Map processing method and device, equipment and storage medium

Abstract

The disclosure provides a map processing method and device, equipment and a storage medium, relates to the technical field of artificial intelligence, and in particular to the technical field of intelligent transportation, smart city, traffic simulation and traffic digital management. The specific implementation scheme is: a mapping relationship of map elements in a first map and a second map is established, wherein the accuracy of the first map is higher than that of the second map; according to a preset semantic road network protocol, map data corresponding to the map elements having the mapping relationship in the first map and the second map is integrated to obtain a target map, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers. By using the above technical scheme, a map meeting the requirements of the preset semantic road network protocol is quickly generated on the basis of taking into account the mapping cost, which is conducive to keeping the calculation results of different spatial scales consistent.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of artificial intelligence, in particular to the technical field of intelligent transportation, smart city, traffic simulation, and digital management of transportation. BACKGROUND

[0002] In the urban transportation industry, road network data is the basis for various systems such as intelligent transportation management systems and traffic simulation systems.

[0003] Currently, the road network data of the above-mentioned systems mainly comes from mature maps such as navigation maps or high-definition maps, or maps constructed by manual drawing. Using the adopted maps, related processing such as traffic perception, model calculation, and traffic deduction can be performed. SUMMARY

[0004] The present disclosure provides a map processing method, device, equipment, and storage medium.

[0005] According to an aspect of the present disclosure, a map processing method is provided, comprising:

[0006] establishing a mapping relationship of map elements in a first map and a second map, wherein the accuracy of the first map is higher than the accuracy of the second map;

[0007] integrating map data corresponding to the map elements in the first map and the second map that exist in the mapping relationship according to a preset semantic road network protocol, to obtain a target map that meets the requirements of the preset semantic road network protocol, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers.

[0008] According to another aspect of the present disclosure, a map processing device is provided, comprising:

[0009] a mapping relationship establishing module configured to establish a mapping relationship of map elements in a first map and a second map, wherein the accuracy of the first map is higher than the accuracy of the second map;

[0010] a data integration module configured to integrate map data corresponding to the map elements in the first map and the second map that exist in the mapping relationship according to a preset semantic road network protocol, to obtain a target map that meets the requirements of the preset semantic road network protocol, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers.

[0011] According to another aspect of the present disclosure, an electronic device is provided, comprising:

[0012] at least one processor; and

[0013] a memory in communication with the at least one processor; wherein

[0014] 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 according to the embodiments of the present disclosure.

[0015] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to perform the method according to the embodiments of the present disclosure.

[0016] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method according to any of the embodiments of the present disclosure.

[0017] It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of the present disclosure, nor is it used 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

[0018] The accompanying drawings are used to better understand the present scheme, and do not limit the present disclosure. Among them:

[0019] Figure 1 is a flowchart of a map processing method according to an embodiment of the present disclosure;

[0020] Figure 2 is a schematic diagram of a visual display interface according to an embodiment of the present disclosure;

[0021] Figure 3 is a macro-scale schematic diagram according to an embodiment of the present disclosure;

[0022] Figure 4 is a meso-scale schematic diagram according to an embodiment of the present disclosure;

[0023] Figure 5 is a micro-scale schematic diagram according to an embodiment of the present disclosure;

[0024] Figure 6 is a flowchart of another map processing method according to an embodiment of the present disclosure;

[0025] Figure 7 is a flowchart of a line element matching process according to an embodiment of the present disclosure;

[0026] Figure 8is a flowchart of another map processing method according to an embodiment of the present disclosure;

[0027] Figure 9 is a structural schematic diagram of a map processing apparatus according to an embodiment of the present disclosure;

[0028] Figure 10 is a block diagram of an electronic device for implementing the map processing method according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0029] Exemplary embodiments of the present disclosure are described herein with reference to the accompanying drawings, which are provided to assist in a comprehensive understanding of the present disclosure, and should be considered as merely exemplary. Accordingly, those skilled 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, in the following description, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

[0030] Figure 1 is a flowchart of a map processing method according to an embodiment of the present disclosure, which can be applied to the case of constructing a map across spatial scales. The constructed map can be applied to various systems in the urban traffic industry, such as intelligent traffic management systems, traffic simulation systems of various spatial scales, urban signal control systems, urban traffic brains, urban twin traffic systems, and transportation operations coordination centers (TOCCs). The method can be executed by a map processing apparatus, which can be implemented in hardware and / or software, and can be configured in an electronic device. Referring to Figure 1 , the method specifically includes the following:

[0031] S101, establishing a mapping relationship of map elements in a first map and a second map, wherein the accuracy of the first map is higher than that of the second map;

[0032]

[0032] S102, according to a preset semantic road network protocol, integrating map data corresponding to map elements having the mapping relationship in the first map and the second map, to obtain a target map meeting requirements of the preset semantic road network protocol, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers.

[0033] The first map and the second map can be existing maps of different precisions, for example, the first map can be a high-precision map, and the second map can be a navigation map. The high-precision map, also known as a high-definition map, can be understood as a map defined with high precision and refinement. The precision thereof can generally reach a level capable of distinguishing individual lanes, and the map can be stored in a standardized protocol according to various traffic elements in a traffic scene, can be applied to autonomous driving, and contains geometric linear aspects such as the longitudinal slope, transverse slope and curvature of a road and a refined traffic semantic level, but lacks information related to large-scale road levels. The navigation map, also known as a traditional map, generally reflects elements such as important intersections and arterial roads in terms of precision, focuses on the connectivity of a road, and lacks geometric linear aspects such as the longitudinal slope, transverse slope and curvature of a road and a refined traffic semantic level, and the traffic semantics are few, that is, lacks more detailed road information and other related traffic elements.

