optimized communication quality parameters are the set indexes that affect the communication effect after adjustment and optimization, including signal transmission power, transmission frequency, etc.; the distributed storage network is a network system composed of multiple roadside edge computing unit nodes and dispersively storing vehicle map data; the map detail slice is a data segment containing fine information of lane lines and traffic signs after dynamic logical slicing processing; the basic road network information is the road framework data contained in the basic layer data, including road direction, connection relationship, etc.; the preset threshold value is the signal strength standard value for judging whether the vehicle enters the effective signal coverage area; the current position coordinates of the vehicle are the specific positioning data of the vehicle in the geographical space; the stable data transmission channel is a link that can smoothly transmit data based on the optimized communication quality parameters; the segmented packaging is the operation of dividing and packaging the map detail slice and the basic road network information into data packets according to a certain size; the receiving module of the vehicle is a hardware component installed on the vehicle for receiving data sent by the roadside communication unit; the navigation information is the map related data for vehicle navigation, including the map detail slice and the basic road network information.

[0114] In the embodiments of the present application, first, the signal monitoring function of the roadside communication unit is used in step S1041 to continuously receive signals emitted by passing vehicles in the area and detect the signal strength in real time. The detected signal strength is compared with a preset threshold. When the signal strength exceeds the preset threshold, it is determined that the vehicle has entered the effective signal coverage area of the roadside communication unit, for example, a certain roadside communication unit beside the main road C in area A. The preset signal strength threshold is -85 dBm. When vehicle B drives to the vicinity of the communication unit, the communication unit detects that the signal strength of vehicle B is -80 dBm, which exceeds the preset threshold, so it is determined that vehicle B has entered the effective signal coverage area.

[0115] Secondly, the current position coordinates of the vehicle are obtained by the roadside communication unit in step S1042, and the coordinates are input into the query system of the distributed storage network. The system matches the corresponding geographic area according to the coordinates, and then queries the map detail slices and basic road network information stored in the area, for example, after vehicle B enters the effective signal coverage area, the roadside communication unit obtains its current position coordinates (X1, Y1). The query system determines that the position belongs to the middle section area of main road C according to (X1, Y1), and then queries the map detail slices containing the double-yellow solid line, three-lane separation line and traffic sign speed limit 60 sign, left turn prohibited sign of the middle section lane line of main road C, and the basic road network information containing the trend of the middle section of main road C and the connection relationship with adjacent roads stored on the roadside edge computing unit node corresponding to the area.

[0116] Then, the signal transmission power and transmission frequency of the roadside communication unit are adjusted according to the optimized communication quality parameters in step S1043 to establish a stable data transmission channel between the vehicle and the roadside communication unit. At the same time, the data packaging algorithm is used to segment the queried map detail slices and basic road network information according to the size of 1 MB, and each segment of data is packaged into an independent data packet, for example, according to the optimized communication quality parameters, the signal transmission power of the roadside communication unit is adjusted to 18 dBm and the transmission frequency is adjusted to 5 GHz. It is confirmed by testing that there is no packet loss between vehicle B and the communication unit, a stable transmission channel is established, and the map detail slices with a size of 3.5 MB and the basic road network information with a size of 1.2 MB are divided into 5 data packets, the first 4 are 1 MB, and the last one is 0.7 MB.

[0117] Finally, the road side communication unit sends the packaged information to the receiving module of vehicle B in the order of data packet number through the established stable data transmission channel, and the receiving module of vehicle B receives the data packet and integrates it to obtain the complete map detail slice and basic road network information. When vehicle B continues to drive into the effective signal coverage area of the next road side communication unit, the process is repeated to ensure that vehicle B can obtain the required navigation information immediately when driving into a new area, realizing the continuity and accuracy of navigation. For example, the road side communication unit sends data packets to the receiving module of vehicle B in the order of 1-5, and the receiving module successfully receives and integrates them. The navigation system of vehicle B instantly displays the lane lines, traffic signs, and road connection information of the middle section of main road C. When vehicle B drives to the east section of main road C and enters the effective coverage area of the next road side communication unit, the data acquisition and transmission process is triggered again, and the navigation system of vehicle B seamlessly updates the navigation information of the east section of the road.

