CN116977574A

CN116977574A - Data processing method, device and computer readable storage medium

Info

Publication number: CN116977574A
Application number: CN202210435255.5A
Authority: CN
Inventors: 肖童星
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2022-04-24
Filing date: 2022-04-24
Publication date: 2023-10-31

Abstract

The application discloses a data processing method, equipment and a computer readable storage medium, wherein the method comprises the following steps: determining the position association relation between at least two target position points in a two-dimensional road network; generating a set of relative elevation constraint conditions corresponding to at least two target position points according to the position association relation between the at least two target position points; the relative elevation constraint condition set is used for indicating conditions which are required to be met by the relative elevations corresponding to the at least two target position points respectively; determining initial distribution characteristic information of initial relative elevations corresponding to at least two target position points respectively; based on the initial distribution characteristic information and the relative elevation constraint condition set, respectively adjusting at least two initial relative elevations to obtain the relative elevations corresponding to at least two target position points respectively. By adopting the application, the acquisition cost of elevation data can be saved and the accuracy of relative elevation can be improved. The embodiment of the application can be applied to various fields such as map fields, traffic fields and the like.

Description

Data processing method, device and computer readable storage medium

Technical Field

The present application relates to the field of internet technologies, and in particular, to a data processing method, apparatus, and computer readable storage medium.

Background

Along with the development of society, road traffic becomes more and more complicated, and people often need to complete route planning, route navigation and the like by means of an electronic map when going out. Because the two-dimensional electronic map (including the two-dimensional information of the road, namely, the longitude information and the latitude information) cannot intuitively display the space spread of the overpass and the overhead road, the requirement of the three-dimensional electronic map (including the longitude information, the latitude information and the altitude information of the road) is more and more obvious.

In order to generate relative elevation data for navigation, the prior art generally adopts a laser real-time positioning and mapping (Simultaneous Localization and Mapping, abbreviated as SLAM) technology, and combines with other high-precision sensors to collect absolute elevation data, and then converts the collected absolute elevation data into relative elevation data. Obviously, the elevation data acquisition cost of this technique is very high.

Disclosure of Invention

The embodiment of the application provides a data processing method, a device, equipment and a computer readable storage medium, which not only can save the acquisition cost of elevation data of a target position point, but also can improve the accuracy of the relative elevation of the target position point.

In one aspect, an embodiment of the present application provides a data processing method, including:

acquiring at least two target position points of a road from a two-dimensional road network, and determining a position association relationship between the at least two target position points;

generating a set of relative elevation constraint conditions corresponding to at least two target position points according to the position association relation between the at least two target position points; the relative elevation constraint condition set is used for indicating conditions which are required to be met by the relative elevations corresponding to the at least two target position points respectively;

acquiring initial relative elevations corresponding to at least two target position points respectively, and determining initial distribution characteristic information of the at least two initial relative elevations;

based on the initial distribution characteristic information and the relative elevation constraint condition set, respectively adjusting at least two initial relative elevations to obtain the relative elevations corresponding to at least two target position points respectively.

In one aspect, an embodiment of the present application provides a data processing apparatus, including:

the first determining module is used for acquiring at least two target position points of a road from the two-dimensional road network and determining the position association relationship between the at least two target position points;

the first generation module is used for generating a set of relative elevation constraint conditions corresponding to at least two target position points according to the position association relation between the at least two target position points; the relative elevation constraint condition set is used for indicating conditions which are required to be met by the relative elevations corresponding to the at least two target position points respectively;

The second determining module is used for acquiring initial relative elevations corresponding to at least two target position points respectively and determining initial distribution characteristic information of the at least two initial relative elevations;

the second generation module is used for respectively adjusting at least two initial relative elevations based on the initial distribution characteristic information and the relative elevation constraint condition set to obtain the relative elevations respectively corresponding to at least two target position points.

Wherein, the first determination module includes:

the first acquisition unit is used for acquiring a road from navigation data corresponding to the two-dimensional road network, and acquiring a starting point corresponding to the road and a termination point corresponding to the road;

the first determining unit is used for determining a starting point and an ending point as at least two target position points if the relative elevation description information for the road does not exist in the navigation data;

the second determining unit is used for acquiring the capping point indicated by the relative elevation description information if the relative elevation description information for the road exists in the navigation data, and determining the capping point, the starting point and the ending point indicated by the relative elevation description information as at least two target position points; and the capping point indicated by the relative elevation description information is used for indicating that the road relationship corresponding to the road comprises a road capping relationship.

Wherein the at least two target location points comprise a target location point W _o O is a positive integer, and o is less than or equal to the total number of at least two target position points; the road includes a target position point W _o A first road to which the road belongs;

a first determination module comprising:

a second acquisition unit for acquiring, at least two target positionsIn the points, the point W belonging to the first road and corresponding to the target position is obtained _o Adjacent target position points as adjacent target position points;

a third determining unit for determining adjacent target position points and target position points W _o The two have adjacent association relations;

a fourth determining unit for determining the target position point W according to the first road _o Road relation of adjacent target position point and target position point W _o Adjacent association relation between the target position points W is determined _o Is a positional association relation of (a) and (b).

Wherein the fourth determination unit includes:

a first determination subunit for determining if the first road is at the target position point W _o Without road relation, adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a position association relation of the plurality of images;

a first acquisition subunit for acquiring the first road at the target position point W _o The road relation of the road map is a road map relation, and a first target position point is obtained from at least two target position points; the relative elevation corresponding to the first target position point is equal to the target position point W _o The corresponding relative elevation has an elevation difference, and the two-dimensional position information corresponding to the first target position point is equal to the target position point W _o The corresponding two-dimensional position information is the same;

a second determination subunit for determining the first target position point and the target position point W _o The two have an up-down association relation;

a third determination subunit for combining the first target position point with the target position point W _o Upper and lower association relation between adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

Wherein the fourth determination unit includes:

a second acquisition subunit for acquiring the first road at the target position point W _o The road relation of (a) is roadThe road adjacency relation, a second target position point belonging to a second road is obtained from at least two target position points; the relative elevation corresponding to the first target position point is equal to the target position point W _o No height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the first target position point and the target position point W _o The corresponding two-dimensional position information is the same; the second road belongs to the road;

a fourth determination subunit for determining the second target position point and the target position point W _o The adjacent incidence relation is formed between the two;

a fifth determination subunit for comparing the second target position point with the target position point W _o Adjacent association relation between adjacent target position points and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

Wherein the fourth determination unit includes:

a third acquisition subunit for determining if the first road is at the target position point W _o The road relation of (1) comprises a road adjacency relation and a road capping relation, and a third target position point belonging to a third road is acquired from at least two target position points based on the road adjacency relation; the relative elevation corresponding to the third target position point is equal to the target position point W _o No height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the third target position point and the target position point W _o The corresponding two-dimensional position information is the same; the third road belongs to the road;

the third acquisition subunit is further used for acquiring a fourth target position point in the at least two target position points based on the road capping relation; the relative elevation corresponding to the fourth target position point is equal to the target position point W _o The corresponding relative elevation has a height difference, and the two-dimensional position information corresponding to the fourth target position point is equal to the target position point W _o The corresponding two-dimensional position information is the same;

a sixth determining subunit for determining a third target position point and a target position point W _o The adjacent incidence relation is formed between the two;

a sixth determining subunit for determining a fourth target position point and a target position point W _o The two have an up-down association relation;

a sixth determination subunit for comparing the third target position point with the target position point W _o Adjacent incidence relation between the fourth target position point and the target position point W _o Upper and lower association relation between adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

Wherein, the first generation module includes:

a third obtaining unit, configured to obtain a target location point pairs having a location association relationship according to a location association relationship between at least two target location points; a is a positive integer, and A target position point pairs comprise target position point pairs B _c The method comprises the steps of carrying out a first treatment on the surface of the c is a positive integer and c is less than or equal to A;

a condition generating unit for generating a target position point pair B _c The position association relationship generates a target position point pair B _c Is a relative elevation constraint of (2);

and a fifth determining unit, configured to determine the corresponding relative elevation constraint conditions of the a target location points as a set of relative elevation constraint conditions corresponding to at least two target location points.

Wherein the condition generating unit includes:

a first generation subunit for generating a target position point pair B _c The position association relationship is adjacent association relationship, and B is based on the target position point pair _c Two-dimensional position information and target gradient corresponding to two target position points respectively, and generating a target position point pair B _c Is a relative elevation constraint of (2);

a second generation subunit for generating a target position point pair B _c The position association relationship is up-down association relationship, and B is based on the target position point pair _c Relative elevation up-down information of two target position points in the model, and target height difference, and generating a target position point pair B _c Is a relative elevation constraint of (2);

a third generation subunit for generating a target position point pair B _c If the position association relationship is adjacent association relationship, generating a target position point pair B according to the target adjacent information _c Is a relative elevation constraint of (2).

Wherein the first generation subunit is specifically configured to generate a target position point pair B according to _c Two-dimensional position information corresponding to two target position points in the map, and determining a target position point pair B _c Two-dimensional planar distance D between two target position points in (2) _c ；

A first generation subunit, configured to generate a square value of a tangent value of the target gradient, for the two-dimensional plane distance D _c The square value of the square value and the square value of the tangent value are multiplied to obtain a constraint value E _c ；

A first generation subunit, which is also specifically configured to pair B target location points _c The square value of the height difference between the corresponding relative elevations of the two target position points is smaller than the constraint value E _c Is determined to be for the target position point pair B _c Is a relative elevation constraint of (2).

Wherein the second generation subunit is specifically configured to generate the target position point pair B according to _c The relative elevation up-down information of two target position points in the model (B) is used for constructing a target position point pair (B) _c Forward height difference F of two target position points in (a) _c ；

A second generation subunit for generating a forward height difference F _c Greater than the target altitude difference, determined as being for the target position point pair B _c Is a relative elevation constraint of (2).

Wherein the second determining module comprises:

A fourth acquiring unit for acquiring a relatively high Cheng Youhua device and inputting at least two initial relative elevations to the relatively high Cheng Youhua device; the relative elevation optimizer includes a distribution feature function;

and a sixth determining unit for determining initial distribution characteristic information of at least two initial relative elevations through the distribution characteristic function.

Wherein the sixth determination unit includes:

the fourth acquisition subunit is used for acquiring square values corresponding to at least two initial relative elevations respectively through the distribution characteristic function;

the fourth generation subunit is used for summing square values corresponding to at least two initial relative elevations respectively to obtain a dispersion degree value of at least two initial relative heights Cheng Duiying;

a seventh determining subunit configured to determine the dispersion degree value of the at least two initial relative heights Cheng Duiying as initial distribution characteristic information of the at least two initial relative elevations.

Wherein, the second generation module includes:

a first input unit for inputting a set of relative elevation constraints to a relative elevation Cheng Youhua machine;

the first adjusting unit is used for respectively adjusting at least two initial relative elevations based on the initial distribution characteristic information in the relative elevation optimizer to obtain relative elevations to be optimized, which correspond to at least two target position points respectively; at least two relative elevations to be optimized meet the relative elevation constraint conditions in the relative elevation constraint condition set;

The second input unit is used for inputting at least two relative elevations to be optimized into the distribution characteristic function, and determining distribution characteristic information to be optimized of the at least two relative elevations to be optimized through the distribution characteristic function;

the second adjusting unit is used for respectively adjusting at least two relative elevations to be optimized based on the distribution characteristic information to be optimized to obtain relative elevations corresponding to at least two target position points respectively; the dispersion degree value corresponding to the distribution characteristic information of at least two relative elevations is smaller than the dispersion degree value corresponding to the distribution characteristic information to be optimized, and the at least two relative elevations meet the relative elevation constraint condition set.

Wherein the second adjusting unit includes:

a fifth generating subunit, configured to adjust at least two relative elevations to be optimized based on the distribution feature information to be optimized, so as to obtain candidate relative elevations corresponding to at least two target position points respectively;

an eighth determining subunit, configured to input at least two candidate relative elevations to a distribution feature function, and determine candidate distribution feature information of the at least two candidate relative elevations through the distribution feature function;

and the ninth determination subunit is used for determining the relative elevation corresponding to at least two target position points respectively according to the distribution characteristic information to be optimized and the candidate distribution characteristic information.