[0034] For various systems in the urban traffic industry, different levels of precision of maps are often required according to different application scenarios. For example, an application scenario focusing on the operation situation of urban roads requires a map similar to a navigation map reflecting the road space scale of elements such as important intersections and arterial roads; for example, for application scenarios such as urban traffic light management, lane construction, road equipment and facility management and maintenance, and road restriction, a lane-level spatial scale high-precision map is required; for example, for an application scenario of deducing traffic congestion states, a map is required that can perceive and predict the traffic congestion state of a city road network from a macro perspective and deduce the traffic state of a perceived key road and intersection from a micro perspective, thereby providing all-round data support for traffic control and decision-making. At present, each system adopts a navigation map for corresponding calculation at a macro scale and a high-precision map for corresponding calculation at a micro scale, and each system is independent from macro to micro, and cannot form an effective linkage, so that the deduced conclusions of different scales often contradict each other, making it difficult to reasonably use the deduced conclusions, and further affecting the application of the corresponding system.

[0035] In the embodiments of the present disclosure, in order to support different application scenarios of various systems in the city traffic industry, a road network protocol for traffic management, i.e., the preset semantic road network protocol in the embodiments of the present disclosure, is constructed. The preset semantic road network protocol can be understood as a preset description protocol for describing traffic information of different spatial scales. The preset semantic road network protocol corresponds to at least two spatial scales (which can also be understood as spatial resolutions). Each spatial scale corresponds to at least one preset layer. The preset layer can be understood as a preset map layer. The preset layer can store spatial geometric information, road topological information, traffic semantic information and the like. There is an association relationship between different preset layers. In the process of performing related calculations based on a map that meets the preset semantic road network protocol, the data content in the corresponding preset layer can be obtained according to the required spatial scale to participate in the calculation, and the data content in the related preset layer can be obtained according to the association relationship between the preset layers to participate in the auxiliary calculation. That is, the data content in different preset layers can be shared and converted, rather than being calculated separately as in the related art, such as using two independent maps of a traditional map and a high-precision map. The embodiments of the present disclosure use the data layering idea to describe traffic objects of different spatial scales, and associate traffic objects of different spatial scales in the same set of maps, which is beneficial to lossless data conversion and state smooth transition in the calculation process for different spatial scales.

[0036] For example, in the process of constructing a target map that meets the requirements of the preset semantic road network protocol, data in existing maps of different precisions can be used to quickly generate a unified traffic semantic map that meets the requirements of the preset semantic road network protocol, so as to obtain a target map for application of various systems in the traffic management industry, thereby effectively saving mapping costs. Specifically, a mapping relationship between map elements in the first map and the second map can be established. The map elements can include geometric elements such as point elements and line elements, and are used to describe different types of road information, such as road intersections and roads. The mapping relationship can include a mapping relationship between point elements in the first map and point elements in the second map, and can also include a mapping relationship between line elements in the first map and line elements in the second map. The establishment manner of the mapping relationship is not limited, for example, the mapping relationship can be established by matching based on geometric relationships and / or name similarities between map elements, and then the matched map elements are paired to establish the mapping relationship.

[0037] In the embodiments of the present disclosure, after the mapping relationship of the map elements is established, the map data corresponding to the map elements having the mapping relationship in the first map and the second map is integrated according to the preset semantic road network protocol, and a target map satisfying the requirement of the preset semantic road network protocol is obtained. The specific format of the target map is not limited, for example, it can be in json format. For example, each preset layer in the preset semantic road network protocol can include multiple fields, different fields are used to describe different traffic information, the description of the traffic information can be understood as traffic semantics, the corresponding map data can be obtained from the first map and the second map according to the meaning of the field, and then filled into the corresponding field, and the target map is obtained.

[0038] The technical scheme provided by the embodiments of the present disclosure establishes the mapping relationship of the map elements in the first map and the second map, wherein the accuracy of the first map is higher than that of the second map, and the map data corresponding to the map elements having the mapping relationship in the first map and the second map is integrated according to the preset semantic road network protocol, and a target map satisfying the requirement of the preset semantic road network protocol is obtained, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers. By using the above technical scheme, the data in the existing maps with different accuracies is used to quickly generate a unified target map that satisfies the requirement of the preset semantic road network protocol and can be applied to various systems of the traffic management industry, thereby effectively saving the mapping cost. Moreover, since the preset semantic road network protocol adopts the data layered map description idea, the calculation ability of different spatial scales is possessed in the process of related calculation based on the obtained target map, and since the calculation is dependent on the same set of maps, the information in different layers can be shared and transformed, so that the calculation results of different spatial scales can be consistent.

[0039] In an optional implementation, the preset semantic road network protocol corresponds to at least three spatial scales, and the at least three spatial scales include a macro scale, at least one meso scale and a micro scale. The advantage of such setting is that more spatial scales are set, which satisfies more rich application scenarios and is more conducive to smooth conversion between data of different spatial scales.

[0040] In an optional implementation, the macro scale includes road intersections and roads; the meso scale includes road breaking points and road segments, the road breaking points are used to represent positions where the number of lanes and / or lane lines in the same road changes, and the road segments have the road intersections and / or the road breaking points as endpoints; and the micro scale includes lanes. The advantage of such setting is that the traffic objects contained in different spatial scales are reasonably divided, and the existing navigation map data and high-precision map data can also be better compatible.