[0118] In actual application, after a smart traffic project deploys road side equipment and distributed storage network on main road C, secondary road D and branch road E in area A, it begins to test vehicle navigation data transmission. Test vehicle F drives into main road C from the west entrance of area A. During the driving process, the road side communication unit beside main road C continuously monitors the signal strength of vehicle F. When vehicle F is about 500 meters away from a road side communication unit, the communication unit detects that the signal strength is -82dBm, which exceeds the preset threshold of -85dBm, and determines that vehicle F has entered the effective signal coverage area. Then, the communication unit obtains the current position coordinates (X2, Y2) of vehicle F, queries the distributed storage network to obtain the map detail slice corresponding to the west section of main road C, which includes the west section of double yellow solid line, two-lane separation line and speed limit 50 sign, and the basic road network information, including the west section of the road, the connection relationship with branch road E. According to the optimized communication quality parameters, signal transmission power 17dBm, transmission frequency 5GHz, a stable transmission channel is established to package the map detail slice (2.8MB) and basic road network information (1.1MB) into 4 data packets with 1MB segmentation, and send them to the receiving module of vehicle F through the transmission channel. After vehicle F successfully receives and integrates the data, the navigation system accurately displays the west section of the road information. When vehicle F continues to drive east and enters the effective coverage area of the next road side communication unit, the above process is repeated, and the navigation system instantly updates the road information of the middle section of main road C. During the entire driving process, the navigation information of vehicle F is continuous and accurate, and there is no information delay or loss, verifying the effectiveness of the step scheme.

[0119] In the overall scheme of step S104, by monitoring the signal strength of the vehicle in real time and determining whether the vehicle enters the effective coverage area, it is ensured that the data transmission process can be triggered in time; by accurately querying the map data of the corresponding position in the distributed storage network, it is ensured that the vehicle can obtain the information matched with the current position; by establishing a stable transmission channel based on the optimized communication parameters and segmenting the data, the stability and efficiency of data transmission are improved; by continuously providing navigation information for vehicles entering new areas, the continuity and accuracy of vehicle navigation are realized. The overall scheme provides reliable protection for efficient and stable acquisition of map navigation information by vehicles during driving, and improves the user experience of vehicle navigation.

[0120] The following is a complete embodiment for steps S101 to S104:

[0121] As shown in Figure 3 , a smart traffic company launched a project in city A, and applied the storage method to serve the traffic network of main road C and secondary road D. First, the vehicle map data source of city A was obtained through satellite mapping and field collection, and was processed by layering with an analysis tool to separate the basic layer data containing road direction and connection relationship, and the detail layer data containing lane line position and traffic sign coordinates. Second, a roadside edge computing unit and a communication unit were deployed every 1.2 kilometers on main road C and every 1.5 kilometers on secondary road D, and a data channel was built with optical fiber. The signal was monitored by a physical layer processor to calculate the communication effective value and the connection effective value, and the parameters such as power 15dBm were adjusted to 18dBm, and the coverage area was defined as 550 meters on main road and 500 meters on secondary road with no blind area. Then, the edge unit position was determined by GPS, and the detail layer data was dynamically sliced in combination with the coverage area and the basic road network information. The granularity was adjusted according to the element density, 60-80 elements per slice on main road and 20-30 elements per slice on branch road, 120 slices were generated, and were distributed to the optimal nodes according to the storage capacity, signal reliability and distance. Finally, when vehicle B entered the coverage area of the 8th communication unit and the signal reached the threshold of -80dBm, the coordinates (X1, Y1) were obtained, the corresponding slice and basic information were queried, and were packaged into 4 data packets for transmission, and the vehicle navigation was displayed in real time; the process was repeated when the vehicle entered the next area to realize seamless update.