The ninth determining subunit is specifically configured to determine a dispersion degree value corresponding to the distribution characteristic information to be optimized and a dispersion distance between the dispersion degree values corresponding to the candidate distribution characteristic information;

the ninth determining subunit is further specifically configured to obtain, if the dispersion distance is smaller than the dispersion distance threshold, a relative elevation corresponding to each of the at least two target position points from the relative elevation set; the relative elevation set comprises at least two relative elevations to be optimized and at least two candidate relative elevations;

and the ninth determination subunit is further specifically configured to, if the dispersion distance is equal to or greater than the dispersion distance threshold, respectively adjust at least two candidate relative elevations based on the candidate distribution feature information, so as to obtain the relative elevations corresponding to the at least two target position points respectively.

Wherein, the data processing device still includes:

the first acquisition module is used for acquiring position points except at least two target position points in the road from navigation data corresponding to the two-dimensional road network as intermediate position points;

the second acquisition module is used for acquiring a fifth target position point and a sixth target position point which respectively have adjacent association relations with the middle position point in at least two target position points;

The third determining module is used for determining the relative elevation corresponding to the intermediate position point according to the fifth target position point and the sixth target position point;

and the fourth determining module is used for determining the relative elevation corresponding to the at least two target position points and the relative elevation corresponding to the middle position point as the relative elevation corresponding to the road.

Wherein the third determining module includes:

a seventh determining subunit, configured to determine, if the relative elevation corresponding to the fifth target position point is greater than the relative elevation corresponding to the sixth target position point, a relative elevation difference between the relative elevation corresponding to the fifth target position point and the relative elevation corresponding to the sixth target position point;

an eighth determining subunit, configured to determine a first two-dimensional plane distance between the sixth target location point and the intermediate location point, and determine a second two-dimensional plane distance between the fifth target location point and the sixth location point;

and the ninth determining subunit is configured to determine a distance ratio between the first two-dimensional plane distance and the second two-dimensional plane distance, and weight and sum the relative elevation difference and the relative elevation corresponding to the sixth target position point based on the distance ratio, so as to obtain the relative elevation corresponding to the intermediate position point.

In one aspect, the application provides a computer device comprising: a processor, a memory, a network interface;

the processor is connected to the memory and the network interface, where the network interface is used to provide a data communication function, the memory is used to store a computer program, and the processor is used to call the computer program to make the computer device execute the method in the embodiment of the present application.

In one aspect, embodiments of the present application provide a computer readable storage medium having a computer program stored therein, the computer program being adapted to be loaded by a processor and to perform a method according to embodiments of the present application.

In one aspect, embodiments of the present application provide a computer program product comprising a computer program stored on a computer readable storage medium; the processor of the computer device reads the computer program from the computer-readable storage medium, and the processor executes the computer program, so that the computer device performs the method in the embodiment of the present application.

In the embodiment of the application, based on the position association relation between at least two target position points of the road in the two-dimensional road network, the computer equipment can generate a relative elevation constraint condition set, and further can generate relative elevations corresponding to the at least two target position points meeting the relative elevation constraint condition set. The method and the device can save the acquisition cost of the elevation data of the target position point and improve the accuracy of the relative elevation of the target position point.

Drawings

In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of a system architecture according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a scenario for data processing according to an embodiment of the present application;

FIG. 3 is a flowchart illustrating a data processing method according to an embodiment of the present application;

FIG. 4 is a second schematic diagram of a scenario of data processing according to an embodiment of the present application;

FIG. 5 is a second flow chart of a data processing method according to an embodiment of the present application;

FIG. 6 is a third schematic view of a scenario of data processing according to an embodiment of the present application;

FIG. 7 is a flowchart illustrating a data processing method according to an embodiment of the present application;

FIG. 8 is a schematic diagram of a data processing apparatus according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of a computer device according to an embodiment of the present application.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

For ease of understanding, the related concepts will first be explained.

The intelligent vehicle-road cooperative system (Intelligent Vehicle Infrastructure Cooperative Systems, IVICS), which is simply called a vehicle-road cooperative system, is one development direction of an Intelligent Transportation System (ITS). The vehicle-road cooperative system adopts advanced wireless communication, new generation internet and other technologies, carries out vehicle-vehicle and vehicle-road dynamic real-time information interaction in all directions, develops vehicle active safety control and road cooperative management on the basis of full-time idle dynamic traffic information acquisition and fusion, fully realizes effective cooperation of people and vehicles and roads, ensures traffic safety, improves traffic efficiency, and forms a safe, efficient and environment-friendly road traffic system.

Absolute elevation refers to the distance from a point to an absolute base in the direction of the plumb line, simply referred to as elevation.

Relative elevation refers to the distance of a point in the direction of the plumb line from a hypothetical level base, also known as a hypothetical elevation. In the present application, the relative elevation of the road is considered as the difference in elevation between each point on the road and the ground, and the set leveling base is the ground.

SD maps, standard Definition Map, common navigation electronic maps, are generally two-dimensional, with no elevation information.

HD maps, high Definition Map, high-precision maps, can accurately and comprehensively characterize road features.

The optimization is a branch of application mathematics, and mainly refers to a method for selecting a certain research scheme to optimize a target under a certain condition limit.

Convex optimization: also called convex optimization, which is a sub-field of mathematical optimization, the problem of minimizing convex functions defined in a convex set is studied, in a way that is simpler than the mathematical optimization problem of the general case.

The interior point method is an algorithm for solving a linear programming or nonlinear convex optimization problem.

The application relates to the map field and the traffic field, and the specific implementation process is shown in the following embodiments.

Referring to fig. 1, fig. 1 is a schematic diagram of a system architecture according to an embodiment of the application. As shown in fig. 1, the system may include a service server 100 and a terminal device cluster, where the terminal device cluster may include: the terminal apparatuses 200a, 200b, 200c, …, and 200n, it will be appreciated that the above system may include one or more terminal apparatuses, and the present application is not limited to the number of terminal apparatuses.

Wherein a communication connection may exist between the clusters of terminal devices, for example, a communication connection exists between terminal device 200a and terminal device 200b, and a communication connection exists between terminal device 200a and terminal device 200 c. Meanwhile, any terminal device in the terminal device cluster may have a communication connection with the service server 100, for example, a communication connection exists between the terminal device 200a and the service server 100, where the communication connection is not limited to a connection manner, may be directly or indirectly connected through a wired communication manner, may be directly or indirectly connected through a wireless communication manner, or may also be other manners, and the application is not limited herein.

It should be understood that each terminal device in the cluster of terminal devices shown in fig. 1 may be provided with an application client, which, when running in the respective terminal device, may interact with the service server 100 shown in fig. 1, i.e. the communication connection described above, respectively. The application client may be an application client with a map loading function, such as a video application, a social application, an instant messaging application, a navigation application, a music application, a shopping application, an electronic map application, a browser, and the like. The application client may be an independent client, or may be an embedded sub-client integrated in a certain client (for example, a social client, a travel client, etc.), which is not limited herein. Taking an electronic map application as an example, the service server 100 may be a set of multiple servers including a background server, a data processing server and the like corresponding to the electronic map application, so that each terminal device may perform data transmission with the service server 100 through an application client corresponding to the electronic map application, for example, each terminal device may upload its local two-dimensional road network to the service server 100 through an application client of the electronic map application, and further the service server 100 may generate a three-dimensional road network based on the two-dimensional road network and return the three-dimensional road network to the terminal device.

It will be appreciated that in embodiments of the present application, data relating to user information (e.g., two-dimensional road networks) and the like, when embodiments of the present application are applied to a particular product or technology, user approval or consent is required, and the collection, use and processing of the relevant data is required to comply with relevant laws and regulations and standards of the relevant country and region.

For the convenience of subsequent understanding and description, the embodiment of the present application may select one terminal device as a target terminal device in the terminal device cluster shown in fig. 1, for example, use the terminal device 200a as a target terminal device. When the two-dimensional road network is obtained and a generation instruction for converting the two-dimensional road network into the three-dimensional road network is received, the terminal device 200a can send the two-dimensional road network as data to be processed to the service server 100; the road network corresponding to the common navigation electronic (SD) map is called a two-dimensional road network, navigation data which does not contain elevation information but provides longitude information, latitude information and road relation between roads is called navigation data corresponding to the two-dimensional road network, and the navigation data are all navigation data corresponding to the two-dimensional road network.

Further, after receiving the data to be processed (i.e., the two-dimensional road network) sent by the terminal device 200a, the service server 100 may obtain at least two target location points of the road from the two-dimensional road network, where the at least two target location points include the following two parts: 1. the road is positioned at the point of the capping area; 2. a starting point of the road and an ending point of the road. Further, the service server 100 determines a positional association relationship between at least two target position points; according to the position association relation between the at least two target position points, a relative elevation constraint condition set corresponding to the at least two target position points can be generated, wherein the relative elevation constraint condition set is used for indicating conditions required to be met by the relative elevations corresponding to the at least two target position points respectively; further, the service server 100 obtains initial relative elevations corresponding to at least two target location points respectively, obtains a relative elevation Cheng Youhua device including a distribution feature function, and inputs at least two initial relative elevations and a relative elevation constraint condition set to the relative elevation Cheng Youhua device; through the distribution feature function, the service server 100 may determine initial distribution feature information for at least two initial relative elevations; further, in the relative elevation optimizer, based on the initial distribution feature information and the set of relative elevation constraint conditions, the service server 100 may respectively adjust at least two initial relative elevations to obtain relative elevations corresponding to at least two target location points respectively. The at least two relative elevations not only meet the relative elevation constraint condition set, but also have the optimal dispersion degree value corresponding to the distribution characteristic information corresponding to the at least two relative elevations in the relative elevation constraint condition set.

Further, the service server 100 acquires, as the intermediate position point, position points other than at least two target position points in the road from the two-dimensional road network, and may acquire, among the at least two target position points, a fifth target position point and a sixth target position point each having an adjacent association relationship with the intermediate position point; further, the service server 100 may determine a relative elevation corresponding to the intermediate position point according to the fifth target position point and the sixth target position point; and determining the relative elevation corresponding to the road as the relative elevation corresponding to the at least two target position points and the relative elevation corresponding to the intermediate position points. Subsequently, the service server 100 transmits the relative elevation corresponding to the road to the terminal device 200a.

After receiving the relative elevation corresponding to the road sent by the service server 100, the terminal device 200a may render the road in the two-dimensional road network to generate a three-dimensional road network, where the three-dimensional road network includes a three-dimensional road, that is, a road with a spatial effect, and further, the terminal device 200a may display the three-dimensional road network on its corresponding screen.

Optionally, the service server 100 obtains the intermediate position point of the road in the two-dimensional road network by using the terminal device 200a and the terminal device 200a corresponding to the at least two target position points respectively at a relatively high Cheng Fanhui, and the subsequent process is consistent with the process of determining the relative elevation corresponding to the intermediate position point and further determining the relative elevation corresponding to the road by using the service server 100 according to the fifth target position point and the sixth target position point, so that the description is omitted.

Optionally, if the relative height Cheng Youhua device is stored locally in the terminal device 200a, the terminal device may acquire at least two target location points of the road from the two-dimensional road network, determine a location association relationship between the at least two target location points, and further, may generate a set of relative elevation constraint conditions corresponding to the at least two target location points according to the location association relationship between the at least two target location points; further, the terminal device 200a inputs the initial relative elevation corresponding to at least two target location points and the relative elevation constraint condition set to the relative elevation Cheng Youhua device, and the subsequent process is consistent with the process of obtaining the relative elevation corresponding to the road by the service server through the relative elevation Cheng Youhua device, so that the detailed description is omitted.

The relatively high Cheng Youhua device local to the terminal device 200a may be generated or updated by the service server 100 and then sent to the terminal device 200 a.

The embodiment of the application provides a method for generating the road relative elevation according to a two-dimensional road network, which has less original data and does not need precise equipment to collect the absolute elevation of the road, so that the information collection cost can be greatly reduced, and high-quality road relative elevation data for lane-level navigation can be efficiently generated.

It should be noted that, the service server 100, the terminal device 200a, the terminal device 200b, and the terminal device 200c may be a blockchain node in a blockchain network, and the data (for example, the two-dimensional road network and the relative elevation corresponding to at least two target location points) described in full text may be stored, where the storage mode may be a mode that the blockchain node generates a block according to the data and adds the block to the blockchain for storage.

