Map management system, map management device, and storage medium

Abstract

Provided are a map management system, a map management device, and a storage medium that can improve the consistency, uniformity, traceability, and usability of map data. The map management system includes a cloud server having a first processor configured to manage map data for a predetermined region, an edge server having a second processor configured to manage map data for a region, and a vehicle having a third processor configured to collect raw data for updating the map data while traveling. Map update data generated based on the raw data is shared in the cloud server and the edge server for each region, and an update history of the map data based on the map update data is respectively accumulated in the cloud server and the edge server to form a plurality of blockchains.

Description

Technical Field

[0001] This disclosure relates to map management systems, map management devices, and storage media. Background Technology

[0002] Patent document 1 discloses a technique for using blockchain (distributed ledger technology) to manage the updates of map data.

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: U.S. Patent Application Publication No. 2020 / 0042012 Summary of the Invention

[0006] The problem that the invention aims to solve

[0007] In the technology disclosed in Patent Document 1, because a blockchain is used to manage the updates of map data for the entire region, the data update speed is slow and the availability is low. Furthermore, since this technology primarily emphasizes data consistency and uniformity, issues arise such as unclear sources of map data, resulting in low data traceability. Therefore, there is a need for technologies that can improve the consistency, uniformity, traceability, and availability of map data.

[0008] This disclosure is made in view of the foregoing and is intended to provide a map management system, map management device, and map management program that can improve the consistency, uniformity, traceability, and usability of map data.

[0009] Methods for solving problems

[0010] The map management system disclosed herein comprises: a cloud server having a first processor configured to manage map data of a pre-defined region; an edge server having a second processor configured to manage map data of the region; and a vehicle having a third processor configured to collect raw data for updating the map data while in motion. By sharing map update data generated based on the raw data in the cloud server and the edge server for each region, and accumulating the update history of the map data based on the map update data in the cloud server and the edge server respectively, multiple blockchains are formed.

[0011] The map management device disclosed herein includes a processor configured to manage map data for a pre-defined region. The processor, for each region, shares map update data generated based on raw data obtained from moving vehicles between a cloud server managing the map data for that region and other edge servers managing the map data for that region, and together with the cloud server and the other edge servers, accumulates the map data update history based on the map update data, thereby forming multiple blockchains.

[0012] The storage medium of this disclosure stores a map management program that enables a processor configured to manage map data for a predefined region to perform the following steps: sharing map update data generated based on raw data obtained from moving vehicles between a cloud server managing the map data for the region and other edge servers managing the map data for the region for each region, and accumulating, together with the cloud server and the other edge servers, the map update history based on the map update data to form multiple blockchains.

[0013] Invention Effects

[0014] According to this disclosure, the consistency, uniformity, traceability and availability of map data can be improved. Attached Figure Description

[0015] Figure 1 This is a diagram that schematically illustrates the structure of a map management system according to an implementation method.

[0016] Figure 2 This is a diagram that schematically illustrates the processing flow of a map management system according to an implementation method.

[0017] Figure 3 This is a block diagram showing details of the constituent elements of a map management system according to an embodiment.

[0018] Figure 4 This is a flowchart illustrating a first example of an information provision method performed by a map management system according to an embodiment.

[0019] Figure 5 This is a flowchart illustrating a second example of an information provision method performed by a map management system according to an embodiment.

[0020] Figure 6 This is a flowchart illustrating a third example of an information provision method performed by a map management system according to an embodiment.

[0021] Label Explanation

[0022] 1. Map Management System

[0023] 10 cloud servers

[0024] 11 Control Department

[0025] 111 Map Data Update Department

[0026] 12 Ministry of Communications

[0027] 13 Storage Department

[0028] 131 Local Map DB

[0029] 132 Map Update History

[0030] 20 edge servers

[0031] 21 Control Department

[0032] 211 Updated Judgment Department

[0033] 212 Update Data Generation Department

[0034] 213 Map Data Update Department

[0035] 214 Map Data Distribution Department

[0036] 22 Ministry of Communications

[0037] 23 Storage Department

[0038] 231 Local Map DB

[0039] 232 Map Update History

[0040] 30 vehicles

[0041] 31 Control Department

[0042] 311 Data Collection Department

[0043] 32 Ministry of Communications

[0044] 33 Storage Department

[0045] 34 sensor groups

[0046] NW Network Detailed Implementation

[0047] While referring to the appendix Figure 1 The map management system, map management device, and map management program according to embodiments of the present disclosure will be described below. It should be noted that the constituent elements in the following embodiments include constituent elements that can be substituted and are easily substituted by those skilled in the art, or substantially the same constituent elements.