[0122] The vehicle map data distributed storage method based on edge computing provided by the present application improves the storage and management efficiency of data through layering processing and distributed storage of vehicle map data. The communication quality parameters are dynamically optimized and the effective signal coverage area is defined to ensure the stability and efficiency of communication between the vehicle and the roadside unit. The distributed storage network enables the vehicle to quickly obtain the required map data, improves the timeliness of data transmission, and ensures the safe and reliable operation of the autonomous vehicle.

[0123] Figure 4A structural schematic diagram of a specific embodiment of a vehicle-mounted map data distributed storage system based on edge computing provided by an embodiment of the present application is shown in FIG. 1. Figure 4 The system can include:

[0124] A hierarchical module 41 is configured to acquire a vehicle-mounted map data source and perform hierarchical processing on the vehicle-mounted map data source to separate out basic layer data containing basic road network information and detail layer data containing lane line and traffic sign fine information.

[0125] An adjustment module 42 is configured to deploy a roadside edge computing unit and a matching roadside communication unit, monitor and evaluate the communication effective value and communication connection effective value of the roadside communication unit through a physical layer processor, and adjust and optimize the communication quality parameter according to the evaluation result to dynamically define the effective signal coverage area of the roadside communication unit.

[0126] A slicing module 43 is configured to perform dynamic logical slicing processing on the lane line and traffic sign fine information in the detail layer data according to the physical distribution position of each roadside edge computing unit and the effective signal coverage area of the matching communication unit thereof, in combination with the basic road network information provided by the basic layer data, and distribute the sliced vehicle-mounted map data on the optimal roadside edge computing unit corresponding node to form a distributed storage network.

[0127] A distribution module 44 is configured to acquire the map detail slice and basic road network information related to the current position of the vehicle from the distributed storage network based on the optimized communication quality parameter when the vehicle enters the effective signal coverage area of the roadside communication unit, and distribute the map detail slice and the basic road network information to the vehicle.

[0128] The vehicle-mounted map data distributed storage system based on edge computing of the embodiment of the present application is used to implement the foregoing vehicle-mounted map data distributed storage method based on edge computing, and therefore the specific embodiments of the vehicle-mounted map data distributed storage system based on edge computing can be seen from the foregoing embodiment part of the vehicle-mounted map data distributed storage method based on edge computing, and the specific embodiments can be referred to the description of the corresponding part of the embodiment, which will not be described here.

[0129] The present application also provides an electronic device, comprising a memory for storing a computer program and a processor for executing the computer program to implement the steps of the vehicle-mounted map data distributed storage method based on edge computing.

[0130] The application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program.

[0131] In an example embodiment, the computer readable storage medium can include, but is not limited to, a U disk, a read-only memory, a random access memory, a mobile hard disk, a magnetic disk or an optical disk, and various media capable of storing a computer program.

[0132] The embodiments of the application further provide a computer program product, and the computer program product includes a computer program, and the computer program is executed by a processor to implement the steps in the above-mentioned embodiments of the edge computing-based vehicle-mounted map data distributed storage method.

[0133] The skilled person can further realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been described in general terms in the above description. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the application.

[0134] The above describes in detail the edge computing-based vehicle-mounted map data distributed storage method and system provided by the application. The principles and implementation manners of the application are described by using specific examples in this paper, and the above example description is only used to help understand the method of the application and its core idea. It should be pointed out that for ordinary skilled person in the art, without departing from the principles of the application, the application can be improved and modified in several ways, and these improvements and modifications also fall within the protection scope of the application.