The block chain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, a consensus mechanism, an encryption algorithm and the like, and is mainly used for sorting data according to time sequence, encrypting the data into an account book, preventing the account book from being tampered and forged, and simultaneously verifying, storing and updating the data. A blockchain is essentially a de-centralized database in which each node stores an identical blockchain, and a blockchain network can distinguish nodes into core nodes, data nodes, and light nodes. The core nodes, data nodes and light nodes together form a blockchain node. The core node is responsible for the consensus of the whole blockchain network, that is to say, the core node is a consensus node in the blockchain network. The process of writing the transaction data in the blockchain network into the ledger may be that a data node or a light node in the blockchain network acquires the transaction data, transfers the transaction data in the blockchain network (that is, the node transfers in a baton manner) until the transaction data is received by a consensus node, packages the transaction data into a block, performs consensus on the block, and writes the transaction data into the ledger after the consensus is completed. The transaction data is relatively high Cheng Shili corresponding to the two-dimensional road network and at least two target position points respectively, and the service server 100 (blockchain node) generates blocks according to the transaction data after the transaction data are identified, and stores the blocks into the blockchain network; for reading transaction data (i.e. the two-dimensional road network and the relative elevation corresponding to at least two target position points respectively), a block containing the transaction data can be obtained in the blockchain network by the blockchain node, and further, the transaction data can be obtained in the block.

It will be appreciated that the method provided by the embodiments of the present application may be performed by a computer device, including but not limited to a terminal device or a service server. The service server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing a cloud database, cloud service, cloud computing, cloud functions, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, basic cloud computing service such as big data and an artificial intelligence platform. Terminal devices include, but are not limited to, cell phones, computers, intelligent voice interaction devices, intelligent home appliances, vehicle terminals, aircraft, and the like. The terminal device and the service server may be directly or indirectly connected through a wired or wireless manner, which is not limited in the embodiment of the present application.

Further, referring to fig. 2, fig. 2 is a schematic diagram of a scenario of data processing according to an embodiment of the present application. The embodiment of the application can be applied to various scenes, including but not limited to cloud technology, artificial intelligence, intelligent transportation, auxiliary driving and the like. The embodiment of the application can be applied to service scenes such as map recommendation scenes, map distribution scenes, map search scenes and the like aiming at the three-dimensional electronic map, and specific service scenes are not listed one by one. The implementation process of the data processing scenario may be performed in a service server, or may be performed in a terminal device, or may be performed interactively in the terminal device and the service server, which is not limited herein. For convenience of description and understanding, embodiments of the present application will be described with reference to an example in a service server, where the service server may be the service server 100 of the embodiment corresponding to fig. 1.

The traffic server obtains navigation data not including road elevation data, which may include two-dimensional information of roads, and road relationships between the roads. Based on the navigation data, the service server may generate a two-dimensional road network, such as the two-dimensional road network 20a illustrated in fig. 2, and it should be noted that the present application does not limit the source of the navigation data, and may be actual navigation data, such as navigation data collected during driving; may be fictitious navigation data, such as that fictitious for the construction of an autopilot simulation system. In addition, the application does not limit the data content of the navigation data, the number of roads of the road, and the road relation between the roads, and can be set according to the practical application scene.

As shown in fig. 2, the two-dimensional road network 20a includes a road 201a and a road 202a, where a road capping relationship exists between the road 201a and the road 202a, and the intersection between a position point M1 of the road 201a and a position point M2 of the road 202a is in a two-dimensional plane, but the position point M1 and the position point M2 have a high-low relationship (up-down relationship), that is, the corresponding relative heights of the two are different, such as P (M1) > P (M2) in fig. 2; it should be noted that, the navigation data in the embodiment of the present application does not provide elevation data of the road, so elevation data of the location point in the road is not provided, but when the two location points are gland points, the up-down relationship of the two location points which are gland points can be provided, that is, P (M1) and P (M2) are unknown, but the magnitude relationship of P (M1) and P (M2) can be determined, where P (M1) represents the relative elevation corresponding to the location point M1 of the road 201a, and P (M2) represents the relative elevation corresponding to the location point M2 of the road 202 a. The road capping relation may represent that a projection intersection exists on a two-dimensional plane, but a position point (may be called a capping point) in the road corresponding to the projection intersection has an up-down relation.

Referring to fig. 2 again, the service server obtains a start point of the road 201a and an end point of the road 201a from the two-dimensional road network 20a, such as the position point K1 and the position point J1 in fig. 2, and obtains a start point of the road 202a and an end point of the road 202a, such as the position point G2 and the position point I2 in fig. 2; further, since the position point M1 of the road 201a and the position point M2 of the road 202a are in the capping area, the service server acquires the position point M1 and the position point M2, and determines the position point K1, the position point J1, the position point G2, the position point I2, the position point M1, and the position point M2 as at least two target position points 20b.

As can be seen from fig. 2, the road 201a includes 3 target location points, wherein the location point K1 is adjacent to the location point M1, and the location point J1 is adjacent to the location point M1, so that the location point K1 and the location point M1 have an adjacent association relationship, which can be also understood as that the target location point pair (K1, M1) has an adjacent association relationship; the position point M1 and the position point J1 have an adjacent association relationship, and it can be understood that the target position point pair (M1, J1) has an adjacent association relationship. The road 202a includes 3 target location points, where the location point G2 is adjacent to the location point M2, and the location point I2 is adjacent to the location point M2, so that the location point G2 and the location point M2 have an adjacent association relationship, which may also be understood as that the target location point pair (G2, M2) has an adjacent association relationship; the position point M2 and the position point I2 have an adjacent association relationship, and it can be understood that the target position point pair (M2, I2) has an adjacent association relationship. Since the position point M1 on the road 201a and the position point M2 on the road 202a are in the same capping area, the position point M1 and the position point M2 have a capping association (equivalent to a vertical association), and it can be understood that the target position point pair (M1, M2) has a vertical association.

Further, the service server determines the target position point pair (K1, M1), the target position point pair (M1, J1), the target position point pair (G2, M2), the target position point pair (M2, I2), and the target position point pair (M1, M2) having the upper and lower association relations, respectively, as the position association relation 20c between the at least two target position points 20 b.

Further, the service server can generate a relative elevation constraint condition 1 for the target position point pair (K1, M1) according to the target position point pair (K1, M1) with the adjacent association relation; from the target position point pair (M1, J1) having the adjacent association relation, a relative elevation constraint condition 2 for the target position point pair (M1, J1) can be generated; the service server can generate a relative elevation constraint condition 3 aiming at the target position point pair (G2, M2) according to the target position point pair (G2, M2) with the adjacent association relation; from the target position point pair (M2, I2) having the adjacent association relation, a relative elevation constraint condition 4 for the target position point pair (M2, I2) can be generated; the service server can generate a relative elevation constraint condition 5 aiming at the target position point pair (M1, M2) according to the target position point pair (M1, M2) with the upper-lower association relation; for a specific process of generating the relative altitude constraint by the service server, please refer to the following description of step S102 in the embodiment corresponding to fig. 3, which will not be described herein.

Referring to fig. 2 again, the service server combines the relative altitude constraint 1, the relative altitude constraint 2, the relative altitude constraint 3, the relative altitude constraint 4, and the relative altitude constraint 5 into a set of relative altitude constraints 20d corresponding to at least two target location points 20 b. It will be appreciated that a target location point pair has a location association, so that a target location point pair corresponds to a relative elevation constraint. For ease of description and understanding, fig. 2 illustrates that the total number of target location point pairs is equal to 5, so that 5 relative elevation constraints are included in the set of relative elevation constraints 20d.

Further, the service server obtains initial relative heights corresponding to at least two target location points, as illustrated in fig. 2, where at least two initial relative heights 20e are 0, and it is obvious that the initial relative height (P (M1) =0) corresponding to the target location point M1 and the initial relative height (P (M2) =0) corresponding to the target location point M2 do not satisfy the upper-lower association relationship between the target location point M1 and the target location point M2. The service server determines initial distribution characteristic information of at least two initial relative elevations 20e, adjusts the at least two initial relative elevations 20e based on the initial distribution characteristic information and the relative elevation constraint condition set 20d respectively, and obtains the relative elevations corresponding to the at least two target position points respectively when the adjusted at least two relative elevations meet the relative elevation constraint condition set 20d and the distribution characteristic information corresponding to the adjusted at least two relative elevations is optimal. The above-mentioned process is not described in detail, and please refer to the description of step S103-step S104 in the embodiment corresponding to fig. 3 below.

As can be seen from the above, the embodiment of the present application converts the problem of generating the relative elevation into the optimization problem by using only the positional association relationship of the road at a plurality of points, so that the road relative elevation data with high quality can be generated at low cost.

Further, referring to fig. 3, fig. 3 is a flowchart illustrating a data processing method according to an embodiment of the application. The data processing method may be performed by a service server (e.g., the service server 100 shown in fig. 1 described above), or may be performed by a terminal device (e.g., the terminal device 200a shown in fig. 1 described above), or may be performed interactively by the service server and the terminal device. For easy understanding, the embodiment of the present application is described as an example in which the method is executed by a service server. As shown in fig. 3, the data processing method may include at least the following steps S101 to S104.

Step S101, at least two target position points of a road are obtained from a two-dimensional road network, and the position association relationship between the at least two target position points is determined.

Specifically, a road is obtained from navigation data corresponding to a two-dimensional road network, and a starting point corresponding to the road and an ending point corresponding to the road are obtained; if the relative elevation description information for the road does not exist in the navigation data, determining a starting point and an ending point as at least two target position points; if the relative elevation description information aiming at the road exists in the navigation data, acquiring a capping point indicated by the relative elevation description information, and determining the capping point, the starting point and the ending point indicated by the relative elevation description information as at least two target position points; and the capping point indicated by the relative elevation description information is used for indicating that the road relationship corresponding to the road comprises a road capping relationship.

Specifically, the at least two target location points include a target location point W _o O is a positive integer, and o is less than or equal to the total number of at least two target position points; the road includes a target position point W _o A first road to which the road belongs; in at least two target position points, acquiring a target position point W belonging to a first road _o Adjacent target position points as adjacent target position points; determining adjacent target position points and target position points W _o The two have adjacent association relations; according to the first road at the target position point W _o Road relation of adjacent target position point and target position point W _o Adjacent association relation between the target position points W is determined _o Is a positional association relation of (a) and (b).

Wherein the target position point W is determined _o The specific process of the position association relation of the (c) can comprise: if the first road is at the target position point W _o Without road relation, adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a position association relation of the plurality of images; if the first road is at the target position point W _o The road relation of the road map is a road map relation, and a first target position point is obtained from at least two target position points; the relative elevation corresponding to the first target position point is equal to the target position point W _o The corresponding relative elevation has an elevation difference, and the two-dimensional position information corresponding to the first target position point is equal to the target position point W _o The corresponding two-dimensional position information is the same; determining a first target position point and a target position point W _o The two have an up-down association relation; the first target position point and the target position point W _o Upper and lower association relation between adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

Wherein the target position point W is determined _o The specific process of the position association relation of the (c) can comprise: if the first road is at the target position point W _o The road relation of the road is a road adjacent relation, and a second target position point belonging to a second road is obtained from at least two target position points; the relative elevation corresponding to the first target position point is equal to the target position point W _o No height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the first target position point and the target position point W _o The corresponding two-dimensional position information is the same; the second road belongs to the road; determining a second target position point and a target position point W _o The adjacent incidence relation is formed between the two; second target position point and target position point W _o Adjacent association relation between adjacent target position points and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

Wherein the method comprises the steps ofDetermining a target position point W _o The specific process of the position association relation of the (c) can comprise: if the first road is at the target position point W _o The road relation of (1) comprises a road adjacency relation and a road capping relation, and a third target position point belonging to a third road is acquired from at least two target position points based on the road adjacency relation; the relative elevation corresponding to the third target position point is equal to the target position point W _o No height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the third target position point and the target position point W _o The corresponding two-dimensional position information is the same; the third road belongs to the road; acquiring a fourth target position point from at least two target position points based on the road capping relation; the relative elevation corresponding to the fourth target position point is equal to the target position point W _o The corresponding relative elevation has a height difference, and the two-dimensional position information corresponding to the fourth target position point is equal to the target position point W _o The corresponding two-dimensional position information is the same; determining a third target position point and a target position point W _o The adjacent incidence relation is formed between the two; determining a fourth target position point and a target position point W _o The two have an up-down association relation; a third target position point is combined with the target position point W _o Adjacent incidence relation between the fourth target position point and the target position point W _o Upper and lower association relation between adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

The service server acquires navigation data which does not comprise road elevation data, wherein the navigation data can comprise description information of roads, and particularly can comprise road identifications, position points carrying two-dimensional position information in the roads and road relations among the roads. The embodiment of the application does not limit the road mark, and can be any information which can be used for marking the road; for easy understanding and description, the embodiments of the present application only describe the target location point in the road, and herein, the intermediate location point in the road is not described temporarily, and for the description of the intermediate location point, please refer to the embodiment corresponding to fig. 5 below.