[0048] The map management system, map management device, and map management program implemented in this manner manage the updates of high-definition maps (HD maps) using multiple blockchains. In services utilizing data from this HD map (hereinafter referred to as "map data"), for example, raw data (image data, sensor data, etc.) related to the road being traveled is collected from vehicles, and changes to the road are automatically detected based on this data. Then, map data reflecting these road changes is distributed to vehicles traveling on that road.

[0049] (Map Management System)

[0050] While referring to Figures 1-3 The map management system of this embodiment will be described below. Figure 1 As shown, the map management system 1 includes a cloud server 10, an edge server 20, and a vehicle 30. Specifically, the map management device in this embodiment is implemented by the functions of the edge server 20. The cloud server 10, the edge server 20, and the vehicle 30 all have communication capabilities and are configured to communicate with each other via a network NW. This network NW may be, for example, an internet connection network or a mobile phone connection network.

[0051] In the map management system 1, for example... Figure 2 As shown, data exchange occurs between multiple cloud servers 10 (cloud servers A and B), multiple edge servers 20 (edge ​​servers C, D, and E), and multiple vehicles 30 (vehicles F, G, H, and I). In this diagram, cloud server A, edge server C, and edge server D manage the updating of map data in region X. Additionally, cloud server B, edge server D, and edge server E manage the updating of map data in region Y. Furthermore, edge computing and blockchain are used to manage map data updates for each region X and Y.

[0052] In this scenario, for example, vehicle F traveling in region X sends raw data collected from the roads to edge server C, which has a corresponding connection with region X (output). Edge server C then generates map update data based on the raw data and sends this map update data to edge server D and cloud server A, both of which have corresponding connections with region X. Similarly, vehicle G traveling in region X sends raw data collected from the roads to edge server D, and edge server D sends the generated map update data to edge server C and cloud server A.

[0053] Additionally, for example, vehicle H traveling in region Y will send the raw data collected from the roads to edge server D, which has a corresponding connection with region Y. Edge server D will then generate map update data based on the raw data and send this map update data to edge server E and cloud server B, both of which have corresponding connections with region Y. Similarly, vehicle I traveling in region Y will send the raw data collected from the roads to edge server E, and edge server E will send the generated map update data to edge server D and cloud server B.

[0054] Thus, in the map management system 1, map update data is shared between the cloud server 10 and the edge server 20 for each region, and the update history of the map data (local map DB) based on this map update data is stored separately in the cloud server 10 and the edge server 20, thereby forming multiple blockchains B1 and B2. That is, in the map management system 1, instead of using a single blockchain to manage the updates of map data for all regions as in the past, multiple blockchains are formed, with each blockchain managing the updates of map data for a portion of the regions.

[0055] It should be noted that, in Figure 2 In the example shown, a blockchain is constructed using one cloud server 10, but multiple blockchains can also be constructed using one cloud server 10. Furthermore, in this example, one cloud server 10 is associated with one region, but one cloud server 10 can also be associated with multiple regions.

[0056] In addition, Figure 2 In the example, the number of cloud servers 10 and edge servers 20 constituting blockchains B1 and B2 is fixed, but it can be dynamically changed, for example, based on the update frequency of map data. In this case, for example, if the update frequency of map data in the cloud servers 10 and edge servers 20 constituting blockchains B1 and B2 exceeds a preset threshold, the number of cloud servers 10 and edge servers 20 constituting blockchains B1 and B2 is reduced. On the other hand, if the update frequency of map data in the cloud servers 10 and edge servers 20 constituting blockchains B1 and B2 is below the threshold, the number of cloud servers 10 and edge servers 20 constituting blockchains B1 and B2 is increased. By dynamically changing the number of cloud servers 10 and edge servers 20 constituting blockchains B1 and B2 according to the update frequency of map data, the communication cost between cloud servers 10, edge servers 20, and vehicle 30 can be optimized.