Claims

1. An edge-computing-based distributed storage method for vehicle map data, characterized in that, The application relates to a vehicle-mounted map data processing method and system. The application comprises the following steps: Obtaining a vehicle-mounted map data source and performing hierarchical processing on the vehicle-mounted map data source to separate basic layer data containing basic road network information and detail layer data containing lane line and traffic sign fine information; Deploying a roadside edge computing unit and a matching roadside communication unit, monitoring and evaluating the communication effective value and communication connection effective value of the roadside communication unit through a physical layer processor, and adjusting and optimizing the communication quality parameter according to the evaluation result to dynamically define the effective signal coverage area of the roadside communication unit; According to the physical distribution position of each roadside edge computing unit and the effective signal coverage area of the matching communication unit, and in combination with the basic road network information provided by the basic layer data, performing dynamic logical slicing processing on the lane line and traffic sign fine information in the detail layer data, and distributing the sliced vehicle-mounted map data on the optimal roadside edge computing unit corresponding node to form a distributed storage network, which comprises the following steps: Determining the physical distribution position of each roadside edge computing unit in the geographical space and obtaining the effective signal coverage area of each communication unit; identifying the key elements in the detail layer data that need to be processed according to the basic road network information provided by the basic layer data, wherein the key elements include lane line and traffic sign fine information; logically dividing the key elements according to the physical distribution position and the effective signal coverage area to form preliminary data segments; adjusting the segments by analyzing the correlation of the preliminary data segments in different positions, so that each segment contains the most relevant lane line and traffic sign information; selecting the optimal storage node for each data segment, comprehensively considering the storage capacity, signal reliability and physical distance of the storage node, and distributing the adjusted data segments to the corresponding roadside edge computing unit to build a distributed storage network; 2. The method of claim 1, wherein, When a vehicle enters the effective signal coverage area of the roadside communication unit, obtaining the map detail slice and basic road network information related to the current position of the vehicle from the distributed storage network based on the optimized communication quality parameter, and distributing the map detail slice and the basic road network information to the vehicle. Logically dividing the key elements according to the physical distribution position and the effective signal coverage area to form preliminary data segments, which comprises the following steps: Based on the physical distribution position, determining the spatial relationship between each roadside edge computing unit, and simultaneously determining the signal area boundary of each communication unit based on the effective signal coverage area; Combining the spatial relationship and the signal area boundary, establishing a location-signal association mapping, and grouping the key elements according to the belonging signal area according to the association mapping; Dividing the key elements in each group to generate data blocks, and adjusting the division granularity of the data blocks according to the element attribute and distribution density; Iteratively optimizing the division boundary of the data blocks to maximize the internal element correlation degree of each division segment and minimize the overlap between segments, and obtaining the preliminary data segments.

3. The method of claim 1, wherein, The roadside edge computing unit and the matching roadside communication unit are deployed, the communication effective value and the communication connection effective value of the roadside communication unit are monitored and evaluated by the physical layer processor, and the communication quality parameters are adjusted and optimized according to the evaluation result, so as to dynamically define the effective signal coverage area of the roadside communication unit, including: The roadside edge computing unit and the matching roadside communication unit are deployed, the roadside edge computing unit is physically connected with the roadside communication unit, and a data interaction channel is established; The signals received by the roadside communication unit are segmented and analyzed by the physical layer processor, the communication effectiveness indicators are extracted, and the communication effectiveness indicators are calculated multiple times to generate a communication effective value; The integrity information of the communication connection is continuously monitored through the data interaction channel, the connection state characteristics are extracted, and the communication connection effective value is generated according to the connection state characteristics; The communication effective value and the communication connection effective value are jointly evaluated, and the communication quality parameters are adjusted and optimized according to the joint evaluation result; Through the dynamic adjustment of the communication quality parameters, the signal output characteristics of the roadside communication unit are reconfigured, and combined with the real-time change of the signal environment, the effective signal coverage area of the roadside communication unit is gradually limited and updated until the optimized signal range definition is realized.