Based on the navigation data, the service server may generate a two-dimensional road network, please refer to fig. 4, and fig. 4 is a second schematic view of a data processing scenario provided by the embodiment of the present application. As shown in fig. 4, the two-dimensional road network 30b includes a road 301a, a road 302a, and a road 303a, wherein the road 301a includes a location point L1, a location point N1, a location point Q1, and a location point R1; the road 302a includes a location point T2, a location point Q2, a location point U2, a location point V2; the road 303a includes a position point X3, a position point N3, a position point U3, a position point Y3; the link 304a includes a location point V4 and a location point Z4. It should be noted that the location points (including the intermediate location points described below) mentioned in the present application all carry two-dimensional location information (i.e., longitude information and latitude information).

Referring to fig. 4 again, the service server obtains a start point of the road 301a and an end point of the road 301a from the two-dimensional road network 30b, such as the position point L1 and the position point R1 in fig. 4, and obtains a start point of the road 302a and an end point of the road 302a, such as the position point T2 and the position point V2 in fig. 4; the service server obtains the start point of the road 303a and the end point of the road 303a, such as the position point X3 and the position point Y3 in fig. 4, and obtains the start point of the road 304a and the end point of the road 304a, such as the position point V4 and the position point Z4 in fig. 4; if the relative elevation description information for the road does not exist in the navigation data, the service server determines the starting point and the ending point as at least two target position points.

Referring to fig. 4 again, fig. 4 illustrates that the navigation data includes the relative elevation description information for the road, and the relative elevation description information is illustrated with three relative elevation up-down information; the first relative elevation up-down information is that the position point N1 of the road 301a and the position point N3 of the road 303a intersect on a two-dimensional plane, but the position point N1 and the position point N3 have an up-down relationship, as illustrated in fig. 4, P (N1) > P (N3), that is, the relative elevation corresponding to each of the two is different, where P (N1) and P (N3) are unknown, P (N1) represents the relative elevation corresponding to the position point N1 of the road 301a, and P (N3) represents the relative elevation corresponding to the position point N3 of the road 303 a. The second relative elevation up-down information is that the position point Q1 of the road 301a and the position point Q2 of the road 302a intersect on a two-dimensional plane, but the position point Q1 and the position point Q2 have an up-down relationship, as illustrated by P (Q1) > P (Q2) in fig. 4, where P (Q1) and P (Q2) are unknown, P (Q1) represents a relative elevation corresponding to the position point Q1 of the road 301a, and P (Q2) represents a relative elevation corresponding to the position point Q2 of the road 302 a. The third relative elevation up-down information is that the position point U2 of the road 302a and the position point U3 of the road 303a intersect on a two-dimensional plane, but the position point U2 and the position point U3 have an up-down relationship, as illustrated in fig. 4, P (U2) > P (U3), that is, the relative elevation corresponding to each of the two is different, where P (U2) and P (U3) are unknown, P (U2) represents the relative elevation corresponding to the position point U2 of the road 302a, and P (U3) represents the relative elevation corresponding to the position point U3 of the road 303 a.

Therefore, the service server acquires the position point N1, the position point N3, the position point Q1, the position point Q2, the position point U2, and the position point U3, and determines the start point corresponding to each road, the end point corresponding to each road, and the capping point corresponding to each road as at least two target position points 30c.

The embodiment of the application does not limit the number of roads to which the position points which are mutually gland points belong, can be determined according to actual application scenes, for example, a spiral mountain road or a spiral three-dimensional bridge can be provided with gland areas, and under the scenes, the gland points can be provided on the spiral mountain road; for example, there is a capping area (such as the road 301a and the road 302a in fig. 4) between the upper road and the lower road, and in this scenario, there may be capping points on both roads; in urban interchange roads, it may even occur that there are capping points for three or more roads.

The embodiment of the application firstly uses the position point Q1 to exemplify the target position point W _o The first road is exemplified by the road 301a to which the location point Q1 belongs; in the at least two target location points 30c, the service server acquires the target location points which belong to the road 301a and are adjacent to the location point Q1, namely the location point N1 and the location point R1 in fig. 4, so the location point N1 and the location point R1 are respectively taken as adjacent target location points of the location point Q1; further, the service server determines that the location point N1 and the location point Q1 have adjacent association relation, which can also be understood that the target location point pair (N1, Q1) has adjacent relation A linkage relationship; the determined position point R1 and the position point Q1 have adjacent association relation, and the target position point pair (Q1, R1) can be understood to have adjacent association relation; because the position point Q1 and the position point Q2 are in the same gland area, the service server determines that the position point Q1 and the position point Q2 have gland association relationship (equivalent to up-down association relationship), and can also understand that the target position point pair (Q1, Q2) has up-down association relationship; since the road 301a does not have a road adjacency relationship at the position point Q1, the service server can determine the adjacent association relationship between the position point N1 and the position point Q1, the adjacent association relationship between the position point R1 and the position point Q1, and the up-down association relationship between the position point Q1 and the position point Q2 as the position association relationship for the position point Q1.

It can be understood that the determining process of the position association relationship corresponding to the position point Q2, the position point N1, the position point N3, the position point U2 and the position point U3 is consistent with the determining process of the position association relationship corresponding to the position point Q1, so that details of the determining process of the position association relationship corresponding to the position point Q1 are not repeated, please refer to the description of the determining process of the position association relationship corresponding to the position point Q1.

The embodiment of the application uses the position point X3 to exemplify the target position point W _o The first road is exemplified by the road 303a to which the location point X3 belongs; of the at least two target location points 30c, the traffic server acquires a target location point that belongs to the road 303a and that is adjacent to the location point X3, that is, the location point N3 in fig. 4, so the location point N3 is taken as an adjacent target location point of the location point X3; further, the service server determines that the position point X3 and the position point N3 have adjacent association relation, and can also understand that the target position point pair (X3, N3) has adjacent association relation; since the road 303a does not have a road adjacency relationship nor a road capping relationship at the position point X3, the service server can determine the adjacent association relationship between the position point X3 and the position point N3 as the position association relationship for the position point X3.

It can be understood that the determining process of the position association relationship corresponding to the position point L1, the position point T2, the position point R1, the position point Y3, and the position point Z4 is consistent with the determining process of the position association relationship corresponding to the position point X3, so that details of the determining process of the position association relationship corresponding to the position point X3 are not repeated, please refer to the description of the determining process of the position association relationship corresponding to the position point X3.

As shown in fig. 4, there is target adjacent information for the road in the navigation data, that is, the position point V2 of the road 302a is adjacent to the position point V4 of the road 304a, and the two have no upper and lower relationship, such as P (V2) =p (V4) in fig. 4, that is, the relative elevations corresponding to the two are the same, where P (V2) and P (V4) are unknown. The letter "P" in the present application indicates a relative elevation, and therefore, explanation and description thereof will not be repeated.

The embodiment of the application uses the position point V4 to exemplify the target position point W _o The first road is exemplified by the road 304a to which the location point V4 belongs; in the at least two target location points 30c, the service server acquires a target location point that belongs to the road 304a and is adjacent to the location point V4, that is, the location point Z4 in fig. 4, so the location point Z4 is taken as an adjacent target location point of the location point V4; further, the service server determines that the position point V4 and the position point Z4 have an adjacent association relationship, and can also understand that the target position point pair (V4, Z4) has an adjacent association relationship; since the road 304a has a road adjacent relationship between the position point V4 and the road 302a (equivalent to the second road), the position point V2 is determined as the second target position point corresponding to the position point V4, so the service server may determine that the position point V2 has an adjacent relationship with the position point V4, and may also understand that the target position point pair (V2, V4) has an adjacent relationship; since the road 304a does not have a road capping relationship at the position point V4, the service server can determine the adjacent association relationship between the position point V2 and the position point V4 and the adjacent association relationship between the position point V4 and the position point Z4 as the position association relationship for the position point V4.

It can be understood that, for the determining process of the position association relationship of the position point V2, the determining process of the position association relationship corresponding to the position point V4 is consistent, so that the embodiment of the application will not be described in detail, please refer to the description of the determining process of the position association relationship corresponding to the position point V4.

Further, the service server determines the position association relationship corresponding to each target position point as a position association relationship 30f between at least two target position points, such as a target position point pair (L1, N1), a target position point pair (N1, Q1), a target position point pair (Q1, R1), a target position point pair (T2, Q2), a target position point pair (Q2, U2), a target position point pair (U2, V2), a target position point pair (X3, N3), a target position point pair (N3, U3), a target position point pair (U3, Y3), a target position point pair (V4, Z4) each having an upper and lower association relationship, a target position point pair (Q1, Q2), a target position point pair (U2, U3), a target position point pair (N1, N3), and a target position point pair (V2, V4) having an adjacent association relationship in fig. 4.

Step S102, generating a set of relative elevation constraint conditions corresponding to at least two target position points according to the position association relation between the at least two target position points; the relative elevation constraint condition set is used for indicating conditions to be met by the relative elevations corresponding to the at least two target position points respectively.

Specifically, according to the position association relationship between at least two target position points, obtaining A target position point pairs respectively having the position association relationship; a is a positive integer, and A target position point pairs comprise target position point pairs B _c The method comprises the steps of carrying out a first treatment on the surface of the c is a positive integer and c is less than or equal to A; according to the target position point pair B _c The position association relationship generates a target position point pair B _c Is a relative elevation constraint of (2); and determining the corresponding relative elevation constraint conditions of the A target position points as a set of the corresponding relative elevation constraint conditions of at least two target position points.

Wherein, according to the target position point pair B _c The position association relationship generates a target position point pair B _c The specific process of the relative elevation constraint of (c) may include: if the target position point is B _c The position association relationship is adjacent association relationship, and B is based on the target position point pair _c Two-dimensional position information and target gradient corresponding to two target position points respectively, and generating a target position point pair B _c Is a relative elevation constraint of (2); if the target isPoint set B _c The position association relationship is up-down association relationship, and B is based on the target position point pair _c Relative elevation up-down information of two target position points in the model, and target height difference, and generating a target position point pair B _c Is a relative elevation constraint of (2); if the target position point is B _c If the position association relationship is adjacent association relationship, generating a target position point pair B according to the target adjacent information _c Is a relative elevation constraint of (2).

Wherein, according to the target position point pair B _c Two-dimensional position information and target gradient corresponding to two target position points respectively, and generating a target position point pair B _c The specific process of the relative elevation constraint of (c) may include: according to the target position point pair B _c Two-dimensional position information corresponding to two target position points in the map, and determining a target position point pair B _c Two-dimensional planar distance D between two target position points in (2) _c The method comprises the steps of carrying out a first treatment on the surface of the Generating a square value of the tangent value of the target gradient for the two-dimensional plane distance D _c The square value of the square value and the square value of the tangent value are multiplied to obtain a constraint value E _c The method comprises the steps of carrying out a first treatment on the surface of the Pairing the target position points B _c The square value of the height difference between the corresponding relative elevations of the two target position points is smaller than the constraint value E _c Is determined to be for the target position point pair B _c Is a relative elevation constraint of (2).

Wherein, according to the target position point pair B _c Relative elevation up-down information of two target position points in the model, and target height difference, and generating a target position point pair B _c The specific process of the relative elevation constraint of (c) may include: according to the target position point pair B _c The relative elevation up-down information of two target position points in the model (B) is used for constructing a target position point pair (B) _c Forward height difference F of two target position points in (a) _c The method comprises the steps of carrying out a first treatment on the surface of the Will forward difference in height F _c Greater than the target altitude difference, determined as being for the target position point pair B _c Is a relative elevation constraint of (2).

It is understood that a target location point pair has only one location association relationship, and thus, the service server may generate a relative elevation constraint condition based on a target location point pair and the location association relationship that it has. The target position point pair with the upper and lower association relationship (also called gland association relationship) needs to satisfy the constraint condition of the gland region, and the condition can be expressed by a formula (1).

P(α)-P(β)>h (1)

The α and β in the formula (1) represent two target position points with an upper-lower association relationship, and the navigation data indicate that the target position point α is located above the target position point β, and the letter "P" in the present application represents a relative elevation, so that explanation and redundant description are omitted. h represents the minimum height of the gland area, namely the target height difference, which can be set according to the actual application scene, and the minimum height is found to be more reasonable to take 4 meters in the test, and too high h can lead to no solution of the optimization problem in the step S104, and too low h can lead to overlapping of two roads of the gland area, so that the visual effect is poor.

As described in connection with fig. 4, the known target position point pair (Q1, Q2), the target position point pair (U2, U3), and the target position point pair (N1, N3) all have an up-down association relationship (also referred to as a gland association relationship), and the target position point Q1 is located above the target position point Q2, the target position point U2 is located above the target position point U3, and the target position point N1 is located above the target position point N3, so the service server can generate three relative elevation constraint conditions in connection with the formula (1), as shown in the formula (2).