[0057] (Cloud server)

[0058] The cloud server 10 is used to manage map data for a pre-defined region. The cloud server 10 is implemented by a general-purpose computer such as a workstation or personal computer. In addition, the cloud server 10 includes a control unit (first processor) 11, a communication unit 12, and a storage unit 13.

[0059] Specifically, the control unit 11 includes a processor such as a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or a FPGA (Field-Programmable Gate Array), and a memory (main storage unit) such as RAM (Random Access Memory) or ROM (Read Only Memory). The control unit 11 loads and executes a program stored in the storage unit 13 into the working area of ​​the main storage unit, and controls each component through program execution, thereby achieving functions consistent with the intended purpose. The control unit 11 functions as a map data update unit 111 through the execution of the program stored in the storage unit 13.

[0060] The map data update unit 111 updates the local map DB 131 based on map update data obtained from the edge server 20, which constitutes the same blockchain. Additionally, the map data update unit 111 stores this update history as map update history 132 in the storage unit 13. By utilizing blockchain to share map update data and map data update history among the cloud server 10 and multiple edge servers 20, the consistency, uniformity, traceability, and availability of map data can be improved.

[0061] The communication unit 12 is composed, for example, of a LAN (Local Area Network) interface board and a wireless communication circuit for wireless communication. The communication unit 12 is connected to a network NW, such as the Internet, which is a public communication network. Furthermore, the communication unit 12 communicates with the edge server 20 and the vehicle 30 through its connection to this network NW.

[0062] Storage unit 13 comprises recording media such as EPROM (Erasable Programmable ROM), hard disk drive (HDD), and removable media. Examples of removable media include USB (Universal Serial Bus) memory, CD (Compact Disc), DVD (Digital Versatile Disc), and BD (Blu-ray Disc). Storage unit 13 can store operating systems (OS), various programs, various tables, various databases, etc.

[0063] The storage unit 13 stores a local map DB 131 and a map update history 132. The local map DB 131 is, for example, a relational database that stores map data corresponding to regions established with the cloud server 10 in a traceable manner. The map update history 132 is information related to the update history of the local map DB 131 based on map update data obtained from the edge server 20, which constitutes the same blockchain.

[0064] (Edge Server)

[0065] Edge server 20 is used to manage map data for a predefined geographical area. Edge server 20 is implemented by a general-purpose computer such as a workstation or personal computer. In addition, in map management system 1, multiple bases (map data distribution bases) are set up in geographically separated locations, and an edge server 20 is set up at each base.

[0066] The edge server 20 includes a control unit (second processor) 21, a communication unit 22, and a storage unit 23. The structure of the communication unit 22 and the storage unit 23 is the same as that of the communication unit 12 and the storage unit 13 of the cloud server 10. The control unit 21 functions as an update determination unit 211, an update data generation unit 212, a map data update unit 213, and a map data distribution unit 214 by executing programs stored in the storage unit 23.

[0067] The update determination unit 211 determines whether a map data update is needed. For example, if the update determination unit 211 detects changes in the roads of a region based on raw data obtained from vehicle 30, it determines that a map data update for that region is needed. Additionally, the update determination unit 211 determines that a map data update for a region is needed, for example, if the map data for a certain region has not been updated for a certain period. Furthermore, the update determination unit 211 determines that a map data update for that region is needed, for example, if it obtains information from vehicle 30 indicating that an obstacle or accident has occurred in a certain region.

[0068] Here, the update determination unit 211 can also request the transmission of raw data from the vehicle 30 traveling in a certain area if the map data of a certain area has not been updated for a certain period of time or if information indicating that an obstacle or accident has occurred in a certain area is obtained from the vehicle 30. By using the request from the edge server 20 as a trigger to obtain raw data from the vehicle 30, map update data can be generated only when needed, thus reducing the processing load on the edge server 20.

