Map updating method and device, electronic equipment and storage medium

Abstract

The present disclosure provides a map updating method, relates to the technical field of artificial intelligence, and particularly relates to the technical field of electronic map and the technical field of intelligent transportation. A specific implementation scheme is as follows: obtaining road name text data from text data corresponding to point of interest data; determining at least one road sign according to local map data corresponding to the point of interest data, wherein the local map data corresponds to a target region, and the target region is in a target map; in response to determining that the at least one road sign and the road name text are both unmatched, determining target road data from the local map data; and generating an updated road sign of the target road data according to the road name text data, so as to update the target map. The present disclosure also provides a map updating device, an electronic device and a storage medium.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of artificial intelligence, in particular to the field of electronic map and the field of intelligent transportation, and can be applied to the image processing scenario. More specifically, the present disclosure provides a map updating method and device, an electronic device and a storage medium. BACKGROUND

[0002] With the development of artificial intelligence technology, the application scenarios of electronic maps are increasing. Road test data can be collected by vehicles equipped with collection devices. According to the road test data, the road identification of the road in the electronic map can be determined. SUMMARY

[0003] The present disclosure provides a map updating method, device, equipment and storage medium.

[0004] According to an aspect of the present disclosure, a map updating method is provided, which includes: obtaining road name text data from text data corresponding to point of interest data; determining at least one road identification according to local map data corresponding to the point of interest data, wherein the local map data corresponds to a target area in a target map; in response to determining that the at least one road identification does not match the road name text, determining target road data from the local map data; and generating an updated road identification of the target road data according to the road name text data to update the target map.

[0005] According to another aspect of the present disclosure, a map updating device is provided, which includes: an obtaining module configured to obtain road name text data from text data corresponding to point of interest data; a first determining module configured to determine at least one road identification according to local map data corresponding to the point of interest data, wherein the local map data corresponds to a target area in a target map; a second determining module configured to determine target road data from the local map data in response to determining that the at least one road identification does not match the road name text; and a generating module configured to generate an updated road identification of the target road data according to the road name text data to update the target map.

[0006] According to another aspect of the present disclosure, an electronic device is provided, which includes: at least one processor; and a memory communicatively connected with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method provided by the present disclosure.

[0007] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, the computer instructions being used to enable a computer to perform the method provided by the present disclosure.

[0008] According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method provided by the present disclosure.

[0009] It should be understood that the contents described in this part are not intended to identify key or important features of the embodiments of the present disclosure, nor to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0010] The accompanying drawings are used to better understand the present scheme, and do not constitute a limitation on the present disclosure. Among them:

[0011] Figure 1 is an exemplary system architecture schematic diagram of a system to which the map update method and device according to one embodiment of the present disclosure can be applied;

[0012] Figure 2 is a flowchart of a map update method according to one embodiment of the present disclosure;

[0013] Figure 3 is a flowchart of acquiring road name text data from text data corresponding to point of interest data according to one embodiment of the present disclosure;

[0014] Figure 4 is a principle diagram of a map update method according to one embodiment of the present disclosure;

[0015] Figure 5 is a block diagram of a map update device according to one embodiment of the present disclosure; and

[0016] Figure 6 is a block diagram of an electronic device to which the map update method according to one embodiment of the present disclosure can be applied. DETAILED DESCRIPTION

[0017] Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, which include various details of the embodiments of the present disclosure to assist in understanding, and should be considered as merely exemplary. Thus, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of known functions and constructions are omitted in the following description for clarity and conciseness.

[0018] Road test data can be collected by a vehicle in which a collection device is deployed. Based on image recognition technology, an image of a road name sign in the road test data can be processed to obtain a road identification of a road in an electronic map. However, the collection interval of the road test data is long, which causes the road identification in the map to be unable to be updated in time after the road name changes or a new road is added. In addition, for an image with low clarity or being blocked by an obstacle, the image recognition technology cannot accurately recognize the road name in the image, which further causes the road identification to be unable to be updated in time.