P(Q1)-P(Q2)>h

P(U2)-P(U3)>h (2)

P(N1)-P(N3)>h

Wherein, the target position point pair with the adjacency association relation is required to satisfy the adjacency height continuous constraint condition, and the condition can be expressed by a formula (3).

P(ε)＝P(δ) (3)

Wherein epsilon and delta in the formula (3) represent two target position points with adjacent association relation, and for two adjacent roads, the two adjacent roads need to be continuous at the adjacent points, otherwise, the situation of abrupt change of the height of the adjacent points, namely one high and one low, occurs, and the visual effect is influenced.

As described in connection with FIG. 4, the known target location point pairs (V2, V4) have an adjacent relationship, so that the service server can generate a relative elevation constraint in connection with equation (3), as shown in equation (4).

P(V2)＝P(V4)(4)

The target position point pair with the adjacent association relation is required to meet the gradient constraint condition, and the condition can be expressed by a formula (5).

(P(φ)-P(γ)) ² <s ² d ² (φ，γ) (5)

Wherein phi and gamma in the formula (5) represent two target position points with adjacent association, s represents the tangent value of the maximum gradient (namely the target gradient), which can be set according to the actual application scene, and the maximum gradient is found to take 1 angle reasonably in the test, and d ² The term (Φγ) represents the target position point Φ and the distance of the target position point γ on the plane. Since the navigation data provides longitude and latitude coordinates, namely two-dimensional position information, the two-dimensional position information between two target position points can be calculated to obtain the plane distance, and d is the distance ² The (φγ) is a known amount. If the road shape is a curve, the planar distance is the arc length.

As described in connection with fig. 4, the known target location point pair (L1, N1), the target location point pair (N1, Q1), the target location point pair (Q1, R1), the target location point pair (T2, Q2), the target location point pair (Q2, U2), the target location point pair (U2, V2), the target location point pair (X3, N3), the target location point pair (N3, U3), the target location point pair (U3, Y3), and the target location point pair (V4, Z4) all have adjacent association relationships, so the service server can generate ten relative elevation constraint conditions in connection with the formula (5), as shown in the formula (6).

(P(L1)-P(N1)) ² <s ² d ² (L1，N1)

(P(N1)-P(Q1)) ² <s ² d ² (N1，Q1)

(P(Q1)-P(R1)) ² <s ² d ² (Q1，R1)

(P(T2)-P(Q2)) ² <s ² d ² (T2，Q2)

(P(Q2)-P(U2)) ² <s ² d ² (Q2，U2)

(P(U2)-P(V2)) ² <s ² d ² (U2，V2)

(P(X3)-P(N3)) ² <s ² d ² (X3，N3)

(P(N3)-P(U3)) ² <s ² d ² (N3，U3)

(P(U3)-P(Y3)) ² <s ² d ² (U3，Y3)

(P(V4)-P(Z4)) ² <s ² d ² (V4，Z4) (6)

Finally, the service server determines the relative elevation constraint conditions respectively included in the formula (2), the formula (4) and the formula (6) as a set of relative elevation constraint conditions corresponding to at least two target position points 30c in fig. 4.

Step S103, initial relative elevations corresponding to at least two target position points are obtained, and initial distribution characteristic information of the at least two initial relative elevations is determined.

Specifically, a relatively high Cheng Youhua device is obtained, and at least two initial relative elevations are input to the relatively high Cheng Youhua device; the relative elevation optimizer includes a distribution feature function; and determining initial distribution characteristic information of at least two initial relative elevations through the distribution characteristic function.

Wherein, the specific process of determining the initial distribution characteristic information of at least two initial relative elevations may include: obtaining square values corresponding to at least two initial relative elevations respectively through a distribution characteristic function; summing the square values corresponding to the at least two initial relative elevations respectively to obtain a dispersion degree value of the at least two initial relative elevations Cheng Duiying; the dispersion degree value of at least two initial relative heights Cheng Duiying is determined as initial distribution characteristic information of at least two initial relative elevations.

The service server obtains the initial relative elevation corresponding to the at least two target location points, and the embodiment of the application does not limit the source of obtaining the at least two initial relative elevations, and the initial relative elevations can be randomly generated or have fixed values, for example, all of which are 0 as illustrated in fig. 2. Typically, at least two initial relative elevations do not satisfy a relative elevation constraint in the set of relative elevation constraints.

In the practical test, it is found that the capping region constraint condition, the adjacent height continuous constraint condition and the gradient constraint condition mentioned in step S102 are mutually coupled, that is, when the capping region height is found to be unable to meet the requirement, the gradient constraint condition or the adjacent point height continuous condition may be destroyed when the height of the corresponding target position point is modified; when the gradient is found to be unsatisfied with the requirement, the height constraint condition of the gland area or the continuous condition of the adjacent point height can be damaged when the height of the corresponding target position point is modified; when the adjacent point height is found to be discontinuous, the capping area height condition or gradient constraint condition may be destroyed when the height of the corresponding target position point is modified.

In order to solve the problem, the application establishes a unified mathematical model, comprehensively considers three types of constraints, namely, converting the problem of generating relative elevation into the problem of mathematical optimization. In the mathematical model, the heights of the target position points in the road need to satisfy the three types of constraints (i.e., the set of relative elevation constraints in step S102), while it is desirable that the sum of squares of the heights corresponding to at least two target position points is minimum; because the sum of the squares of at least two elevations (i.e., relative elevations) approximates the variance of at least two relative elevations, i.e., the degree of dispersion of at least two relative elevations. Thus, the service server may render a high quality visual effect when the relatively high Cheng Jin of the at least two target location points, respectively, may be concentrated.

The service server obtains the relative height Cheng Youhua device and inputs at least two initial relative heights into the relative height Cheng Youhua device, wherein the relative height optimizer includes a distribution characteristic function, which can be shown in formula (7).

Wherein ζ in equation (7) represents the dispersion degree value of at least two relative elevations, i.e. the distribution characteristic information, μ _λ Represents the lambda target position point, and the lambda range is [1, theta ]]θ is the total number of at least two target location points.

By distributing the feature function, the business server can determine initial distribution feature information for at least two initial relative elevations.

Step S104, based on the initial distribution characteristic information and the relative elevation constraint condition set, respectively adjusting at least two initial relative elevations to obtain the relative elevations respectively corresponding to at least two target position points.

Specifically, the set of relative elevation constraints is input to a relatively tall Cheng Youhua machine; in the relative elevation optimizer, respectively adjusting at least two initial relative elevations based on the initial distribution characteristic information to obtain relative elevations to be optimized, which correspond to at least two target position points respectively; at least two relative elevations to be optimized meet the relative elevation constraint conditions in the relative elevation constraint condition set; inputting at least two relative elevations to be optimized into a distribution characteristic function, and determining distribution characteristic information to be optimized of the at least two relative elevations to be optimized through the distribution characteristic function; respectively adjusting at least two relative elevations to be optimized based on the distribution characteristic information to be optimized to obtain the relative elevations corresponding to at least two target position points respectively; the dispersion degree value corresponding to the distribution characteristic information of at least two relative elevations is smaller than the dispersion degree value corresponding to the distribution characteristic information to be optimized, and the at least two relative elevations meet the relative elevation constraint condition set.

The specific process of respectively adjusting the at least two relative elevations to be optimized based on the distribution characteristic information to be optimized to obtain the relative elevations corresponding to the at least two target position points respectively may include: respectively adjusting at least two relative elevations to be optimized based on the distribution characteristic information to be optimized to obtain candidate relative elevations corresponding to at least two target position points respectively; inputting at least two candidate relative elevations into a distribution characteristic function, and determining candidate distribution characteristic information of the at least two candidate relative elevations through the distribution characteristic function; and determining the relative elevation corresponding to at least two target position points respectively according to the distribution characteristic information to be optimized and the candidate distribution characteristic information.

The specific process of determining the relative elevation corresponding to each of the at least two target position points according to the distribution characteristic information to be optimized and the candidate distribution characteristic information may include: determining a dispersion degree value corresponding to the distribution characteristic information to be optimized and a dispersion distance between the dispersion degree values corresponding to the candidate distribution characteristic information; if the dispersion distance is smaller than the dispersion distance threshold value, acquiring the relative elevation corresponding to at least two target position points from the relative elevation set; the relative elevation set comprises at least two relative elevations to be optimized and at least two candidate relative elevations; and if the dispersion distance is equal to or greater than the dispersion distance threshold, respectively adjusting at least two candidate relative elevations based on the candidate distribution characteristic information to obtain the relative elevations respectively corresponding to at least two target position points.

Mathematical optimization there are many well-established mathematical tools that can be used, such as interior point methods in convex optimization, with which solutions can be efficiently performed. The embodiment of the application adopts the optimization idea to generate a relatively high Cheng Youhua device, is not limited to an optimization mathematical tool, and can be any optimization tool.

The service server inputs the set of relative elevation constraints to the relative height Cheng Youhua device, and it can be understood that, in a general case, at least two initial relative elevations do not meet the set of relative elevation constraints, so in the relative elevation optimizer, the service server adjusts the at least two initial relative elevations based on the initial distribution feature information, the adjustment policy may be to approach the set of relative elevation constraints, that is, the adjusted at least two initial relative elevations increasingly meet three types of relative elevation constraints, and finally, the service server may obtain at least two relative elevations to be optimized corresponding to at least two target position points, where the at least two relative elevations to be optimized meet the relative elevation constraints in the set of relative elevation constraints.

Because it is desirable to generate a stereoscopic road with good rendering effect, when the relative heights corresponding to at least two target position points respectively meet the three types of constraint conditions, the sum of squares of at least two relative heights is simultaneously desired to be minimum, that is, the dispersion degree value is minimum. In this case, the service server further adjusts at least two relative elevations to be optimized, that is, the at least two relative elevations to be optimized are both input into the distribution feature function, and the distribution feature information to be optimized of the at least two relative elevations to be optimized can be determined through the distribution feature function; based on the distribution characteristic information to be optimized, the service server respectively adjusts at least two relative elevations to be optimized to obtain candidate relative elevations corresponding to at least two target position points respectively; it will be appreciated that at least two candidate relative elevations each satisfy the three types of relative elevation constraints described above.

The service server inputs at least two candidate relative elevations into a distribution characteristic function, and candidate distribution characteristic information of the at least two candidate relative elevations can be determined through the distribution characteristic function; the business server determines the dispersion degree value corresponding to the distribution characteristic information to be optimized and the dispersion distance between the dispersion degree values corresponding to the candidate distribution characteristic information; if the dispersion distance is smaller than the dispersion distance threshold, the service server may determine that the candidate distribution feature information and the distribution feature information to be optimized are both optimal solutions of the distribution feature function, that is, the dispersion degree value is the minimum value, and at this time, at least two relative elevations to be optimized or at least two candidate relative elevations may be determined as relative elevations corresponding to at least two target position points respectively.

If the dispersion distance is equal to or greater than the dispersion distance threshold, the service server may determine that the candidate distribution feature information and the to-be-optimized distribution feature information are not optimal solutions of the distribution feature function, that is, the dispersion degree value is not the minimum value, and at this time, based on the candidate distribution feature information, the service server adjusts at least two candidate relative elevations respectively until the dispersion distance of two adjacent dispersion degree values is less than the dispersion distance threshold, and determines the relative elevations corresponding to two adjacent dispersion degree values, of which the dispersion distance is less than the dispersion distance threshold, as the relative elevations corresponding to at least two target position points respectively.

Optionally, if the adjustment times for the at least two candidate relative elevations are equal to the adjustment times threshold, the dispersion distance of the two adjacent dispersion degree values is still equal to or greater than the dispersion distance threshold, and the service server determines the at least two candidate relative elevations generated by the last adjustment as at least two sharing processes; optionally, if the adjustment times for at least two candidate relative elevations are equal to the adjustment times threshold, the dispersion distance of the two adjacent dispersion degree values is still equal to or greater than the dispersion distance threshold, the service server obtains the minimum dispersion distance, and determines the candidate relative elevation corresponding to the minimum dispersion distance as the relative elevation corresponding to at least the target position point respectively.

Referring to fig. 5, fig. 5 is a second flowchart of a data processing method according to an embodiment of the present application. The method may be performed by a service server (e.g., the service server 100 shown in fig. 1 and described above), by a terminal device (e.g., the terminal device 200a shown in fig. 1 and described above), or by both the service server and the terminal device. For easy understanding, the embodiment of the present application is described as an example in which the method is executed by a service server. As shown in fig. 5, the method may include at least the following steps.