4. The method of claim 3, wherein, The signals received by the roadside communication unit are segmented and analyzed by the physical layer processor, the communication effectiveness indicators are extracted, and the communication effectiveness indicators are calculated multiple times to generate a communication effective value, including: The continuous signal stream received by the roadside communication unit is divided into multiple signal segments at fixed time intervals, each signal segment is independently analyzed by the physical layer processor to obtain a set of communication characteristic parameters of each signal segment; The signal strength data and the data transmission rate data of each signal segment are obtained from the communication characteristic parameter set, and the signal stability value and the data transmission success rate value per unit time are calculated based on the signal strength data and the data transmission rate data; The signal stability value and the data transmission success rate value are respectively weighted, and the weighted results are fused according to the preset proportion to obtain a comprehensive score, and the communication effective value is calculated based on the comprehensive score.

5. The method of claim 1, wherein, When the vehicle enters the effective signal coverage area of the roadside communication unit, the map detail slice and the basic road network information related to the current position of the vehicle are obtained from the distributed storage network based on the optimized communication quality parameters, and the map detail slice and the basic road network information are distributed to the vehicle, including: The roadside communication unit continuously monitors the change of the signal strength of the vehicle in the region, and determines that the vehicle enters the effective signal coverage area when the signal strength exceeds the preset threshold; Based on the current position coordinates of the vehicle, the map detail slice and the basic road network information of the corresponding position in the distributed storage network are queried; According to the optimized communication quality parameters, a stable data transmission channel is established, and the queried map detail slice and basic road network information are segmented and packaged; The packaged information is sent to the vehicle's receiving module through the data transmission channel, ensuring that the vehicle can obtain the required navigation information in real time when entering a new area, thus achieving continuity and accuracy in vehicle navigation.

6. The method of claim 1, wherein, The system acquires an in-vehicle map data source and performs layered processing on the data source, separating it into a base layer containing basic road network information and a detail layer containing fine information about lane lines and traffic signs, including: Obtain vehicle map data source, extract road network related information from the vehicle map data source, analyze the road network related information to identify basic structural elements, and combine the basic structural elements into basic layer data; Simultaneously, information elements related to lane lines and traffic signs are identified from the vehicle map data source, and these information elements are further analyzed in detail to form detailed layer data. The initial base layer data and detail layer data are filtered to remove redundant information and ensure the accuracy of the data hierarchy. By reconstructing the data, the filtered information is integrated into the corresponding levels, thus completing the separation and construction of basic layer data and detailed layer data.

7. An edge computing-based vehicle-mounted map data distributed storage system for performing the edge computing-based vehicle-mounted map data distributed storage method of any one of claims 1-6. include: The layering module is used to acquire vehicle map data sources and perform layering processing on the vehicle map data sources, separating basic layer data containing basic road network information and detailed layer data containing lane lines and traffic sign fine information. The adjustment module is used to deploy roadside edge computing units and supporting roadside communication units. It monitors and evaluates the effective communication value and effective communication connection value of the roadside communication units through the physical layer processor, and adjusts and optimizes the communication quality parameters according to the evaluation results to dynamically define the effective signal coverage area of ​​the roadside communication units. The slicing module is used to dynamically and logically slice the lane lines and traffic sign details in the detail layer data based on the physical distribution location of each roadside edge computing unit and the effective signal coverage area of ​​its supporting communication unit, combined with the basic road network information provided by the basic layer data. The sliced ​​vehicle map data is then distributed and stored on the corresponding nodes of the optimal roadside edge computing units to form a distributed storage network. The distribution module is used to obtain map detail slices and basic road network information related to the vehicle's current location from the distributed storage network based on optimized communication quality parameters when the vehicle enters the effective signal coverage area of ​​the roadside communication unit, and distribute the map detail slices and basic road network information to the vehicle.

8. An electronic device, comprising: include: Memory, used to store computer programs; A processor, configured to implement the steps of the edge computing-based distributed storage method for vehicle map data as described in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, enables the implementation of the distributed storage method for vehicle map data based on edge computing as described in any one of claims 1 to 6.

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