[0019] Figure 1 is an exemplary system architecture schematic diagram according to an embodiment of the present disclosure to which a map updating method and device can be applied. It should be noted that, Figure 1 The system architecture shown is only an example of a system architecture to which an embodiment of the present disclosure can be applied, to help those skilled in the art understand the technical content of the present disclosure, but does not mean that the embodiment of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0020] As Figure 1 shown, the system architecture 100 according to the embodiment can include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is a medium for providing a communication link between the terminal devices 101, 102, 103 and the server 105. The network 104 can include various connection types, such as wired and / or wireless communication links, etc.

[0021] A user can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. The terminal devices 101, 102, 103 can be various electronic devices with a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers and desktop computers, etc.

[0022] The server 105 can be a server providing various services, such as a background management server supporting a website browsed by a user using the terminal devices 101, 102, 103 (only as an example). The background management server can analyze and process received user requests and other data, and feed back the processing results (such as a web page, information or data obtained or generated according to a user request, etc.) to the terminal device.

[0023] It should be noted that the map updating method provided by the embodiments of the present disclosure can be generally executed by the server 105. Accordingly, the map updating apparatus provided by the embodiments of the present disclosure can be generally arranged in the server 105. The map updating method provided by the embodiments of the present disclosure can also be executed by a server or a server cluster different from the server 105 and capable of communicating with the terminal device 101, 102, 103 and / or the server 105. Accordingly, the map updating apparatus provided by the embodiments of the present disclosure can also be arranged in a server or a server cluster different from the server 105 and capable of communicating with the terminal device 101, 102, 103 and / or the server 105.

[0024] Figure 2 is a flowchart of a map updating method according to an embodiment of the present disclosure.

[0025] As shown in Figure 2 , the method 200 can include operation S210 to operation S240.

[0026] In operation S210, road name text data is acquired from text data corresponding to point of interest data.

[0027] In the embodiments of the present disclosure, the text data corresponding to the point of interest data can correspond to the address of the point of interest. For example, the point of interest (POI) data can indicate the name of the point of interest, the city where the point of interest is located, the coordinates of the point of interest, the status of the point of interest, the address of the point of interest, and the like. The text data corresponding to the point of interest data can be from the address of the point of interest. In one example, the text data can be "A City B District Xiwang East Road 10th Court (C Street Xiwang Community Northeast Direction)". The road name text data that can be acquired is "Xiwang East Road".

[0028] In operation S220, at least one road identifier is determined according to local map data corresponding to the point of interest data.

[0029] In the embodiments of the present disclosure, the map data can include at least one road data. For example, the road data can include the road identifier.

[0030] In the embodiments of the present disclosure, the local map data corresponds to a target area, and the target area is in a target map. For example, a circular target area can be determined with the coordinates of the point of interest as the center according to a preset radius. For another example, the local map data can include at least one road data. In this embodiment, at least one road identifier is "Southeast Wa Road" and "Northeast Wa Road" as an example.

[0031] In operation S230, in response to determining that the at least one road identifier and the road name text do not match, target road data is determined from the local map data.

[0032] In this embodiment of the disclosure, road name text can be fuzzily matched with at least one road sign. For example, the similarity between the road name text and at least one road sign can be calculated for fuzzy matching. If a similarity score is greater than or equal to a preset fuzzy similarity threshold, it can be determined that there is a road sign that matches the road name text. If any similarity score is less than the preset fuzzy similarity threshold, it can be determined that at least one road sign does not match the road name text. In one example, the road name text data "Northwest Wangdong Road" may not match either the road sign "Southeast Wadi Road" or the road sign "Northeast Wadi Road".

[0033] For example, road data without road markings in local map data can be used as target road data.

[0034] In operation S240, based on the road name text data, updated road labels for the target road data are generated to update the target map.

[0035] For example, based on the road name text data "Northwest Wangdong Road", the updated road sign "Northwest Wangdong Road" can be generated and added to the target road data to update the target map.

[0036] By utilizing point-of-interest (POI) data to update road signs in a map through the embodiments of this disclosure, road sign updates can be achieved through multi-source updates, improving map update timeliness and user experience. Furthermore, it reduces reliance on road test data, saving hardware resources consumed in image recognition from road test data and lowering map update costs.