[0069] The update data generation unit 212 generates map update data based on the original data obtained from vehicle 30. Then, the update data generation unit 212 sends the generated map update data to the edge server 20 and cloud server 10, which constitute the same blockchain. It should be noted that the map update data may also include information related to the vehicle 30, the source of the original data, and the edge server 20, the source of the map update data. By including this information related to the vehicle 30, the source of the original data, and the edge server 20, the traceability of the map data can be improved.

[0070] Map data update unit 213 updates the local map DB 231 based on map update data generated by update data generation unit 212. Additionally, map data update unit 213 updates the local map DB 231 based on map update data obtained from edge servers 20 that constitute the same blockchain. Furthermore, map data update unit 213 stores the current update history as map update history 232 in storage unit 23. By utilizing blockchain to share map update data and map data update history among cloud server 10 and multiple edge servers 20, the consistency, uniformity, traceability, and availability of map data can be improved.

[0071] Map data distribution unit 214 sends map data of the corresponding region to vehicle 30 according to the request from vehicle 30. As a result, vehicle 30 is able to obtain the latest map data of the region it is traveling in.

[0072] The storage unit 23 stores a local map DB 231 and a map update history 232. The local map DB 231 is, for example, a relational database that stores map data corresponding to regions established with the edge server 20 in a traceable manner. The map update history 232 is information related to the update history of the local map DB 231 based on map update data obtained from the edge server 20, which constitutes the same blockchain.

[0073] (vehicle)

[0074] Vehicle 30 is a mobile entity capable of communicating with the outside world. While traveling on a road, vehicle 30 collects raw data for updating map data related to that road.

[0075] The vehicle 30 includes a control unit (third processor) 31, a communication unit 32, a storage unit 33, and a sensor group 34. The control unit 31 is an ECU (Electronic Control Unit) that comprehensively controls the operation of various components installed in the vehicle 30. The control unit 31 functions as a data collection unit 311 by executing programs stored in the storage unit 33.

[0076] The data collection unit 311 collects raw data using the sensor array 34 while the vehicle 30 is in motion. Examples of information collected by the data collection unit 311 include road images (videos) surrounding the vehicle 30, sensor data, CAN data, and in-vehicle images (videos). The data collection unit 311 then sends the raw data collected during the vehicle 30's operation to the edge server 20, which manages map data for the corresponding region.

[0077] It should be noted that vehicle 30 determines the edge server 20 it communicates with, for example, based on a pre-stored or acquired routing table. This "routing table" represents the region and the corresponding edge server 20 associated with that region, used to determine the edge server 20 that vehicle 30 communicates with. The routing table is either pre-stored by vehicle 30 or obtained from the edge server 20 or cloud server 10 associated with that region when entering it.

[0078] Here, the data collection unit 311 can also send raw data to the edge server 20 according to a request from the edge server 20. By using a request from the edge server 20 as a trigger to send raw data from the vehicle 30, raw data can be sent only when needed, thus reducing the communication cost between the vehicle 30 and the edge server 20 and the processing load of the vehicle 30.

[0079] In addition, the data collection unit 311 can also determine whether an update to the map data in the edge server 20 is needed based on a pre-set benchmark. If an update to the map data is needed, the raw data is sent to the edge server 20. By sending raw data only when an update to the map data in the edge server 20 is needed, the communication cost between the vehicle 30 and the edge server 20 and the processing load of the vehicle 30 can be reduced.

[0080] It should be noted that, even if a vehicle 30 determines that a map data update is needed and sends raw data from the vehicle 30 to the edge server 20, the update determination unit 211 of the edge server 20 may again determine whether a map data update is needed. For example, consider the following scenario: multiple vehicles 30 determine that a map data update is needed for roads in a specific region, and these vehicles 30 send raw data to the edge server 20. In this case, the update determination unit 211 determines that a map data update is needed if the number of vehicles 30 that sent raw data is a predetermined number or more (e.g., 20 or more). By receiving raw data from many vehicles 30 and updating the map data only when the necessity for updating the map data is high, the processing load on the edge server 20 can be reduced.