[0041] Exemplarily, the point elements in the map elements can be regarded as nodes, and the nodes can be divided into two categories, one of which is a road intersection, and the other is a road breaking point, which belong to different preset layers. The road intersection can be understood as a physical junction, which is a road branching point and an area where traffic flow exchanges exist. The road breaking point (zipper) can be understood as a non-physical junction, where the number of lanes and / or lane lines change, and there is no exchange of traffic flow in the conflicting direction. Optionally, in order to reflect more detailed traffic information, the road breaking point can be determined according to a preset road breaking rule. The preset road breaking rule may, for example, include: breaking at a place where the number of lanes changes; breaking at a place where there is an early right turn; breaking at a place where there is a pedestrian zebra crossing in the middle of the road; breaking at a place where the main and auxiliary roads and ramps converge and diverge; breaking at a place where there is a U-turn in the middle of the road; breaking at a place where the dashed line becomes a solid line in the preset range of the road intersection, and the like.

[0042] Exemplarily, the road in the macro scale is between road intersections, that is, the two endpoints as the starting point and the ending point are road intersections, and the road generally does not contain road details. The road is broken into several segments according to the preset road breaking rule, and each segment can be referred to as a road segment (roadseg) and belongs to the meso scale. The endpoints of the road segment can be a road intersection and a road breaking point, or both can be road breaking points. There can be several lanes in the road and the road segment, which can reflect the road details and belong to the micro scale. In addition, the lane lines in the road intersection and the road breaking point also belong to the micro scale.

[0043] Exemplarily, the related information of each object contained in each spatial scale is stored in different preset layers, for example, which can include: a road intersection layer, a road breaking point layer, a macro road layer, a road segment line layer, and a lane line layer.

[0044] Optionally, on the basis of the above objects, more objects can be set to more comprehensively describe the traffic information. For example, the part of the road inside the road intersection and the road link can be referred to as a road connector (roadConnector), corresponding to a road connector layer; the part of the road segment inside the road breaking point and the road segment link can be referred to as a road segment connector (roadsegConnector), corresponding to a road segment connector layer; the part of the lane inside the road intersection and the road breaking point and the lane link can be referred to as a lane connector (laneConnector), corresponding to a lane connector layer.

[0045] Optionally, the preset semantic road network protocol can also support visual display, which can include point objects on the road surface, such as street lamps and signs, and the corresponding three-dimensional model data can be stored in the corresponding preset layer (such as a road surface point object layer) and loaded when visualized. For each of the above preset layers containing point objects and line objects, a corresponding preset layer containing face objects can be set, and the relevant data required for visual rendering can be stored in the preset layer, for example, the road intersection face layer, the road breaking point face layer, the macro road face layer, the road segment face layer, the lane face layer, the road connector face layer, the road segment connector face layer, the lane connector face layer, and the road surface face object (such as objects that need to add textures) layer.

[0046] For example, a road intersection can be taken as an example, and the following can be understood with reference to Figures 2 to 5 For example, a road intersection can be taken as an example, and the following can be understood with reference to Figure 2 is a schematic diagram of a visual display interface provided according to an embodiment of the present disclosure, which can display detailed information of the road intersection in the page, and specifically can be a visual display of a high-precision map; Figure 3 is a macro-scale schematic diagram provided according to an embodiment of the present disclosure, Figure 3 which shows the expression form of the road intersection at the road level spatial scale, including the road intersection in the form of a point and the road in the form of a line; Figure 4 is a meso-scale schematic diagram provided according to an embodiment of the present disclosure, Figure 4 which shows the expression form of the road intersection at the road segment scale, including the road intersection in the form of a point and the road breaking point, and the road segment in the form of a line; Figure 5 is a micro-scale schematic diagram provided according to an embodiment of the present disclosure, Figure 5 which shows the expression form of the road intersection at the lane level spatial scale, including the road intersection in the form of a point and the road breaking point, and the lane in the form of a line.

[0047] In an optional embodiment, the data structure corresponding to the preset layer includes a field for representing static traffic semantics and / or dynamic traffic semantics. The advantage of such a setting is that the target map can contain more rich traffic semantic information, supporting different application requirements in the system.

[0048] For example, the static traffic semantics can be understood as semantic information of a traffic object with a change frequency lower than a first preset frequency, for example, once a year, that is, a traffic object that is not easily changed, such as a road, a road section, a center point of a road intersection, and the like; and the dynamic traffic semantics can be understood as semantic information of a traffic object with a change frequency higher than a second preset frequency, which is generally less than the first preset frequency, for example, once a day or once a month, that is, a traffic object that is easily changed, such as a change of a left arrow of a road, a speed limit, a road sign for publishing information, a traffic direction of a lane in different time periods, and the like.

[0049] For example, the preset semantic road network protocol can include 18 preset layers, and one optional implementation of a layer name, a meaning, and a field included can be referred to Table 1 as follows.

[0050] Table 1: Preset layers in a preset semantic network protocol

[0051]

[0052]

[0053]

[0054] For example, the preset semantic network protocol can support city-level road network traffic model related calculations and front-end web visualization, and can also support road visualization and editing requirements. For example, a user receives a modification operation based on a face layer in a visualization page, and then modifies data in a corresponding layer according to an association relationship between the face layer and a line layer and a point layer.

[0055] Figure 6 is a flowchart of another map processing method according to an embodiment of the disclosure. The embodiment is based on the above-mentioned optional embodiments, and proposes an optional solution for further description of the establishment of a mapping relationship. Referring to Figure 6 The method comprises the following steps.

[0056] S601, converting the first map and the second map to the same preset coordinate system.

[0057] For example, the first map and the second map can be uniformly converted to a GWS84 coordinate system or a WGS coordinate system, specifically a geocentric coordinate system, a spatial rectangular coordinate system, and an origin coinciding with the earth's center of mass, which is a coordinate system adopted by a global positioning system (GPS).