[0037] The following will combine Figure 3 Some implementation methods for extracting road name text data from text data corresponding to point of interest data are described in detail.

[0038] Figure 3 This is a flowchart illustrating the process of obtaining road name text data from text data corresponding to point-of-interest data, according to an embodiment of this disclosure.

[0039] like Figure 3 As shown, method 310 can obtain road name text data from text data corresponding to point-of-interest data. The following will provide a detailed explanation in conjunction with operations S311 to S314.

[0040] In operation S311, the text data is segmented to obtain the segmentation result.

[0041] In the embodiments of the present disclosure, the text data can be processed by using a natural language processing model to obtain a plurality of sub-text data. For example, the natural language processing model can be a trained deep learning model, which can be used to segment the text data. For another example, a classification model can also be used to classify the sub-text data to obtain the type of the sub-text data.

[0042] In the embodiments of the present disclosure, the segmentation result includes a plurality of sub-text data, and the segmentation result further includes the type of the sub-text data. For example, the type of the sub-text data can include at least one of the following: a first-level district name, a road name, a second-level district name, a landmark name, a house number, and a building name. In one example, the segmentation result of the text data “A City B District Northwest Wanda East Road No. 10, C Street Northwest Wanda Community Northeast” can include the sub-text data “A City B District”, the sub-text data “Northwest Wanda East Road”, the sub-text data “No. 10”, and the sub-text data “C Street Northwest Wanda Community”. The type of the sub-text data “A City B District” is a first-level district name, the type of the sub-text data “Northwest Wanda East Road” is a road name, the type of the sub-text data “No. 10” is a house number, and the type of the sub-text data “C Street Northwest Wanda Community” is a landmark name. In one example, the segmentation result of the text data “A City B District Building Materials City No. 22” can include the sub-text data “A City B District”, the sub-text data “Building Materials City”, and the sub-text data “No. 22”. The type of the sub-text data “A City B District” is a first-level district name, the type of the sub-text data “Building Materials City” is a second-level district name, and the type of the sub-text data “No. 22” is a house number.

[0043] In operation S312, it is determined whether there is target sub-text data of a preset type in the plurality of sub-text data.

[0044] In the embodiments of the present disclosure, the preset type can be one of a plurality of sub-text types. For example, the preset type can be a road name.

[0045] In the embodiments of the present disclosure, in response to determining that there is target sub-text data of a preset type in the plurality of sub-text data, operation S313 is performed. For example, for the text data “A City B District Northwest Wanda East Road No. 10, C Street Northwest Wanda Community Northeast”, there is the sub-text data “Northwest Wanda East Road” of the road name type, and the sub-text data “Northwest Wanda East Road” can be taken as a target sub-text data to perform operation S313.

[0046] In the embodiments of the present disclosure, in response to determining that there is no target sub-text data of a preset type in the plurality of sub-text data, operation S314 is performed. For example, for the text data “A City B District Building Materials City No. 22”, there is no sub-text data of the road name type. Operation S314 can be performed to end the flow.

[0047] In operation S313, road name text data is acquired according to the target subtext data.

[0048] For example, the subtext data "Xinbeiwang East Road" can be taken as the road name text data.

[0049] According to the embodiments of the present disclosure, the road name text data can be effectively acquired from the text data, so as to accurately update the name of the road in the map.

[0050] It can be understood that some embodiments of acquiring the road name text data are described in detail above, and the method of the present disclosure will be further described in detail in combination with relevant embodiments.

[0051] Figure 4 is a schematic diagram of a map updating method according to an embodiment of the present disclosure.

[0052] As shown in Figure 4 , the target map includes a point of interest P401 and a point of interest P402. The point of interest data of the point of interest P401 corresponds to the text data "D Middle School, No. 18, Fumin Road, C City". The point of interest data of the point of interest P402 corresponds to the text data "H Park, bottom of Fumin Road, C City". The target map further includes a road R401, a road R402, a road R403 and a road R404. In the map data of the target map, the road data of the road R401 does not have a road identifier, the road identifier of the road R402 is "Xindu Road", the road identifier of the road R403 is "Yuying Road", and the road identifier of the road R404 is "Huayuan Road".