Step S201, at least two target position points of the road are obtained from the two-dimensional road network, and the position association relationship between the at least two target position points is determined.

In the specific implementation process of step S201, please refer to step S101 in the embodiment corresponding to fig. 3, and details are not described here.

Step S202, generating a set of relative elevation constraint conditions corresponding to at least two target position points according to the position association relation between the at least two target position points; the relative elevation constraint condition set is used for indicating conditions to be met by the relative elevations corresponding to the at least two target position points respectively.

In electronic navigation (e.g. lane-level navigation), the road is three-dimensional, i.e. with elevation information, for aesthetic rendering effects and to restore the real world as much as possible. The elevation can be divided into absolute elevation and relative elevation, and absolute elevation Cheng Yongyu cannot be directly rendered in lane-level navigation, because there are mainly two points: 1. the absolute elevation of the road is national data, so the absolute elevation cannot be directly used for navigation lane-level navigation; 2. some urban terrain is very rough, such as mountain cities and the like. If the absolute elevation is directly used, the height of the lowest point in the image needs to be calculated in real time in lane-level navigation, and then the height of the camera is adjusted to obtain a better rendering effect, but such real-time calculation can increase the burden of a central processing unit (central processing unit, abbreviated as CPU), and can be blocked very in some low-end devices, so that experience is affected.

Thus, a relative elevation, i.e. a hypothetical elevation, is often employed in lane-level navigation. The relative elevation meets the following four requirements:

(1) the height of the real road is restored as much as possible, but the height cannot be completely consistent;

(2) although the road is not completely consistent with a real road, the upper and lower relationship of the road, namely the capping relationship, needs to be consistent with the real road, namely for two roads with capping relationship, who is above and who is below the road cannot be different from reality;

(3) the gradient of the road is smooth enough, so that the lane-level navigation is rendered with a better visual effect. In some cases where the grade of a real road is relatively high, the resulting relative elevation also needs to be sufficiently smooth;

(4) the height of the anterior and posterior roads at the junction needs to be continuous and smooth enough near the junction.

Thus, there are three types of constraints in the relative elevation unique to the target location point generated by the service server, namely, the capping zone altitude constraint, the road grade constraint, and the altitude continuity condition of the road at the adjacency point. As will be described below.

1. The capping region is highly constrained. The navigation data corresponding to the two-dimensional road network can provide the height relation of the two roads in the capping area, but does not give the height difference of the two roads in the capping area. The difference in height between the two roads in the capping area cannot be too small when generating the relative elevation, otherwise they look superimposed, and the visual effect is poor, so that it is necessary to control the minimum difference in height in the capping area.

2. Road grade constraints. The generated relative elevation needs to satisfy the condition that the road gradient change is gentle, and no steep rise or fall of the road gradient can occur, so that it is necessary to control the maximum value of the road gradient.

3. Highly continuous conditions at the adjacent points. For the front and rear roads, the needs of the two roads at the adjacent points should be continuous, otherwise, the situation of high abrupt change at the adjacent points, namely one high and one low, can occur, and the visual effect is influenced.

For a specific generation process of the set of relative altitude constraints, please refer to the description of step S102 in the embodiment corresponding to fig. 3.

Step S203, obtaining initial relative elevations corresponding to at least two target position points respectively, and determining initial distribution characteristic information of the at least two initial relative elevations;

step S204, based on the initial distribution characteristic information and the relative elevation constraint condition set, respectively adjusting at least two initial relative elevations to obtain the relative elevations respectively corresponding to at least two target position points.

In the specific implementation process of step S203 to step S204, please refer to step S103 to step S104 in the embodiment corresponding to fig. 3, which is not described herein.

Step S205, obtaining the position points except at least two target position points in the road from the navigation data corresponding to the two-dimensional road network as the intermediate position points.

Specifically, it can be understood that the navigation data includes other position points besides the start point of the road, the end point of the road and the position point of the capping area, and the embodiment of the application uses the navigation data as the intermediate position point, please refer to fig. 6, and fig. 6 is a schematic diagram of a data processing scenario provided by the embodiment of the application. As shown in fig. 6, the two-dimensional road network 50a is different from the two-dimensional road network 30b in fig. 4 in that the intermediate position point 501a is added to the two-dimensional road network 50a, and in fig. 3, the intermediate position point is hidden in the two-dimensional road network 30b for convenience of description of the target position point. It will be appreciated that fig. 6 is an example of 1 intermediate position point, and in practical application, one or more intermediate position points may be included in the navigation data corresponding to the two-dimensional road network.

In step S206, a fifth target position point and a sixth target position point, which have adjacent association relations with the intermediate position point, respectively, are obtained from the at least two target position points.

Specifically, in conjunction with fig. 6, the service server acquires, from at least two target location points, a location point having an adjacent association relationship with the intermediate location point 501a, such as the location point Q2 (which may be equivalent to the fifth target location point) and the location point U2 (which may be equivalent to the sixth target location point) in fig. 6.

In step S207, a relative elevation corresponding to the intermediate position point is determined according to the fifth target position point and the sixth target position point.

Specifically, if the relative elevation corresponding to the fifth target position point is greater than the relative elevation corresponding to the sixth target position point, determining a relative elevation difference between the relative elevation corresponding to the fifth target position point and the relative elevation corresponding to the sixth target position point; determining a first two-dimensional plane distance between the sixth target position point and the intermediate position point, and determining a second two-dimensional plane distance between the fifth target position point and the sixth position point; and determining a distance ratio between the first two-dimensional plane distance and the second two-dimensional plane distance, and carrying out weighted summation on the relative elevation difference and the relative elevation corresponding to the sixth target position point based on the distance ratio to obtain the relative elevation corresponding to the intermediate position point.

Specifically, at this time, the service server has generated the relative elevation corresponding to at least two target position points, so the magnitude relation between the relative elevation corresponding to the fifth target position point and the relative elevation corresponding to the sixth target position point may be determined, and in the case where the relative elevation corresponding to the fifth target position point is greater than the relative elevation corresponding to the sixth target position point, the service server may determine the relative elevation difference between the relative elevation corresponding to the fifth target position point and the relative elevation corresponding to the sixth target position point, as shown in fig. 6, P '=p (Q2) -P (U2), where P' represents the relative elevation difference. In addition, the location points all carry two-dimensional location information, so the service server may determine a first two-dimensional plane distance between the sixth target location point (e.g., location point U2 in fig. 6) and the intermediate location point (e.g., location point Q2 in fig. 6), where d (U2, 501 a) represents the first two-dimensional plane distance as shown in fig. 6; further, the service server may determine a second two-dimensional plane distance between the fifth target location point and the sixth location point, as shown in fig. 6, d (Q2, U2) represents the second two-dimensional plane distance; and determining a distance ratio d 'between the first two-dimensional plane distance and the second two-dimensional plane distance, and carrying out weighted summation on the relative elevation difference and the relative elevation corresponding to the sixth target position point based on the distance ratio d' to obtain the relative elevation corresponding to the intermediate position point.

In step S208, the relative elevation corresponding to each of the at least two target position points and the relative elevation corresponding to each of the intermediate position points are determined as the relative elevation corresponding to the road.

Specifically, the relative elevation corresponding to the road can be used for rendering lane-level navigation, a three-dimensional road effect is generated, and then a high-precision navigation map can be generated.

Fig. 7 is a schematic flow chart of a data processing method according to an embodiment of the present application. As shown in fig. 7, in step S301, a service server obtains at least two target location points; for this specific procedure, please refer to the description of step S101; step S302, constructing a height constraint condition according to the height relation of the road in the capping area; the height constraint condition is a relative height constraint condition corresponding to two target position points with an upper-lower association relationship, please refer to the description of the formula (1); step S303, constructing a high continuous condition of two roads at an adjacent point according to the road topology relation; the height constraint condition is a relative height constraint condition corresponding to two target position points with adjacent association relation, please refer to the description of the above formula (3); step S304, constructing gradient constraint conditions between any two adjacent target position points on the road; the gradient constraint condition is a relative elevation constraint condition corresponding to two target position points with adjacent association relation, please refer to the description of the above formula (5); step S305, solving the optimization problem to obtain the relative elevation corresponding to each of the at least two target position points, wherein the process corresponds to the above step S104, and therefore, details are not repeated here; step S306, determining the relative elevation corresponding to the intermediate position point; step S307, determining the relative elevation corresponding to the road.

The embodiment of the application provides a method for generating the relative elevation of a road according to two-dimensional road network information, which converts the problem of generating the relative elevation into a mathematical optimization problem and can efficiently and high-quality generate the relative elevation data of the road for lane-level navigation by using a mature optimization solving algorithm. In addition, the method needs less original data, and does not need to collect absolute elevation of a road by using precise equipment, so that the information collection cost can be greatly reduced.

Further, referring to fig. 8, fig. 8 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application. The data processing device 1 may be adapted to perform the respective steps of the method provided by the embodiments of the application. As shown in fig. 8, the data processing apparatus 1 may include: a first determination module 11, a first generation module 12, a second determination module 13 and a second generation module 14.

The first determining module 11 is configured to obtain at least two target location points of a road from a two-dimensional road network, and determine a location association relationship between the at least two target location points;

the first generation module 12 is configured to generate a set of relative elevation constraint conditions corresponding to at least two target location points according to a location association relationship between the at least two target location points; the relative elevation constraint condition set is used for indicating conditions which are required to be met by the relative elevations corresponding to the at least two target position points respectively;

The second determining module 13 is configured to obtain initial relative elevations corresponding to at least two target location points, and determine initial distribution feature information of the at least two initial relative elevations;

the second generating module 14 is configured to adjust at least two initial relative elevations respectively based on the initial distribution feature information and the set of relative elevation constraint conditions, so as to obtain relative elevations corresponding to at least two target location points respectively.

The specific functional implementation manner of the first determining module 11, the first generating module 12, the second determining module 13, and the second generating module 14 may refer to step S101-step S104 in the corresponding embodiment of fig. 3, which is not described herein.

Referring again to fig. 8, the first determining module 11 may include: a first acquisition unit 111, a first determination unit 112, and a second determination unit 113.

A first obtaining unit 111, configured to obtain a road from navigation data corresponding to a two-dimensional road network, and obtain a starting point corresponding to the road and an ending point corresponding to the road;

a first determining unit 112, configured to determine a start point and an end point as at least two target location points if no relative elevation description information for the road exists in the navigation data;

A second determining unit 113, configured to obtain, if the relative elevation description information for the road exists in the navigation data, a capping point indicated by the relative elevation description information, and determine the capping point, the starting point, and the ending point indicated by the relative elevation description information as at least two target location points; and the capping point indicated by the relative elevation description information is used for indicating that the road relationship corresponding to the road comprises a road capping relationship.

The specific functional implementation manner of the first obtaining unit 111, the first determining unit 112, and the second determining unit 113 may refer to step S101 in the corresponding embodiment of fig. 3, which is not described herein.

Referring again to FIG. 8, at least two target location points include target location point W _o O is a positive integer, and o is less than or equal to the total number of at least two target position points; the road includes a target position point W _o A first road to which the road belongs;

the first determining module 11 may include: a second acquisition unit 114, a third determination unit 115, and a fourth determination unit 116.

A second obtaining unit 114 for obtaining a target position point W belonging to the first road among the at least two target position points _o Adjacent target position points as adjacent target position points;

A third determining unit 115 for determining adjacent target position points and target position points W _o The two have adjacent association relations;

a fourth determining unit 116 for determining the target position point W according to the first road _o Road relation of adjacent target position point and target position point W _o Adjacent association relation between the target position points W is determined _o Is a positional association relation of (a) and (b).

The specific functional implementation manner of the second obtaining unit 114, the third determining unit 115, and the fourth determining unit 116 may refer to step S101 in the corresponding embodiment of fig. 3, and will not be described herein.

Referring back to fig. 8, the fourth determining unit 116 may include: a first determination subunit 1161, a first acquisition subunit 1162, a second determination subunit 1163, and a third determination subunit 1164.

A first determining subunit 1161 for determining if the first road is at the target location point W _o Without road relation, adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a position association relation of the plurality of images;

a first obtaining subunit 1162 for determining that the first road is at the target location point W _o The road relation of (1) is a road capping relation, and is obtained from at least two target position points A first target location point; the relative elevation corresponding to the first target position point is equal to the target position point W _o The corresponding relative elevation has an elevation difference, and the two-dimensional position information corresponding to the first target position point is equal to the target position point W _o The corresponding two-dimensional position information is the same;

a second determining subunit 1163 for determining the first target location point and the target location point W _o The two have an up-down association relation;

a third determining subunit 1164 for determining the first target position point and the target position point W _o Upper and lower association relation between adjacent target position point and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

The specific functional implementation manner of the first determining subunit 1161, the first obtaining subunit 1162, the second determining subunit 1163, and the third determining subunit 1164 may refer to step S101 in the corresponding embodiment of fig. 3, and will not be described herein.