[0058] S602, establishing a first mapping relationship of point elements based on a distance relationship of the point elements in the first map and the second map in the preset coordinate system.

[0059] wherein the map elements include point elements and line elements, the point elements include road junctions, and the line elements include roads and road segments.

[0060] Exemplarily, the meaning of the point elements in the two kinds of map elements is relatively clear, and the point elements can be matched first to establish the mapping relationship of the point elements. Taking the road junction center point coordinates in the first map as the center and a preset length (the specific value is not limited, such as 10 to 20 meters) as the radius, it is determined whether each road junction center point coordinate in the second map falls within the circle, and if so, the mapping relationship between the road junction in the first map and the road junction to which the center point coordinate falls is established.

[0061] Specifically, the road junction h in the high-precision map is traversed, a circle is generated with the center point of the road junction h as the center and a radius R, and the road junction l in the traditional map is traversed. If l is within the circle, the road junction h and the road junction l are paired to form the first mapping relationship.

[0062] S603, for the line elements in the first map and the second map, it is determined whether the end points of the line elements match based on the first mapping relationship, and a second mapping relationship of the line elements is established according to the determination result.

[0063] Exemplarily, the basic structure of the urban road network is point and line, and the starting point and the ending point of each road line is an explicit road junction, so the mapping relationship of the line elements can be constructed by comparing whether the starting and ending points of two roads are the same.

[0064] In an optional implementation, S603 can specifically include: for the first line element in the second map, searching for a target line element in the first map whose starting point and / or ending point exists the first mapping relationship; determining the target line element and the line element in the second map which has an overlay relationship and / or a connectivity relationship with the target line element as a second line element; establishing the second mapping relationship of the first line element and the second line element. The advantage of such setting is that the line elements with corresponding relationship can be found comprehensively.

[0065] For example, the starting point and the ending point corresponding to the first line element in the second map can be determined according to the overlay relationship and / or attribute information in the second map, and then each to-be-matched line element in the first map is traversed, the starting point and the ending point corresponding to the to-be-matched line element are determined according to the overlay relationship and / or attribute information in the second map, it is judged whether the starting point corresponding to the first line element and the starting point corresponding to the to-be-matched line element exist the first mapping relationship, and whether the ending point corresponding to the first line element and the ending point corresponding to the to-be-matched line element exist the first mapping relationship, if the first mapping relationship exists, it is considered that the starting points are the same or the ending points are the same, because the definition of the road in the first map and the second map can be different, for example, there is XX road in the traditional map, and the starting point and the ending point are intersection A and B respectively, and there are XX north road and XX south road in the high-precision map, the starting point of XX north road is intersection 1, and the ending point of XX south road is intersection 2, XX north road and XX south road are connected with the same intersection, intersection A and intersection 1 exist the first mapping relationship, and intersection B and intersection 2 exist the first mapping relationship, and the second mapping relationship between the line element corresponding to XX road and the line elements corresponding to XX north road and XX south road needs to be established, therefore, if at least one of the starting point and the ending point exists the first mapping relationship, it is considered that the corresponding line elements are matched, and then the second mapping relationship can be established. In addition, if there is XX middle road between XX north road and XX south road in the high-precision map, the second mapping relationship between XX road and XX middle road can also be established, therefore, the to-be-matched line element in which the point and / or the ending point exist the first mapping relationship is recorded as a target line element, and the target line element and the line element in the second map which exists the overlay relationship and the connection relationship with the target line element are determined as a second line element, and are used to establish the second mapping relationship with the first line element.

[0066] In the electronic map, the overlay relationship between the roads can be a flat intersection road (referred to as a flat road), wherein the flat road refers to two roads that actually intersect, and the intersection position is the starting point or the ending point, therefore, the starting point and the ending point of the road can be determined through the overlay relationship, and whether the roads are connected can also be determined. In addition, in the electronic map, attribute information of the map element can also be recorded, such as the connection attribute of the point element and the line element, and the connection attribute between the line elements, the starting point and the ending point of the line element, and whether the line elements are connected can be determined according to the attribute information.

[0067] Specifically, S603 can include: determining, for a first line element in the second map, whether a start point and an end point of a first to-be-judged line element in the first map have the first mapping relationship with the first line element; if the start point of the first to-be-judged line element has the first mapping relationship with the first line element, and the end point of the first to-be-judged line element has the first mapping relationship with the end point of the first line element, determining the first to-be-judged line element as a second line element; if the start point of the first to-be-judged line element has the first mapping relationship with the first line element, but the end point of the first to-be-judged line element does not have the first mapping relationship with the end point of the first line element, searching for a second to-be-judged line element having a cover relationship and / or a connectivity relationship with the first to-be-judged line element, if the end point of the second to-be-judged line element has the first mapping relationship with the end point of the first line element, determining the first to-be-judged line element and the second to-be-judged line element as target line elements, and determining the target line elements and line elements in the second map having a cover relationship and / or a connectivity relationship with the target line elements as second line elements; if the start point of the first to-be-judged line element does not have the first mapping relationship with the first line element, but the end point of the first to-be-judged line element has the first mapping relationship with the end point of the first line element, searching for a third to-be-judged line element having a cover relationship and / or a connectivity relationship with the first to-be-judged line element, if the start point of the third to-be-judged line element has the first mapping relationship with the first line element, determining the first to-be-judged line element and the third to-be-judged line element as target line elements, and determining the target line elements and line elements in the second map having a cover relationship and / or a connectivity relationship with the target line elements as second line elements; and establishing a second mapping relationship between the first line element and the second line elements. In this way, the next to-be-judged line element can be quickly found according to the connectivity attribute of the line element in the first map, and then the mapping relationship between a line element in the second map and multiple line elements in the first map is established.