[0081] Furthermore, this explanation assumes that only raw data is collected on the vehicle 30 side and map update data is generated on the edge server 20 side, but map update data can also be generated on the vehicle 30 side. In this case, the control unit 31 generates map update data based on the raw data collected during driving and sends the map update data to the edge server 20, which manages the map data for the corresponding region. Then, the control unit 21 of the edge server 20 sends the map update data obtained from the vehicle 30 to both the edge server 20 and the cloud server 10, which constitute the same blockchain.

[0082] Accepting this situation, the map data update unit 213 of the edge server 20, which obtained map update data from the edge server 20 constituting the same blockchain, updates the map data based on this map update data. In addition, the map data update unit 213 stores the update history at this time as map update history 232 in the storage unit 23.

[0083] Furthermore, the map data update unit 111 of the cloud server 10, which obtains map update data from the edge server 20 constituting the same blockchain, updates the map data based on this map update data. Additionally, the map data update unit 111 stores the current update history as map update history 132 in the storage unit 13. By generating map update data on the vehicle 30 side in this way, it is unnecessary to generate map update data in the edge server 20, thus reducing the processing load on the edge server 20.

[0084] The communication unit 32 is composed of, for example, a DCM (Data Communication Module), and communicates with the cloud server 10 and the edge server 20 via wireless communication through the network NW. The storage unit 33 stores, as needed, raw data collected by the vehicle 30, map data obtained from the edge server 20, etc.

[0085] The sensor group 34 comprises, for example, a vehicle speed sensor, an acceleration sensor, a GPS sensor, a driving space sensor (3D-LiDAR), a millimeter-wave sensor, a camera (imaging device), a temperature sensor, a humidity sensor, and a barometric pressure sensor. The sensor group 34 outputs the detected raw data to the data collection unit 311.

[0086] (Map Management Methods (First Example))

[0087] While referring to Figure 4 The first example of the processing steps of the map management method executed by the map management system 1 of the embodiment will be described. Here, the process of actively sending raw data from vehicle 30 to edge server 20 and generating map update data in edge server 20 will be described. In addition, the following envisions... Figure 2 The processing in "Blockchain B1" of the two blockchains shown will be explained. Therefore, cloud server 10 will be referred to as "cloud server A", one of the two edge servers 20 will be referred to as "edge server C", and the other of the two edge servers 20 will be referred to as "edge server D" for explanation.

[0088] First, the data collection unit 311 of the vehicle 30 collects raw data while driving (step S1) and sends the raw data to the edge server C (step S2). Next, the update determination unit 211 of the edge server C determines whether map data updates are needed (step S3).

[0089] If it is determined that map data updates are not needed (No in step S3), the update determination unit 211 returns to step S3. On the other hand, if it is determined that map data updates are needed (Yes in step S3), the update data generation unit 212 generates map update data based on the original data (step S4). Then, the update data generation unit 212 sends the map update data to the edge server D and cloud server A, which are contained in the same blockchain B1 (step S5).

[0090] Next, the map data update unit 213 of edge servers C and D updates the local map DB231 (steps S6 and S7). Additionally, the map data update unit 111 of cloud server A updates the local map DB131 (step S8).

[0091] Next, the map data update unit 213 of edge servers C and D saves the map update history 232 to the storage unit 23 (steps S9 and S10). Additionally, the map data update unit 111 of cloud server A saves the map update history 132 to the storage unit 13 (step S11). This process concludes.

[0092] (Map Management Methods (Second Example))

[0093] While referring to Figure 5 A second example of the processing steps of the map management method executed by the map management system 1 of the embodiment will be described. Here, the processing of the case where raw data is sent from vehicle 30 to edge server 20 according to a request from edge server 20 and map update data is generated in edge server 20 will be described. In addition, the following envisions... Figure 2 The processing in "Blockchain B1" of the two blockchains shown will be explained. Therefore, cloud server 10 will be referred to as "cloud server A", one of the two edge servers 20 will be referred to as "edge server C", and the other of the two edge servers 20 will be referred to as "edge server D" for explanation.