[0053] The road name text data "Fumin Road" can be acquired from the text data corresponding to the point of interest P401. The road name text data "Fumin Road" can also be acquired from the text data corresponding to the point of interest P402.

[0054] In the embodiments of the present disclosure, local map data corresponding to the point of interest data can be determined. For example, the local map data corresponds to a target area. The target area includes a plurality of target points, and the distance between the target point and the point of interest corresponding to the point of interest data is less than or equal to a preset distance value. For example, as Figure 4As shown, a target region A410 can be determined with the interest point P401 as the center and a preset distance value as the radius. Each point in the target region A410 can be a target point. The distance between a target point and the interest point P401 can be less than or equal to the preset distance value. The local map data corresponding to the interest point P401 can be from the target region A410. For another example, a target region A420 can be determined with the interest point P402 as the center and a preset distance value as the radius. Each point in the target region A420 can be a target point. The distance between a target point and the interest point P402 can be less than or equal to the preset distance value. The local map data corresponding to the interest point P402 can be from the target region A420.

[0055] In the embodiments of the present disclosure, the local map data can include first sub-local map data and second sub-local map data. The second sub-local map data is from at least one target sub-region in the target region. The category of the target sub-region is a preset category. For example, the category of a sub-region can include an external region and an internal region. The preset category can be an internal region. For example, as shown in FIG. 4, the category of the sub-region A411 is an internal region. The sub-region A411 can be a target sub-region. Figure 4 As shown, for the interest point P401, the target region A410 can include a sub-region A411. According to the map data of the target map, the sub-region A411 is inside the D school, and its category can be an internal region. The sub-region A411 can be a target sub-region. For another example, as shown in FIG. 4, for the interest point P402, the target region A420 can include a sub-region A421. According to the map data of the target map, the sub-region A421 is inside the H park, and its category can be an internal region. The sub-region A421 can be a target sub-region. Figure 4 As shown, for the interest point P401, the target region A410 can include a sub-region A411. According to the map data of the target map, the sub-region A411 is inside the D school, and its category can be an internal region. The sub-region A411 can be a target sub-region. For another example, as shown in FIG. 4, for the interest point P402, the target region A420 can include a sub-region A421. According to the map data of the target map, the sub-region A421 is inside the H park, and its category can be an internal region. The sub-region A421 can be a target sub-region.

[0056] In the embodiments of the present disclosure, the first sub-local map data is from a region in the target region except the target sub-region. For example, for the interest point P401, the first sub-local map data is from a region in the target region A401 except the sub-region A411. For another example, for the interest point P402, the first sub-local map data is from a region in the target region A402 except the sub-region A421.

[0057] In the embodiments of the present disclosure, at least one road sign can be determined according to the local map data corresponding to the interest point data. For example, at least one road sign can be determined according to the first sub-local map data. For example, as shown in FIG. 4, at least one road sign can be determined according to the first sub-local map data corresponding to the interest point P401. For another example, as shown in FIG. 4, at least one road sign can be determined according to the first sub-local map data corresponding to the interest point P402. Figure 4As shown, the local map data from the target region A410 includes road data of road R401, road data of road R402, and road data of road R403. Road R403 is in the sub-region A411. For the interest point P401, the road identification "Xindu Road" of road R402 can be determined from the first sub-local map data from the target region A410 except the sub-region A411. For another example, as shown, the local map data from the target region A420 includes road data of road R401 and road data of road R404. For the interest point P401, the road identification "Huayuan Road" of road R404 can be determined from the first sub-local map data from the target region A420 in the sub-region A421. The address data in the interest point data can correspond to an address outside a region such as a school or a park. According to the embodiments of the present disclosure, the road identification is determined according to the first sub-local map data outside the target sub-region, and thus the road identification for matching can be determined more accurately, and the road name can be updated more accurately. Figure 4 As shown, the local map data from the target region A410 includes road data of road R401, road data of road R402, and road data of road R403. Road R403 is in the sub-region A411. For the interest point P401, the road identification "Xindu Road" of road R402 can be determined from the first sub-local map data from the target region A410 except the sub-region A411. For another example, as shown, the local map data from the target region A420 includes road data of road R401 and road data of road R404. For the interest point P401, the road identification "Huayuan Road" of road R404 can be determined from the first sub-local map data from the target region A420 in the sub-region A421. The address data in the interest point data can correspond to an address outside a region such as a school or a park. According to the embodiments of the present disclosure, the road identification is determined according to the first sub-local map data outside the target sub-region, and thus the road identification for matching can be determined more accurately, and the road name can be updated more accurately.