[0068] Figure 7 is a flowchart of a line element matching process according to an embodiment of the present disclosure, as shown in Figure 7As shown, the line element j of the traditional map is traversed, the start and end intersections of the line element j are determined according to the overhang relationship and / or attribute information, and are denoted as t s and t e respectively. Then the line element i in the high-precision map is traversed, the start and end intersections of the line element i are determined according to the overhang relationship and / or attribute information, and are denoted as h s and h e respectively. If the first mapping relationship exists between t s and h s and the first mapping relationship exists between t e and h e, that is, t s = h s and t e = h e, then the line j and the line i are paired, that is, the second mapping relationship is established. If t s = h s and t e ≠ h e (the first mapping relationship does not exist between t e and h e), then the successor line object i+n (n is a positive integer greater than or equal to 1, and n is 1 in the first determination) is found according to the overhang relationship and / or attribute information (specifically, the connectivity attribute of the line element) of the line i, and the end intersection of i+n is determined and denoted as h e i+n. If t e = h e i+n, then the second mapping relationship of the line j and the line object set composed of the line i to the line i+n is established. If t e ≠ h e i+n, then the current line i+n is added to the intermediate line set hn, and n is incremented, that is, the next successor line element is found based on the current line i+n according to the overhang relationship and / or attribute information, that is, the line i+n is re-determined, until the line i+n whose end intersection exists the first mapping relationship is found, and the line j is paired with the line i, the line element in the intermediate line set hn and the last line i+n. If t s ≠ h s and t e = h e, then the predecessor line object i-m (m is a positive integer greater than or equal to 1, and m is 1 in the first determination) is found according to the overhang relationship and / or attribute information (specifically, the connectivity attribute of the line element) of the line i, and the start intersection of i-m is determined and denoted as h s i-m. If t s = h s i-m, then the second mapping relationship of the line j and the line object set composed of the line i to the line i-m is established. If t s ≠ h s i-m, then the current line i-m is added to the intermediate line set hm, and m is incremented, and the process is repeated. If t s ≠ h s and t e ≠ h e, then a new line object i is found in the high-precision map until the traversal ends.

[0069] In an optional implementation, the establishing the second mapping relationship of the first line element and the second line element can specifically include: establishing an initial mapping relationship of the first line element and the second line element; verifying the initial mapping relationship based on a preset verification strategy, and determining the initial mapping relationship that passes the verification as the second mapping relationship of the line element. In this way, the benefits of this setting are that some line element pairs with mis-matching conditions can be filtered out by verifying the initial mapping relationship, thereby ensuring the accuracy of the data in the target map.

[0070] In an optional implementation, the initial mapping relationship is verified based on the preset verification strategy, and the initial mapping relationship that passes the verification is determined as the second mapping relationship of the line element, including: for the line element pair that has the initial mapping relationship, it is determined whether a preset verification index matches successfully, if the preset verification index matches successfully, it is determined that the initial mapping relationship passes the verification, and the initial mapping relationship that passes the verification is determined as the second mapping relationship of the line element, wherein the preset verification index includes at least one of a length of a line element, a distance of a line element, an azimuth angle of a line element, and a name of a line element. In this way, the line element pair that has the mis-matching condition can be accurately filtered out, and the accuracy of the data in the target map is further ensured.

[0071] For example, if the matching is not successful, it is determined that the initial mapping relationship does not pass the verification, and the initial mapping relationship that does not pass the verification is not determined as the second mapping relationship of the line element.

[0072] For example, for the length of the line element, it can be determined whether the length difference and / or the length difference ratio of the line element pair that has the second mapping relationship is less than a preset threshold, if yes, it is considered that the verification is passed.

[0073] For example, for the distance of the line element, it can be determined whether the distance value of the line element pair that has the second mapping relationship is less than a preset distance threshold, if yes, it is considered that the verification is passed, wherein the calculation method of the distance value is not limited, for example, it can be a bidirectional Hausdorff distance H(A, B).

[0074] For example, for the azimuth angle of the line element, it can be determined whether the difference of the azimuth angle of the line element pair that has the second mapping relationship is less than a preset angle threshold, if yes, it is considered that the verification is passed. The azimuth angle can be a heading angle or a road direction, and the road direction includes eight directions: east, south, west, north, southeast, southwest, northeast, and northwest. The heading angle is the included angle between the road line and the north direction. If the angle error range of the two lines is within ±5 degrees, it is considered that the heading angles are the same, and the verification is passed.

[0075] For example, for the name of the line element, a fuzzy matching can be performed on the name of the line element pair that has the second mapping relationship in a text analysis manner, if the matching is successful, it is considered that the verification is passed.

[0076] S604, according to the preset semantic road network protocol, the map data corresponding to the map element pair that has the first mapping relationship and the second mapping relationship in the first map and the second map is integrated, and a target map that meets the requirement of the preset semantic road network protocol is obtained.

[0077] The preset semantic road network protocol corresponds to at least three spatial scales, including a macro scale, at least one meso scale, and a micro scale, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers.

[0078] The map processing method provided by the embodiments of the present disclosure converts existing maps of different precisions into the same coordinate system, first establishes a first mapping relationship of a road intersection of a point element, and then further establishes a second mapping relationship of a road in a line element based on the first mapping relationship, so as to accurately associate map elements in the first map and the second map, and further accurately fill map data with a mapping relationship into a preset semantic road network protocol to quickly and accurately generate a target map meeting the requirements of the preset semantic road network protocol, and further improve the accuracy of the target map, thereby better supporting the application of each system in the urban transportation industry.

[0079] Figure 8 The flowchart of another map processing method provided according to the embodiments of the present disclosure, the embodiments are based on the above-mentioned optional embodiments, and an optional scheme is proposed, and the integration process of the map data is further described.