Referring back to fig. 8, the fourth determining unit 116 may include: the second acquisition subunit 1165, the fourth determination subunit 1166, and the fifth determination subunit 1167.

A second obtaining subunit 1165 for determining if the first road is at the target location point W _o The road relation of the road is a road adjacent relation, and a second target position point belonging to a second road is obtained from at least two target position points; the relative elevation corresponding to the first target position point is equal to the target position point W _o No height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the first target position point and the target position point W _o The corresponding two-dimensional position information is the same; the second road belongs to the road;

a fourth determining subunit 1166 for determining a second target location point and a target location point W _o The adjacent incidence relation is formed between the two;

a fifth determining subunit 1167 for comparing the second target position point with the target position point W _o Adjacent association relation between adjacent target position points and target position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

The specific functional implementation manner of the second obtaining subunit 1165, the fourth determining subunit 1166, and the fifth determining subunit 1167 may refer to step S101 in the corresponding embodiment of fig. 3, which is not described herein.

Referring back to fig. 8, the fourth determining unit 116 may include: the third acquisition subunit 1168 and the sixth determination subunit 1169.

A third obtaining subunit 1168 for determining if the first road is at the target location point W _o The road relation of (1) comprises a road adjacency relation and a road capping relation, and a third target position point belonging to a third road is acquired from at least two target position points based on the road adjacency relation; the relative elevation corresponding to the third target position point is equal to the target position point W _o No height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the third target position point and the target position point W _o The corresponding two-dimensional position information is the same; the third road belongs to the road;

the third obtaining subunit 1168 is further configured to obtain a fourth target location point from at least two target location points based on the road capping relationship; the relative elevation corresponding to the fourth target position point is equal to the target position point W _o The corresponding relative elevation has a height difference, and the two-dimensional position information corresponding to the fourth target position point is equal to the target position point W _o The corresponding two-dimensional position information is the same;

a sixth determining subunit 1169 for determining a third target location point and a target location point W _o The adjacent incidence relation is formed between the two;

the sixth determining subunit 1169 is further configured to determine a fourth target location point and a target location point W _o The two have an up-down association relation;

a sixth determining subunit 1169 is further configured to determine a third target location point from the target location point W _o Adjacent incidence relation between the fourth target position point and the target position point W _o The upper and lower association relation between adjacent target position points and targetsTarget position point W _o The adjacent association relation between the two is determined to be specific to the target position point W _o Is a positional association relation of (a) and (b).

The specific functional implementation manner of the third obtaining subunit 1168 and the sixth determining subunit 1169 may refer to step S101 in the corresponding embodiment of fig. 3, which is not described herein.

Referring again to fig. 8, the first generating module 12 may include: a third acquisition unit 121, a condition generation unit 122, and a fifth determination unit 123.

A third obtaining unit 121, configured to obtain a target location point pairs having a location association relationship according to a location association relationship between at least two target location points; a is a positive integer, and A target position point pairs comprise target position point pairs B _c The method comprises the steps of carrying out a first treatment on the surface of the c is a positive integer and c is less than or equal to A;

a condition generating unit 122 for generating a target position point pair B _c The position association relationship generates a target position point pair B _c Is a relative elevation constraint of (2);

a fifth determining unit 123, configured to determine the relative elevation constraint conditions corresponding to the a target location points as a set of relative elevation constraint conditions corresponding to at least two target location points.

The specific functional implementation manner of the third obtaining unit 121, the condition generating unit 122, and the fifth determining unit 123 may refer to step S102 in the corresponding embodiment of fig. 3, and will not be described herein.

Referring back to fig. 8, the condition generating unit 122 may include: a first generation subunit 1221, a second generation subunit 1222, and a third generation subunit 1223.

A first generation subunit 1221 for generating a target position point pair B _c The position association relationship is adjacent association relationship, and B is based on the target position point pair _c Two-dimensional position information and target gradient corresponding to two target position points respectively, and generating a target position point pair B _c Is a relative elevation constraint of (2);

a second generation subunit 1222 has been provided,for if target position point pair B _c The position association relationship is up-down association relationship, and B is based on the target position point pair _c Relative elevation up-down information of two target position points in the model, and target height difference, and generating a target position point pair B _c Is a relative elevation constraint of (2);

a third generating subunit 1223 for generating a target position point pair B _c If the position association relationship is adjacent association relationship, generating a target position point pair B according to the target adjacent information _c Is a relative elevation constraint of (2).

The specific functional implementation manner of the first generating subunit 1221, the second generating subunit 1222, and the third generating subunit 1223 may refer to step S102 in the corresponding embodiment of fig. 3, which is not described herein.

Referring to fig. 8 again, the first generating subunit 1221 is specifically configured to, according to the target position point pair B _c Two-dimensional position information corresponding to two target position points in the map, and determining a target position point pair B _c Two-dimensional planar distance D between two target position points in (2) _c ；

The first generating subunit 1221 is further specifically configured to generate a square value of the tangent value of the target gradient, for the two-dimensional plane distance D _c The square value of the square value and the square value of the tangent value are multiplied to obtain a constraint value E _c ；

The first generating subunit 1221 is further specifically configured to pair B the target location point _c The square value of the height difference between the corresponding relative elevations of the two target position points is smaller than the constraint value E _c Is determined to be for the target position point pair B _c Is a relative elevation constraint of (2).

The specific functional implementation manner of the first generating subunit 1221 may refer to step S102 in the corresponding embodiment of fig. 3, which is not described herein.

Referring to fig. 8, the second generating subunit 1222 is specifically configured to generate a target position point pair B according to _c The relative elevation up-down information of two target position points in the model (B) is used for constructing a target position point pair (B) _c Forward height difference F of two target position points in (a) _c ；

A second generation subunit 1222 for further specifically generating a forward height difference F _c Greater than the target altitude difference, determined as being for the target position point pair B _c Is a relative elevation constraint of (2).

The specific functional implementation manner of the second generating subunit 1222 may refer to step S102 in the corresponding embodiment of fig. 3, which is not described herein.

Referring again to fig. 8, the second determining module 13 may include: a fourth acquisition unit 131 and a sixth determination unit 132.

A fourth acquiring unit 131 for acquiring a relatively high Cheng Youhua device, and inputting at least two initial relative elevations to the relatively high Cheng Youhua device; the relative elevation optimizer includes a distribution feature function;

a sixth determining unit 132 is configured to determine initial distribution characteristic information of at least two initial relative elevations by using the distribution characteristic function.

The specific functional implementation manner of the fourth obtaining unit 131 and the sixth determining unit 132 may refer to step S103 in the corresponding embodiment of fig. 3, which is not described herein.

Referring back to fig. 8, the sixth determining unit 132 may include: a fourth acquisition subunit 1321, a fourth generation subunit 1322, and a seventh determination subunit 1323.

A fourth obtaining subunit 1321, configured to obtain square values corresponding to at least two initial relative elevations respectively through a distribution feature function;

a fourth generating subunit 1322, configured to sum the square values corresponding to the at least two initial relative elevations respectively to obtain a dispersion degree value of the at least two initial relative heights Cheng Duiying;

the seventh determining subunit 1323 is configured to determine the dispersion degree value of the at least two initial relative heights Cheng Duiying as initial distribution feature information of the at least two initial relative heights.

The specific functional implementation manner of the fourth obtaining subunit 1321, the fourth generating subunit 1322, and the seventh determining subunit 1323 may refer to step S103 in the corresponding embodiment of fig. 3, which is not described herein.

Referring again to fig. 8, the second generating module 14 may include: a first input unit 141, a first adjustment unit 142, a second input unit 143, and a second adjustment unit 144.

A first input unit 141 for inputting a set of relative elevation constraints to a relative elevation Cheng Youhua machine;

the first adjusting unit 142 is configured to respectively adjust, in the relative elevation optimizer, at least two initial relative elevations based on the initial distribution feature information, to obtain relative elevations to be optimized corresponding to at least two target position points respectively; at least two relative elevations to be optimized meet the relative elevation constraint conditions in the relative elevation constraint condition set;

the second input unit 143 is configured to input at least two relative elevations to be optimized into a distribution feature function, and determine distribution feature information to be optimized of the at least two relative elevations to be optimized according to the distribution feature function;

the second adjusting unit 144 is configured to respectively adjust at least two relative elevations to be optimized based on the distribution characteristic information to be optimized, so as to obtain relative elevations corresponding to at least two target position points respectively; the dispersion degree value corresponding to the distribution characteristic information of at least two relative elevations is smaller than the dispersion degree value corresponding to the distribution characteristic information to be optimized, and the at least two relative elevations meet the relative elevation constraint condition set.

The specific functional implementation manner of the first input unit 141, the first adjusting unit 142, the second input unit 143, and the second adjusting unit 144 may refer to step S104 in the corresponding embodiment of fig. 3, and the detailed description thereof is omitted herein.

Referring to fig. 8 again, the second adjusting unit 144 may include: a fifth generation subunit 1441, an eighth determination subunit 1442, and a ninth determination subunit 1443.

A fifth generating subunit 1441, configured to respectively adjust at least two relative elevations to be optimized based on the distribution feature information to be optimized, so as to obtain candidate relative elevations corresponding to at least two target position points respectively;

an eighth determining subunit 1442, configured to input each of the at least two candidate relative elevations to a distribution feature function, and determine candidate distribution feature information of the at least two candidate relative elevations through the distribution feature function;

and a ninth determining subunit 1443, configured to determine, according to the to-be-optimized distribution feature information and the candidate distribution feature information, a relative elevation corresponding to each of the at least two target location points.

The specific functional implementation manner of the fifth generating subunit 1441, the eighth determining subunit 1442, and the ninth determining subunit 1443 may refer to step S104 in the corresponding embodiment of fig. 3, which is not described herein.

Referring to fig. 8 again, a ninth determining subunit 1443 is specifically configured to determine a dispersion distance between a dispersion degree value corresponding to the distribution characteristic information to be optimized and a dispersion degree value corresponding to the candidate distribution characteristic information;

The ninth determining subunit 1443 is further specifically configured to obtain, if the dispersion distance is smaller than the dispersion distance threshold, a relative elevation corresponding to each of the at least two target position points from the relative elevation set; the relative elevation set comprises at least two relative elevations to be optimized and at least two candidate relative elevations;

the ninth determining subunit 1443 is further specifically configured to, if the dispersion distance is equal to or greater than the dispersion distance threshold, respectively adjust at least two candidate relative elevations based on the candidate distribution feature information, to obtain the relative elevations corresponding to the at least two target position points respectively.

The specific functional implementation manner of the ninth determining subunit 1443 may refer to step S104 in the corresponding embodiment of fig. 3, which is not described herein.

Referring again to fig. 8, the data processing apparatus 1 may further include: the first acquisition module 15, the second acquisition module 16, the third determination module 17 and the fourth determination module 18.

A first obtaining module 15, configured to obtain, from navigation data corresponding to a two-dimensional road network, a location point in a road except for at least two target location points, as an intermediate location point;

a second obtaining module 16, configured to obtain, from at least two target location points, a fifth target location point and a sixth target location point that have adjacent association relationships with the intermediate location point respectively;

A third determining module 17, configured to determine a relative elevation corresponding to the intermediate position point according to the fifth target position point and the sixth target position point;

the fourth determining module 18 is configured to determine the relative elevation corresponding to the road as the relative elevation corresponding to the at least two target location points and the relative elevation corresponding to the intermediate location points.

The specific functional implementation manner of the first acquiring module 15, the second acquiring module 16, the third determining module 17 and the fourth determining module 18 may refer to step S201-step S204 in the corresponding embodiment of fig. 5, and will not be described herein.

Referring again to fig. 8, the third determining module 17 may include: the seventh determination subunit 171, the eighth determination subunit 172, and the ninth determination subunit 173.

A seventh determining subunit 171, configured to determine, if the relative elevation corresponding to the fifth target position point is greater than the relative elevation corresponding to the sixth target position point, a relative elevation difference between the relative elevation corresponding to the fifth target position point and the relative elevation corresponding to the sixth target position point;

an eighth determining subunit 172, configured to determine a first two-dimensional plane distance between the sixth target location point and the intermediate location point, and determine a second two-dimensional plane distance between the fifth target location point and the sixth location point;

A ninth determining subunit 173 is configured to determine a distance ratio between the first two-dimensional plane distance and the second two-dimensional plane distance, and weight and sum the relative elevation difference and the relative elevation corresponding to the sixth target position point based on the distance ratio, to obtain the relative elevation corresponding to the intermediate position point.