[0094] First, the data collection unit 311 of the vehicle 30 collects raw data while driving (step S11). Next, the update determination unit 211 of the edge server C determines whether map data updates are needed (step S12).

[0095] If it is determined that map data updates are not needed (No in step S12), the update determination unit 211 returns to step S12. On the other hand, if it is determined that map data updates are needed (Yes in step S12), the update determination unit 211 requests raw data from vehicle 30 (step S13). If this is accepted, the data collection unit 311 sends the raw data to the edge server C (step S14).

[0096] Next, the update data generation unit 212 generates map update data based on the original data (step S15). Then, the update data generation unit 212 sends the map update data to the edge server D and cloud server A contained in the same blockchain B1 (step S16).

[0097] Next, the map data update unit 213 of edge servers C and D updates the local map DB231 (steps S17 and S18). Additionally, the map data update unit 111 of cloud server A updates the local map DB131 (step S19).

[0098] Next, the map data update unit 213 of edge servers C and D saves the map update history 232 to the storage unit 23 (steps S20 and S21). Additionally, the map data update unit 111 of cloud server A saves the map update history 132 to the storage unit 13 (step S22). This process concludes.

[0099] (Map Management Methods (Third Example))

[0100] While referring to Figure 6 A third example of the processing steps of the map management method executed by the map management system 1 of the embodiment will be described. Here, the process of generating map update data based on the original data on the vehicle 30 side will be described. In addition, the following envisions... Figure 2 The processing in "Blockchain B1" of the two blockchains shown will be explained. Therefore, cloud server 10 will be referred to as "cloud server A", one of the two edge servers 20 will be referred to as "edge server C", and the other of the two edge servers 20 will be referred to as "edge server D" for explanation.

[0101] First, the data collection unit 311 of the vehicle 30 collects raw data while driving (step S31). Next, the control unit 31 determines whether map data updates are needed (step S32).

[0102] If it is determined that map data updates are not needed (No in step S32), the control unit 31 returns to step S32. On the other hand, if it is determined that map data updates are needed (Yes in step S32), the control unit 31 generates map update data based on the original data (step S33). Then, the control unit 31 sends the map update data to the edge server C (step S34). Next, the update data generation unit 212 of the edge server C sends the map update data to the edge server D and cloud server A, which are contained in the same blockchain B1 (step S35).

[0103] Next, the map data update unit 213 of edge servers C and D updates the local map DB231 (steps S36 and S37). Additionally, the map data update unit 111 of cloud server A updates the local map DB131 (step S38).

[0104] Next, the map data update unit 213 of edge servers C and D saves the map update history 232 to the storage unit 23 (steps S39 and S40). Additionally, the map data update unit 111 of cloud server A saves the map update history 132 to the storage unit 13 (step S41). This process concludes.

[0105] As described above, the map management system 1, information providing device, and information providing program according to the embodiments can improve the consistency, uniformity, traceability, and availability of map data by utilizing edge computing and blockchain to manage map data updates.

[0106] Furthermore, in the past, since road data was collected using dedicated data collection vehicles instead of ordinary vehicles, and map update data was generated and updated offline, map data update frequencies were sometimes measured in months or years. On the other hand, according to the map management system 1, information providing device, and information providing program of the embodiment, since road data is collected using ordinary vehicles 30, and map update data is generated and updated online, updates can be performed immediately when map data updates are needed.

[0107] Further effects and variations can be readily derived by those skilled in the art. Therefore, the broader scope of the invention is not limited to the specific details and representative embodiments shown and described above. Consequently, various modifications can be made without departing from the spirit or scope of the invention as defined by the appended claims and their equivalents.