[0080] Referring to Figure 8 The method comprises the following steps.

[0081] S801, converting a first map and a second map into the same preset coordinate system.

[0082] S802, establishing a first mapping relationship of a point element based on the distance relationship of the point element in the first map and the second map in the preset coordinate system.

[0083] S803, for a first line element in the second map, finding a target line element with a first mapping relationship of a starting point and / or an ending point from the first map.

[0084] S804, determining the target line element and a line element with an overlying relationship and / or a connected relationship with the target line element in the second map as a second line element.

[0085] S805, establishing an initial mapping relationship of the first line element and the second line element.

[0086] S806, for a line element pair with an initial mapping relationship, determining whether a preset verification index matches successfully, if the matching is successful, determining that the verification is passed, and determining the initial mapping relationship that passes the verification as a second mapping relationship of the line element.

[0087] S807: Determine a to-be-filled field in the preset semantic network protocol, and obtain, from the first map and the second map, map data corresponding to the to-be-filled field of the map elements having a mapping relationship.

[0088] For example, the to-be-filled field in the preset semantic network protocol can refer to the related content in Table 1. Specifically, a correspondence between each to-be-filled field and a first field in a first map protocol corresponding to the first map, and a correspondence between each to-be-filled field and a first field in a first map protocol corresponding to the second map can be established in advance. For a current to-be-filled field, the corresponding map data is searched and obtained from the first map and / or the second map according to the above correspondence.

[0089] S808: Fill the obtained map data into the to-be-filled field, and / or calculate the obtained map data according to a preset calculation manner, and fill the calculation result into the to-be-filled field.

[0090] For example, for the current to-be-filled field, if the obtained map data matches the data content to be filled, the map data can be directly filled into the current to-be-filled field. If the obtained map data does not match the data content to be filled, the map data can be calculated by a preset calculation manner. For example, for some mesoscale to-be-filled field, the map data obtained from the high-precision map can be aggregated and calculated, and then the data to be filled is obtained.

[0091] S809: Generate a target map meeting the requirement of the preset semantic network protocol according to the filling result.

[0092] The map processing method provided by the embodiments of the present disclosure can quickly and accurately generate a target map by establishing a mapping relationship between map elements of a first map and a second map, and then obtaining corresponding data from the first map and the second map for each to-be-filled field in a preset semantic network protocol, and filling the data by direct filling or calculation and filling.

[0093] Figure 9 FIG. 1 is a structural schematic diagram of a map processing device according to an embodiment of the present disclosure. The device can be implemented in hardware and / or software, and can be configured in an electronic device. Referring to FIG. 1, the map processing device 900 includes: Figure 9

[0094] The mapping relationship establishing module 901 is configured to establish a mapping relationship between map elements in a first map and a second map, wherein the first map has a higher precision than the second map.

[0095] ​The data integration module 902 is configured to integrate map data corresponding to a map element pair having the mapping relationship in the first map and the second map according to a preset semantic road network protocol, to obtain a target map satisfying requirements of the preset semantic road network protocol, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers.

[0096] The map processing apparatus provided by the embodiments of the present disclosure can quickly generate a target map satisfying requirements of a preset semantic road network protocol and applicable to various systems of the traffic management industry by using data in existing maps of different precisions, thereby effectively saving mapping costs. In addition, the preset semantic road network protocol adopts a data layered map description idea, so that the target map has computing capabilities of different spatial scales, and information in different layers can be shared and converted to each other, so that the computing results of different spatial scales can be consistent.

[0097] The preset semantic road network protocol corresponds to at least three spatial scales, and the at least three spatial scales include a macro scale, at least one meso scale, and a micro scale.

[0098] In an optional implementation, the macro scale includes a road intersection and a road; the meso scale includes a road breaking point and a road segment, the road breaking point is used to represent a position where a number of lanes and / or lane lines in a same road changes, and the road segment takes the road intersection and / or the road breaking point as an endpoint; and the micro scale includes a lane.

[0099] In an optional implementation, a data structure corresponding to the preset layer includes a field used to represent a static traffic semantic and / or a dynamic traffic semantic.

[0100] In an optional implementation, the map element includes a point element and a line element, the point element includes the road intersection, and the line element includes the road.

[0101] The mapping relationship establishing module includes:

[0102] The coordinate conversion unit is configured to convert the first map and the second map to a same preset coordinate system.

[0103] The first mapping relationship establishing unit is configured to establish a first mapping relationship of the point elements based on a distance relationship of the point elements in the first map and the second map in the preset coordinate system.

[0104] The second mapping relationship establishing unit is configured to determine whether end points of the line elements in the first map and the second map match based on the first mapping relationship, and establish a second mapping relationship of the line elements according to a determination result.

[0105] In an optional implementation, the second mapping relationship establishing unit comprises:

[0106] The target line element determining subunit is configured to, for a first line element in the second map, find a target line element in which a start point and / or an end point exist in the first mapping relationship from the first map.

[0107] The second line element determining subunit is configured to determine the target line element and a line element in the second map in which an overlay relationship and / or a connectivity relationship exist with the target line element as a second line element.

[0108] The mapping relationship establishing subunit is configured to establish a second mapping relationship of the first line element and the second line element.

[0109] In an optional implementation, the mapping relationship establishing subunit comprises:

[0110] The initial relationship establishing subunit is configured to establish an initial mapping relationship of the first line element and the second line element.

[0111] The relationship verifying subunit is configured to, for a line element pair in which the initial mapping relationship exists, determine whether a preset verification index matches successfully, and if the preset verification index matches successfully, determine that the verification is passed, and determine the initial mapping relationship that passes the verification as the second mapping relationship of the line element, wherein the preset verification index comprises at least one of a length of a line element, a distance of a line element, an azimuth angle of a line element, and a name of a line element.