[0058] In the embodiments of the present disclosure, it can be determined whether at least one road identification matches the road name text. For example, for the interest point P401, it can be determined whether the road identification "Xindu Road" of road R402 matches the road name text data "Fumin Road". If the two do not match, the target road data can be acquired from the local map data from the target region A410. For another example, for the interest point P402, it can be determined whether the road identification "Huayuan Road" of road R404 matches the road name text data "Fumin Road". If the two do not match, the target road data can be acquired from the local map data from the target region A420.

[0059] In the embodiments of the present disclosure, determining the target road data from the local map data can include: taking the road name text data as a difference result of the point of interest data. In response to determining that the similarity between the difference results of the plurality of point of interest data is greater than or equal to a preset similarity threshold, an association relationship between the road name text data and the plurality of point of interest data can be established. According to the association relationship, the target road data can be determined from the local map data. For example, in a case where it is determined that the road identification "Xindu Road" of the road R402 does not match the road name text data "Fumin Road", the road name text data "Fumin Road" can be taken as a difference result of the point of interest P401. In a case where it is determined that the road identification "Huayuan Road" of the road R404 does not match the road name text data "Fumin Road", the road name text data "Fumin Road" can be taken as a difference result of the point of interest P402. It can be determined that the similarity between the difference result of the point of interest P401 and the difference result of the point of interest P402 is greater than the preset similarity threshold. The difference result of the point of interest P401 and the difference result of the point of interest P402 can be merged to obtain a merged result. The merged result can be "Fumin Road". An association relationship between the merged result "Fumin Road" and the point of interest P401 and the point of interest P402 can be established. The association relationship can indicate that the point of interest P401 and the point of interest P402 correspond to the same road name. In determining the target road data, it can be determined whether the road between the point of interest P401 and the point of interest P402 has a road identification. As shown in FIG. 4, the road closest to the point of interest P401 and the point of interest P402 can be the road R401. The road R401 does not have a road identification. The road data of the road R401 can be taken as a target road data. Through the embodiments of the present disclosure, the association relationship between different points of interest and the road name text data is established. Therefore, the range of application of a road name text data in a map can be determined in relation to the points of interest, and the target road data can be accurately determined. Figure 4

[0060] In the embodiments of the present disclosure, generating the updated road identification of the target road data according to the road name text data can include: generating the updated road identification according to the merged result. For example, "Fumin Road" can be taken as the updated road identification of the road R401 to update the target map.

[0061] It can be understood that the road data without a road identification is taken as the target road data in the above. However, the present disclosure is not limited thereto. For example, a road data can be manually determined as a target road identification. For another example, a road data with a plurality of road identifications can be taken as the target road data. For another example, a road data with an error fed back by a user can be taken as the target road data.

[0062] ​It can be understood that the method of the present disclosure is described in detail above by taking the target region as a circular region as an example. However, the present disclosure is not limited thereto, and the target region can also be a region in various shapes such as a rectangular region or an elliptical region.

[0063] Figure 5 is a block diagram of a map updating apparatus according to an embodiment of the present disclosure.

[0064] As shown in Figure 5 The apparatus 500 can include an obtaining module 510, a first determining module 520, a second determining module 530, and a generating module 540.

[0065] The obtaining module 510 is configured to obtain road name text data from text data corresponding to point of interest data.

[0066] The first determining module 520 is configured to determine at least one road identifier according to local map data corresponding to the point of interest data. For example, the local map data corresponds to a target region, and the target region is in a target map.

[0067] The second determining module 530 is configured to determine target road data from the local map data in response to determining that the at least one road identifier does not match the road name text.