The specific functional implementation manner of the seventh determining subunit 171, the eighth determining subunit 172 and the ninth determining subunit 173 may refer to step S203 in the corresponding embodiment of fig. 5, which is not described herein.

Further, referring to fig. 9, fig. 9 is a schematic structural diagram of a computer device according to an embodiment of the present application. As shown in fig. 9, the computer device 1000 may include: at least one processor 1001, such as a CPU, at least one network interface 1004, a user interface 1003, a memory 1005, at least one communication bus 1002. Wherein the communication bus 1002 is used to enable connected communication between these components. In some embodiments, the user interface 1003 may include a Display (Display), a Keyboard (Keyboard), and the network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 1005 may also optionally be at least one storage device located remotely from the aforementioned processor 1001. As shown in fig. 9, the memory 1005, which is one type of computer storage medium, may include an operating system, a network communication module, a user interface module, and a device control application.

In the computer device 1000 shown in fig. 9, the network interface 1004 may provide network communication functions; while user interface 1003 is primarily used as an interface for providing input to a user; and the processor 1001 may be used to invoke a device control application stored in the memory 1005 to implement:

It should be understood that the computer device 1000 described in the embodiments of the present application may perform the description of the data processing method or apparatus in the foregoing embodiments, and will not be repeated herein. In addition, the description of the beneficial effects of the same method is omitted.

The embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the description of the data processing method or apparatus in each of the foregoing embodiments is implemented, and will not be repeated herein. In addition, the description of the beneficial effects of the same method is omitted.

The computer readable storage medium may be the data processing apparatus provided in any one of the foregoing embodiments or an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card) or the like, which are provided on the computer device. Further, the computer-readable storage medium may also include both internal storage units and external storage devices of the computer device. The computer-readable storage medium is used to store the computer program and other programs and data required by the computer device. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.

Embodiments of the present application also provide a computer program product comprising a computer program stored in a computer readable storage medium. The processor of the computer device reads the computer program from the computer readable storage medium, and the processor executes the computer program, so that the computer device may perform the description of the data processing method or apparatus in the foregoing embodiments, which is not described herein. In addition, the description of the beneficial effects of the same method is omitted.

The terms first, second and the like in the description and in the claims and drawings of embodiments of the application are used for distinguishing between different objects and not for describing a particular sequential order. Furthermore, the term "include" and any variations thereof is intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or modules but may, in the alternative, include other steps or modules not listed or inherent to such process, method, apparatus, article, or device.

Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

The foregoing disclosure is illustrative of the present application and is not to be construed as limiting the scope of the application, which is defined by the appended claims.

Claims

1. A method of data processing, comprising:

generating a set of relative elevation constraint conditions corresponding to the at least two target position points according to the position association relation between the at least two target position points; the relative elevation constraint condition set is used for indicating conditions which are required to be met by the relative elevations corresponding to the at least two target position points respectively;

Acquiring initial relative elevations corresponding to the at least two target position points respectively, and determining initial distribution characteristic information of the at least two initial relative elevations;

and respectively adjusting the at least two initial relative elevations based on the initial distribution characteristic information and the relative elevation constraint condition set to obtain the relative elevations respectively corresponding to the at least two target position points.

2. The method of claim 1, wherein the obtaining at least two target location points of the road from the two-dimensional road network comprises:

acquiring a road from navigation data corresponding to a two-dimensional road network, and acquiring a starting point corresponding to the road and a termination point corresponding to the road;

if the navigation data does not contain the relative elevation description information for the road, determining the starting point and the ending point as at least two target position points;

if the relative elevation description information aiming at the road exists in the navigation data, acquiring a capping point indicated by the relative elevation description information, and determining the capping point, the starting point and the ending point indicated by the relative elevation description information as at least two target position points; and the capping point indicated by the relative elevation description information is used for indicating that the road relationship corresponding to the road comprises a road capping relationship.

3. The method of claim 1, wherein the at least two target location points comprise a target location point W _o O is a positive integer, and o is less than or equal to the total number of the at least two target position points; the road includes the target position point W _o A first road to which the road belongs;

the determining the position association relationship between the at least two target position points includes:

in the at least two target location points, acquiring a target location point W belonging to the first road _o Adjacent target position points as adjacent target position points;

determining the adjacent target position point and the target position point W _o The two have adjacent association relations;

according to the first road at the target position point W _o Is arranged between the adjacent target position point and the target position point W _o Adjacent association relation between the target position point W and the target position point W is determined _o Is a positional association relation of (a) and (b).

4. A method according to claim 3, wherein said first road is at said target location point W _o Is arranged between the adjacent target position point and the target position point W _o Adjacent association relation between the target position point W and the target position point W is determined _o The position association relation of (a) includes:

if the first road is at the target position point W _o If the road relation is not present, the adjacent target position point is related to the target position point W _o The adjacent association relation between the target position points W is determined as the target position points W _o Is a position association relation of the plurality of images;

if the first road is at the target position point W _o The road relation of the road map is a road map relation, and a first target position point is obtained from the at least two target position points; the first target bitThe relative elevation corresponding to the placement point is equal to the target location point W _o A height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the first target position point and the target position point W _o The corresponding two-dimensional position information is the same;

determining the first target position point and the target position point W _o The two have an up-down association relation;

the first target position point and the target position point W _o Upper and lower association relation between the adjacent target position point and the target position point W _o The adjacent association relation between the target position points W is determined as the target position points W _o Is a positional association relation of (a) and (b).

5. A method according to claim 3, wherein said first road is at said target location point W _o Is arranged between the adjacent target position point and the target position point W _o Adjacent association relation between the target position point W and the target position point W is determined _o The position association relation of (a) includes:

if the first road is at the target position point W _o The road relation of the road is a road adjacent relation, and a second target position point belonging to a second road is obtained from the at least two target position points; the relative elevation corresponding to the first target position point is equal to the target position point W _o No height difference exists between the corresponding relative heights, and the two-dimensional position information corresponding to the first target position point and the target position point W _o The corresponding two-dimensional position information is the same; the second road belongs to the road;

determining the second target position point and the target position point W _o The adjacent incidence relation is formed between the two;

the second target position point is compared with the target position point W _o An adjacent association relationship between the adjacent target position point and the target position point W _o The adjacent association relation between the target position points W is determined as the target position points W _o Position correlation of (a)Is tied up.

6. The method according to claim 1, wherein the generating the set of relative elevation constraints corresponding to the at least two target location points according to the location association relationship between the at least two target location points includes:

According to the position incidence relation between the at least two target position points, obtaining A target position point pairs with the position incidence relation respectively; a is a positive integer, and A target position point pairs comprise target position point pairs B _c The method comprises the steps of carrying out a first treatment on the surface of the c is a positive integer and c is less than or equal to A;

according to the target position point pair B _c The position association relation generates a target position point pair B for the target position point pair _c Is a relative elevation constraint of (2);

and determining the corresponding relative elevation constraint conditions of the A target position points as a set of the corresponding relative elevation constraint conditions of the at least two target position points.

7. The method of claim 6, wherein said determining said target location point pair B _c The position association relation generates a target position point pair B for the target position point pair _c A relative elevation constraint of (2), comprising:

if the target position point pair B _c The position association relationship is adjacent association relationship, and the target position point pair B is based on the position association relationship _c Two-dimensional position information and target gradient corresponding to two target position points respectively, and generating a target position point pair B _c Is a relative elevation constraint of (2);

if the target position point pair B _c The position association relationship is an up-down association relationship, and the target position point pair B is based on the position association relationship _c The relative elevation up-down information of two target position points in the model, and the target height difference, and generating a target position point pair B aiming at the target position points _c Is a relative elevation constraint of (2);

if the target position point pair B _c With bitsSetting the association relationship as an adjacent association relationship, and generating a point pair B aiming at the target position according to the target adjacent information _c Is a relative elevation constraint of (2).

8. The method of claim 1, wherein determining initial distribution characteristic information for at least two initial relative elevations comprises:

acquiring a relative height Cheng Youhua device, and inputting at least two initial relative heights into the relative height Cheng Youhua device; the relative elevation optimizer includes a distribution feature function;

and determining initial distribution characteristic information of the at least two initial relative elevations through the distribution characteristic function.

9. The method of claim 8, wherein said determining initial distribution characteristic information for said at least two initial relative elevations by said distribution characteristic function comprises:

obtaining square values corresponding to the at least two initial relative elevations respectively through the distribution characteristic function;

Summing the square values corresponding to the at least two initial relative elevations respectively to obtain a dispersion degree value of the at least two initial relative heights Cheng Duiying;

and determining the dispersion degree value of the at least two initial relative heights Cheng Duiying as initial distribution characteristic information of the at least two initial relative heights.

10. The method of claim 8, wherein the adjusting the at least two initial relative elevations based on the initial distribution feature information and the set of relative elevation constraints, respectively, to obtain the relative elevations corresponding to the at least two target location points, respectively, comprises:

inputting the set of relative elevation constraints to the relative high Cheng Youhua machine;

in the relative elevation optimizer, the at least two initial relative elevations are respectively adjusted based on the initial distribution characteristic information to obtain relative elevations to be optimized, which correspond to the at least two target position points respectively; at least two relative elevations to be optimized meet the relative elevation constraint conditions in the relative elevation constraint condition set;

inputting the at least two relative elevations to be optimized into the distribution characteristic function, and determining distribution characteristic information to be optimized of the at least two relative elevations to be optimized through the distribution characteristic function;

Respectively adjusting the at least two relative elevations to be optimized based on the distribution characteristic information to be optimized to obtain the relative elevations corresponding to the at least two target position points respectively; the dispersion degree value corresponding to the distribution characteristic information of at least two relative elevations is smaller than the dispersion degree value corresponding to the distribution characteristic information to be optimized, and the at least two relative elevations meet the relative elevation constraint condition set.

11. The method of claim 10, wherein the adjusting the at least two relative elevations to be optimized based on the distribution characteristic information to be optimized to obtain the relative elevations corresponding to the at least two target location points respectively includes:

respectively adjusting the at least two relative elevations to be optimized based on the distribution characteristic information to be optimized to obtain candidate relative elevations corresponding to the at least two target position points respectively;

inputting at least two candidate relative elevations into the distribution characteristic function, and determining candidate distribution characteristic information of the at least two candidate relative elevations through the distribution characteristic function;

and determining the relative elevation corresponding to each of the at least two target position points according to the distribution characteristic information to be optimized and the candidate distribution characteristic information.

12. The method according to claim 11, wherein determining the relative elevation of the at least two target location points according to the distribution feature information to be optimized and the candidate distribution feature information includes:

determining a dispersion distance between dispersion degree values corresponding to the distribution characteristic information to be optimized and dispersion degree values corresponding to the candidate distribution characteristic information;

if the dispersion distance is smaller than the dispersion distance threshold value, acquiring the relative elevation corresponding to the at least two target position points from the relative elevation set; the set of relative elevations includes the at least two relative elevations to be optimized and the at least two candidate relative elevations;

and if the dispersion distance is equal to or greater than the dispersion distance threshold, respectively adjusting the at least two candidate relative elevations based on the candidate distribution characteristic information to obtain the relative elevations respectively corresponding to the at least two target position points.

13. The method according to claim 1, wherein the method further comprises:

acquiring position points except the at least two target position points in the road from navigation data corresponding to the two-dimensional road network as intermediate position points;

Acquiring a fifth target position point and a sixth target position point which respectively have adjacent association relations with the intermediate position point from the at least two target position points;

determining a relative elevation corresponding to the intermediate position point according to the fifth target position point and the sixth target position point;

and determining the relative elevation corresponding to the road as the relative elevation corresponding to the at least two target position points and the relative elevation corresponding to the intermediate position points.

14. A computer device, comprising: a processor, a memory, and a network interface;

the processor is connected to the memory and the network interface, wherein the network interface is configured to provide a data communication function, the memory is configured to store a computer program, and the processor is configured to invoke the computer program to cause the computer device to perform the method of any of claims 1 to 13.

15. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program adapted to be loaded and executed by a processor to cause a computer device having the processor to perform the method of any of claims 1-13.

16. A computer program product, characterized in that the computer program product comprises a computer program stored in a computer readable storage medium, the computer program being adapted to be read and executed by a processor to cause a computer device having the processor to perform the method of any of claims 1-13.