[0112] In an optional implementation, the data integration module comprises:

[0113] The data obtaining unit is configured to determine a to-be-filled field in a preset semantic network protocol, and obtain, from the first map and the second map, map data corresponding to the to-be-filled field of a map element in which the mapping relationship exists.

[0114] The data filling unit is configured to fill the obtained map data into the to-be-filled field, and / or perform calculation on the obtained map data according to a preset calculation manner, and fill a calculation result into the to-be-filled field.

[0115] The map generating unit is configured to generate a target map meeting a requirement of the preset semantic network protocol according to a filling result.

[0116] In the technical solutions of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information comply with relevant laws and regulations and do not violate public order and good customs.

[0117] According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0118] Figure 10 A schematic block diagram of an example electronic device 1000 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.

[0119] As shown in Figure 10 The electronic device 1000 includes a computing unit 1001 that can perform various appropriate actions and processes in accordance with a computer program stored in a read-only memory (ROM) 1002 or a computer program loaded from a storage unit 1008 into a random access memory (RAM) 1003. Various programs and data required for the operation of the electronic device 1000 can also be stored in the RAM 1003. The computing unit 1001, the ROM 1002, and the RAM 1003 are connected to each other through a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0120] Various components in the electronic device 1000 are connected to the I / O interface 1005, including an input unit 1006, such as a keyboard, a mouse, etc.; an output unit 1007, such as various types of displays, speakers, etc.; the storage unit 1008, such as a magnetic disk, an optical disk, etc.; and a communication unit 1009, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1009 allows the electronic device 1000 to exchange information / data with other devices through a computer network, such as the Internet, and / or various telecommunication networks.

[0121] The computing unit 1001 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1001 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1001 performs various methods and processes described above, such as the map processing method. For example, in some embodiments, the map processing method can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 1008. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 1000 via the ROM 1002 and / or the communication unit 1009. When the computer program is loaded onto the RAM 1003 and executed by the computing unit 1001, one or more steps of the map processing method described above can be performed. Alternatively, in other embodiments, the computing unit 1001 can be configured to perform the map processing method by any other suitable means, such as by means of firmware.

[0122] Various implementations of the systems and techniques described above 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.

[0123] 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 a means for implementing the functions / acts 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.

[0124] In the context of this 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.

[0125] 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) 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.

[0126] 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), blockchain network, and the Internet.

[0127] The computer system can include clients and servers. This relationship can be. The servers are generally remote from the users and can be accessed via the Internet using a communication network. The relationship can be a client-server relationship over a communications network, and as such both the client and the server are typically computers, or other client and server computers. In a client-server relationship, the server is often providing functionality and data to the client. For example, the server can provide data, or functionality, to the client using any one of a number of protocols that are well known to those of ordinary skill in the art.

[0128] Artificial intelligence is a discipline that studies enabling computers to simulate some human thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), both hardware and software technologies. Artificial intelligence hardware technology generally includes technologies such as sensors, special artificial intelligence chips, cloud computing, distributed storage, big data processing, etc.; artificial intelligence software technology mainly includes computer vision technology, speech recognition technology, natural language processing technology, machine learning / deep learning technology, big data processing technology, knowledge graph technology, etc.

[0129] Cloud computing refers to accessing elastic and scalable shared physical or virtual resource pools through a network, which can include servers, operating systems, networks, software, applications, and storage devices, and can deploy and manage resources in a self-service manner as needed. Through cloud computing technology, powerful data processing capabilities can be provided for artificial intelligence, blockchain, and other technology applications and model training.

[0130] It should be understood that various forms of the flow shown above can be used to reorder, add or delete steps. For example, the steps described in the present disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions provided by the present disclosure can be achieved, which is not limited herein.

[0131] The above detailed description does not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent replacements and improvements within the spirit and principles of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A method for processing a map, comprising: establishing a mapping relationship of map elements in a first map and a second map, wherein the first map has a higher precision than the second map, the map elements comprise point elements and line elements, the point elements comprise road junctions, and the line elements comprise roads; integrating map data corresponding to the map elements having the mapping relationship in the first map and the second map according to a preset semantic road network protocol to obtain a target map satisfying requirements of the preset semantic road network protocol, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers; wherein the establishing of the mapping relationship of the map elements in the first map and the second map comprises: converting the first map and the second map to a same preset coordinate system; establishing a first mapping relationship of the point elements based on a distance relationship of the point elements in the first map and the second map in the preset coordinate system; for a first line element in the second map, finding a target line element having the first mapping relationship in the first map from a starting point and / or an ending point of the first line element; determining the target line element and a line element having an overlay relationship and / or a connectivity relationship with the target line element in the second map as a second line element; establishing a second mapping relationship of the first line element and the second line element; wherein the finding of the target line element having the first mapping relationship in the first map from the starting point and / or the ending point of the first line element in the second map comprises: for the first line element in the second map, if a starting point of a first to-be-judged line element in the first map has the first mapping relationship with the first line element, but an ending point of the first to-be-judged line element does not have the first mapping relationship with an ending point of the first line element, finding a second to-be-judged line element having an overlay relationship and / or a connectivity relationship with the first to-be-judged line element, and if an ending point of the second to-be-judged line element has the first mapping relationship with the ending point of the first line element, determining the first to-be-judged line element and the second to-be-judged line element as the target line element.

2. The method of claim 1, wherein, The preset semantic road network protocol corresponds to at least three spatial scales, and the at least three spatial scales comprise a macro scale, at least one meso scale, and a micro scale.