[0068] The generating module 540 is configured to generate an updated road identifier of the target road data according to the road name text data, so as to update the target map.

[0069] In some embodiments, the second determining module includes an obtaining submodule configured to take the road name text data as a difference result of the point of interest data, a merging submodule configured to merge a plurality of difference results to obtain a merged result in response to determining that a similarity between the plurality of difference results is greater than or equal to a preset similarity threshold, an establishing submodule configured to establish an association relationship between the merged result and the plurality of point of interest data, and a first determining submodule configured to determine the target road data from the local map data according to the association relationship.

[0070] In some embodiments, the obtaining module includes a cutting submodule configured to cut the text data to obtain a cutting result, wherein the cutting result includes a plurality of subtext data, and the cutting result further includes a type of the subtext data, and an obtaining submodule configured to obtain the road name text data according to target subtext data in the plurality of subtext data in response to determining that the target subtext data is of a preset type.

[0071] In some embodiments, the target region includes a plurality of target points, and a distance between the target point and a point of interest corresponding to the point of interest data is less than or equal to a preset distance value.

[0072] In some embodiments, the target road data does not have the road identification.

[0073] In some embodiments, the local map data includes first sub-local map data and second sub-local map data, the second sub-local map data is from at least one target sub-region in the target region, the target sub-region is of a preset category, and the first sub-local map data is from a region in the target region other than the target sub-region. The first determining module includes a second determining submodule configured to determine at least one road identification according to the first sub-local map data.

[0074] In some embodiments, the generating module includes a generating submodule configured to generate an updated road identification according to the merging result.

[0075] In the technical solutions of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in the technical solutions comply with relevant laws and regulations and do not violate public order and good customs.

[0076] According to embodiments of the present disclosure, the present disclosure further provides an electronic device, a readable storage medium and a computer program product.

[0077] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptops, desktops, tablets, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present disclosure described and / or claimed in this document.

[0078] As shown in Figure 6 The device 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the device 600 can also be stored in the RAM 603. The computing unit 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0079] A number of components in the device 600 are connected to the I / O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a magnetic disk, an optical disk, etc.; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information / data with other devices over a computer network, such as the Internet, and / or various telecommunication networks.

[0080] The computing unit 601 can be various general and / or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The computing unit 601 performs various methods and processes described above, such as the map updating method. For example, in some embodiments, the map updating method can be implemented as a computer software program, which is tangibly embodied in a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 600 via the ROM 602 and / or the communication unit 609. When the computer program is loaded onto the RAM 603 and executed by the computing unit 601, one or more steps of the map updating method described above can be performed. Alternatively, in other embodiments, the computing unit 601 can be configured to perform the map updating method by any other appropriate means, such as by means of firmware.

[0081] Various implementations of the systems and techniques described above herein can be realized in digital electronic circuitry, integrated circuitry, a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), a system on a chip (SOC), a complex programmable logic device (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0082] Program code for carrying out methods of the present disclosure can be written in any combination of one or more programming languages. The program code can be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the program code, when executed by the processor or controller, produces the functions / operations specified in the flowcharts and / or block diagrams. The program code can be executed entirely on a machine, partially on a machine, partially on a machine as a stand-alone software package, partially on a machine and partially on a remote machine or entirely on a remote machine or server.

[0083] In the context of the present disclosure, a machine-readable medium can be a tangible medium that contains or stores a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include but is not limited to an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the machine-readable storage medium will include one or more lines of electrical connections, portable computer disks, hard disk drives, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or Flash memory), optical fibers, portable compact disc read-only memories (CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0084] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) monitor or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0085] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end, middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0086] The computer system can include clients and servers. This relationship can be

[0087] It should be understood that the procedures shown above can be re-ordered, added to, or removed from, while still being within the scope of the present disclosure. For example, the steps recited in the present disclosure can be performed in parallel, in series, or in a different order, as long as the desired results of the technology disclosed in the present disclosure are achieved, and are not limited herein.