Claims

1. A map management system, comprising: A cloud server, having a first processor configured to manage map data for a pre-defined region; An edge server having a second processor configured to manage map data for the region; and The vehicle is equipped with a third processor configured to collect raw data for updating the map data while in motion. By sharing map update data generated from the original data across the cloud server and the edge server for each region, and accumulating the map data update history based on the map update data in both the cloud server and the edge server, multiple blockchains are formed. The third processor outputs the raw data collected during the vehicle's movement to an edge server that manages the map data for the corresponding region. The second processor generates the map update data based on the raw data obtained from the vehicle, and outputs the map update data to the edge servers and cloud servers that constitute the same blockchain. The second processor updates the map data based on the map update data obtained from the edge server constituting the same blockchain, and accumulates the update history of the map data. The first processor updates the map data based on the map update data obtained from the edge server constituting the same blockchain, and accumulates the update history of the map data. The number of cloud servers and edge servers constituting the blockchain changes dynamically based on the update frequency of the map data. If the update frequency of the map data in the cloud servers and edge servers constituting the blockchain exceeds a preset threshold, the number of cloud servers and edge servers constituting the blockchain will be reduced. When the update frequency of the map data in the cloud servers and edge servers constituting the blockchain is below the threshold, the number of cloud servers and edge servers constituting the blockchain is increased.

2. The map management system according to claim 1, The second processor requests the original data from vehicles traveling in areas where the map data has not been updated for a certain period of time. The third processor outputs the raw data to the edge server according to the request from the edge server.

3. The map management system according to claim 1, The third processor determines whether the map data needs to be updated based on a pre-set benchmark. When the third processor determines that the map data needs to be updated, it outputs the original data to the edge server.

4. The map management system according to any one of claims 1 to 3, The second processor outputs map data of the corresponding region to the vehicle according to the request from the vehicle.

5. The map management system according to any one of claims 1 to 3, The map update data includes information related to the source of the original data and the source of the map update data.

6. A map management system, comprising: A cloud server has a first processor configured to manage map data for a pre-defined region; An edge server having a second processor configured to manage map data for the region; and The vehicle is equipped with a third processor configured to collect raw data for updating the map data while in motion. By sharing map update data generated from the original data across the cloud server and the edge server for each region, and accumulating the map data update history based on the map update data in both the cloud server and the edge server, multiple blockchains are formed. The third processor generates the map update data based on the raw data collected during driving, and outputs the map update data to the edge server that manages the map data of the corresponding region. The second processor outputs the map update data to the edge servers and cloud servers that constitute the same blockchain. The second processor updates the map data based on the map update data obtained from the edge server constituting the same blockchain, and accumulates the update history of the map data. The first processor updates the map data based on the map update data obtained from the edge server constituting the same blockchain, and accumulates the update history of the map data. The number of cloud servers and edge servers constituting the blockchain changes dynamically based on the update frequency of the map data. If the update frequency of the map data in the cloud servers and edge servers constituting the blockchain exceeds a preset threshold, the number of cloud servers and edge servers constituting the blockchain will be reduced. When the update frequency of the map data in the cloud servers and edge servers constituting the blockchain is below the threshold, the number of cloud servers and edge servers constituting the blockchain is increased.

7. The map management system according to claim 6, The second processor outputs map data of the corresponding region to the vehicle according to the request from the vehicle.

8. The map management system according to claim 6 or 7, The map update data includes information related to the source of the original data and the source of the map update data.

9. A map management device, It has a processor configured to manage map data for a pre-defined region. The processor, for each region, shares map update data generated based on raw data obtained from moving vehicles between a cloud server managing the map data for that region and other edge servers managing the map data for that region, and accumulates the map data update history based on the map update data together with the cloud server and the other edge servers, thereby forming multiple blockchains. The processor generates the map update data based on the raw data obtained from the vehicle, and outputs the map update data to the edge servers and cloud servers that constitute the same blockchain. The processor updates the map data based on the map update data obtained from edge servers that constitute the same blockchain, and accumulates the update history of the map data. The number of cloud servers and edge servers constituting the blockchain changes dynamically based on the update frequency of the map data. If the update frequency of the map data in the cloud servers and edge servers constituting the blockchain exceeds a preset threshold, the number of cloud servers and edge servers constituting the blockchain will be reduced. When the update frequency of the map data in the cloud servers and edge servers constituting the blockchain is below the threshold, the number of cloud servers and edge servers constituting the blockchain is increased.

10. The map management device according to claim 9, The processor requests the original data from vehicles traveling in areas where the map data has not been updated for a certain period of time.