3. The method of claim 2, wherein, The macro scale comprises road junctions and roads, the meso scale comprises road break points and road segments, the road break points are used to represent positions where the number of lanes and / or lane lines in a same road changes, and the road segments have the road junctions and / or the road break points as endpoints, and the micro scale comprises lanes.

4. The method of claim 1, wherein, A data structure corresponding to the preset layer comprises a field used to represent static traffic semantics and / or dynamic traffic semantics.

5. The method of claim 1, wherein, The establishing of the second mapping relationship of the first line element and the second line element comprises: establishing an initial mapping relationship of the first line element and the second line element; For the line element pair with the initial mapping relationship, it is determined whether a preset verification index matches successfully, if the matching is successful, it is determined that the verification is passed, and the initial mapping relationship that passes the verification is determined as the second mapping relationship of the line element, wherein the preset verification index includes at least one of the length of the line element, the distance of the line element, the azimuth angle of the line element and the name of the line element.

6. The method of claim 1, wherein, According to the preset semantic road network protocol, the map data corresponding to the map element pair with the mapping relationship in the first map and the second map is integrated to obtain a target map meeting the requirements of the preset semantic road network protocol, including: Determine the to-be-filled field in the preset semantic network protocol, and obtain the map data corresponding to the to-be-filled field of the map element with the mapping relationship from the first map and the second map; Fill the obtained map data into the to-be-filled field; and / or, calculate the obtained map data according to a preset calculation method, and fill the calculation result into the to-be-filled field; According to the filling result, a target map meeting the requirements of the preset semantic road network protocol is generated.

7. A map processing apparatus, comprising: a mapping relationship establishing module, configured to establish a mapping relationship of map elements in a first map and a second map, wherein the accuracy of the first map is higher than the accuracy of the second map, the map elements include point elements and line elements, the point elements include road intersections, and the line elements include roads; a data integration module, configured to integrate map data corresponding to the map elements with the mapping relationship in the first map and the second map according to a preset semantic road network protocol, to obtain a target map meeting the requirements of the preset semantic road network protocol, wherein the preset semantic road network protocol corresponds to at least two spatial scales, each spatial scale corresponds to at least one preset layer, and there is an association relationship between different preset layers; wherein the mapping relationship establishing module comprises: a coordinate conversion unit, configured to convert the first map and the second map to the same preset coordinate system; a first mapping relationship establishing unit, configured to establish a first mapping relationship of the point elements based on the distance relationship of the point elements in the first map and the second map in the preset coordinate system; a second mapping relationship establishing unit, configured to determine whether the endpoints of the line elements in the first map and the second map match based on the first mapping relationship, and establish a second mapping relationship of the line elements according to the determination result; the second mapping relationship establishing unit comprises: a target line element determining subunit, configured to find a target line element with the first mapping relationship of the starting point and / or the ending point from the first map for a first line element in the second map; a second line element determining subunit, configured to determine the target line element and the line elements with the overlying relationship and / or the connected relationship with the target line element in the second map as second line elements; a mapping relationship establishing subunit, configured to establish a second mapping relationship of the first line element and the second line elements. The first mapping relationship includes a start point and / or an end point of the first line element in the first map. For the first line element in the second map, if the start point of the first to-be-judged line element in the first map has the first mapping relationship with the first line element, but the end point of the first to-be-judged line element does not have the first mapping relationship with the end point of the first line element, a second to-be-judged line element having a cover relationship and / or a communication relationship with the first to-be-judged line element is found, and if the end point of the second to-be-judged line element has the first mapping relationship with the end point of the first line element, the first to-be-judged line element and the second to-be-judged line element are determined as target line elements.

8. The apparatus of claim 7, wherein, The preset semantic road network protocol corresponds to at least three spatial scales, including a macro scale, at least one meso scale, and a micro scale.

9. The apparatus of claim 8, wherein, The macro scale includes road intersections and roads, the meso scale includes road breaking points and road segments, the road breaking points are used to represent positions where the number of lanes and / or lane lines in the same road change, and the road segments have the road intersections and / or the road breaking points as end points, and the micro scale includes lanes.

10. The apparatus of claim 7, wherein, The data structure corresponding to the preset layer includes a field used to represent static traffic semantics and / or dynamic traffic semantics.

11. The apparatus of claim 7, wherein, The mapping relationship establishing subunit includes: An initial relationship establishing subunit, configured to establish an initial mapping relationship of the first line element and the second line element; A relationship verifying subunit, configured to determine whether a preset verification index matches successfully for a line element pair having the initial mapping relationship, and if the preset verification index matches successfully, determine that the initial mapping relationship passes the verification, and determine the initial mapping relationship that passes the verification as a second mapping relationship of the line element, where the preset verification index includes at least one of a length of a line element, a distance of a line element, an azimuth angle of a line element, and a name of a line element.

12. The apparatus of claim 7, wherein, The data integration module includes: A data acquisition unit, configured to determine a to-be-filled field in a preset semantic network protocol, and acquire, from the first map and the second map, map data of a map element having the mapping relationship and corresponding to the to-be-filled field; A data filling unit, configured to fill the acquired map data into the to-be-filled field, and / or perform calculation on the acquired map data according to a preset calculation manner, and fill a calculation result into the to-be-filled field; A map generation unit, configured to generate a target map meeting a requirement of the preset semantic road network protocol according to a filling result.

13. An electronic device, comprising: at least one processor; and a memory connected with the at least one processor in communication; 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 of any one of claims 1-6.

14. A non-transitory computer readable storage medium having stored thereon computer instructions, wherein, The computer instructions are used to enable the computer to perform the method of any one of claims 1-6.

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