[0088] The specific embodiments described above are not intended to be limiting, and persons skilled in the art will appreciate that various modifications, combinations, sub-combinations and alternatives can be made to the specific embodiments without departing from the spirit and principles of the disclosure. Accordingly, the disclosure is not limited to the specific embodiments described above.

Claims

1. A map updating method, comprising: Extract road name text data from the text data corresponding to the point of interest data; Based on the local map data corresponding to the point of interest data, at least one road sign is determined, wherein the local map data corresponds to the target area, and the target area is located in the target map; In response to determining that the road name text does not match any of the at least one road sign, the road name text data is used as the difference result of the point of interest data; In response to determining that the similarity between the difference results of multiple interest point data is greater than or equal to a preset similarity threshold, the multiple difference results are merged to obtain a merged result; Establish the association between the merged result and the multiple points of interest data; Based on the aforementioned correlation, target road data is determined from the local map data; and Based on the road name text data, an updated road identifier is generated for the target road data to update the target map.

2. The method according to claim 1, wherein, The step of obtaining road name text data from text data corresponding to point-of-interest data includes: The text data is segmented to obtain a segmentation result, wherein the segmentation result includes multiple sub-text data, and the segmentation result also includes the type of the sub-text data; and In response to determining that there is a target sub-text data of a preset type among the multiple sub-text data, the road name text data is obtained based on the target sub-text data.

3. The method according to claim 1, wherein, The target area includes multiple target points, and the distance between the target points and the points of interest corresponding to the point of interest data is less than or equal to a preset distance value.

4. The method according to claim 1, wherein, The target road data does not have road markings.

5. The method according to claim 1, wherein, The local map data includes first sub-local map data and second sub-local map data. The second sub-local map data comes from at least one target sub-region within the target region. The target sub-region is categorized into a preset category. The first sub-local map data comes from areas within the target region other than the target sub-region. Determining at least one road sign based on local map data corresponding to the point of interest data includes: Based on the first sub-local map data, at least one of the road signs is determined.

6. The method according to claim 1, wherein, The step of generating the updated road identifier for the target road data based on the road name text data includes: Based on the merging results, the updated road signage is generated.

7. A map updating device, comprising: The acquisition module is used to extract road name text data from the text data corresponding to the point of interest data; The first determining module is used to determine at least one road sign based on local map data corresponding to the point of interest data, wherein the local map data corresponds to a target area and the target area is located in the target map; The second determining module is configured to determine target road data from the local map data in response to determining that the road name text does not match at least one of the road identifiers; and The generation module is used to generate updated road identifiers for the target road data based on the road name text data, so as to update the target map. The second determining module includes: A submodule is used to obtain the road name text data as the difference result of the point of interest data; The merging submodule is used to merge multiple difference results to obtain a merged result in response to determining that the similarity between the difference results of multiple interest point data is greater than or equal to a preset similarity threshold. A submodule is established to establish the association between the merging result and multiple points of interest data; and The first determining submodule is used to determine the target road data from the local map data based on the association relationship.

8. The apparatus according to claim 7, wherein, The acquisition module includes: A segmentation module is used to segment the text data to obtain a segmentation result, wherein the segmentation result includes multiple sub-text data, and the segmentation result also includes the type of the sub-text data; and The acquisition submodule is used to acquire the road name text data based on the target subtext data in response to determining that there is a target subtext data of a preset type among the multiple subtext data.

9. The apparatus according to claim 7, wherein, The target area includes multiple target points, and the distance between the target points and the points of interest corresponding to the point of interest data is less than or equal to a preset distance value.

10. The apparatus according to claim 7, wherein, The target road data does not have road markings.

11. The apparatus according to claim 7, wherein, The local map data includes first sub-local map data and second sub-local map data. The second sub-local map data comes from at least one target sub-region within the target region. The target sub-region is categorized into a preset category. The first sub-local map data comes from areas within the target region other than the target sub-region. The first determining module includes: The second determining submodule is used to determine at least one of the road signs based on the first sub-local map data.

12. The apparatus according to claim 7, wherein, The generation module includes: A generation submodule is used to generate the updated road sign based on the merging result.

13. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.

14. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 6.

15. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 6.

Images