11. The map management device according to claim 9 or 10, The processor outputs map data of the corresponding region to the vehicle according to the request from the vehicle.

12. The map management device according to claim 9 or 10, The map update data includes information related to the source of the original data and the source of the map update data.

13. A map management device, It has a processor configured to manage map data for a pre-defined region. The processor, for each region, shares map update data generated based on raw data obtained from moving vehicles between a cloud server managing the map data for that region and other edge servers managing the map data for that region, and accumulates the map data update history based on the map update data together with the cloud server and the other edge servers, thereby forming multiple blockchains. The processor obtains the map update data from the vehicle. The processor outputs the map update data to edge servers and cloud servers that constitute the same blockchain. The processor updates the map data based on the map update data obtained from the edge servers that constitute the same blockchain, and accumulates the update history of the map data. The number of cloud servers and edge servers constituting the blockchain changes dynamically based on the update frequency of the map data. If the update frequency of the map data in the cloud servers and edge servers constituting the blockchain exceeds a preset threshold, the number of cloud servers and edge servers constituting the blockchain will be reduced. When the update frequency of the map data in the cloud servers and edge servers constituting the blockchain is below the threshold, the number of cloud servers and edge servers constituting the blockchain is increased.

14. The map management device according to claim 13, The processor outputs map data of the corresponding region to the vehicle according to the request from the vehicle.

15. The map management device according to claim 13 or 14, The map update data includes information related to the source of the original data and the source of the map update data.

16. A storage medium storing a map management program that causes a processor configured to manage map data of a predefined region to perform the following steps: By sharing map update data generated from raw data obtained from moving vehicles among cloud servers and other edge servers that manage map data for each region, and accumulating map data update history based on the map update data together with the cloud servers and other edge servers, multiple blockchains are formed. The map update data is generated based on the raw data obtained from the vehicle, and then output to edge servers and cloud servers that constitute the same blockchain. The map data is updated based on map update data obtained from edge servers that constitute the same blockchain, and the update history of the map data is accumulated. The number of cloud servers and edge servers constituting the blockchain changes dynamically based on the update frequency of the map data. If the update frequency of the map data in the cloud servers and edge servers constituting the blockchain exceeds a preset threshold, the number of cloud servers and edge servers constituting the blockchain will be reduced. When the update frequency of the map data in the cloud servers and edge servers constituting the blockchain is below the threshold, the number of cloud servers and edge servers constituting the blockchain is increased.

17. The storage medium of claim 16, wherein the map management program causes the processor to perform the following steps: The original data is required for vehicles traveling in areas where the map data has not been updated for a certain period of time.

18. The storage medium according to claim 16 or 17, wherein the map management program causes the processor to perform the following steps: Map data of the corresponding region is output to the vehicle according to the request from the vehicle.

19. The storage medium according to claim 16 or 17, The map update data includes information related to the source of the original data and the source of the map update data.

20. A storage medium storing a map management program that causes a processor configured to manage map data of a predefined region to perform the following steps: By sharing map update data generated from raw data obtained from moving vehicles among cloud servers and other edge servers that manage map data for each region, and accumulating map data update history based on the map update data together with the cloud servers and other edge servers, multiple blockchains are formed. Obtain the map update data from the vehicle. The map update data is output to edge servers and cloud servers that constitute the same blockchain. The map data is updated based on map update data obtained from edge servers that constitute the same blockchain, and the update history of the map data is accumulated. The number of cloud servers and edge servers constituting the blockchain changes dynamically based on the update frequency of the map data. If the update frequency of the map data in the cloud servers and edge servers constituting the blockchain exceeds a preset threshold, the number of cloud servers and edge servers constituting the blockchain will be reduced. When the update frequency of the map data in the cloud servers and edge servers constituting the blockchain is below the threshold, the number of cloud servers and edge servers constituting the blockchain is increased.

21. The storage medium of claim 20, wherein the map management program causes the processor to perform the following steps: Map data of the corresponding region is output to the vehicle according to the request from the vehicle.

22. The storage medium according to claim 20 or 21, The map update data includes information related to the source of the original data and the source of the map update data.

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