Method and device for predicting slope resistance

Abstract

The embodiment of the invention provides a slope resistance prediction method and device, and the method comprises the steps: obtaining a navigation route of the travel, the navigation route comprises a plurality of road points, determining the elevation value of each road point according to the latitude and longitude information of each road point, and determining the slope resistance of the travel according to the elevation value, determining the elevation difference between two adjacent road points in the navigation route, determining the interval route distance between the two adjacent road points in the navigation route, and determining the slope resistance between the two adjacent road points in the navigation route according to the elevation difference and the interval route distance. Therefore, the slope resistance is predicted, dependence on expensive network infrastructures is avoided, the implementation and operation cost of the system is reduced, the prediction process of the slope resistance is more flexible and convenient, and the method is particularly suitable for scenes with limited network conditions or sensitive cost.

Description

Technical Field

[0001] The present invention relates to the field of automobile technology, and in particular to a method and device for predicting slope resistance. Background Art

[0002] Currently, there are three main methods for slope resistance consumption identification tasks: real-time slope estimation based on vehicle dynamics, and advance prediction of the slope of the road ahead based on high-precision maps or other environmental perception systems (such as image recognition).

[0003] The real-time slope estimation method based on vehicle dynamics can estimate the slope and slope angle according to the real-time motion parameters of the vehicle, but it cannot judge the slope of the future road. Therefore, the range extender strategy can only be adjusted by means of slope compensation.

[0004] The slope prediction method based on high-precision maps can directly convert longitude and latitude information into elevation information, and the slope can be calculated in combination with road information. However, this type of method has high map production costs and is difficult. The mass production application of high-precision maps must be based on the architecture of the Internet of Vehicles to achieve cloud storage, real-time updates and crowdsourcing of maps. Problems such as these have hindered the development of high-precision maps for slope estimation.

[0005] Slope prediction methods based on image recognition algorithms usually involve using computer vision technology to analyze images of terrain or structural surfaces and predict their slopes. The accuracy of slope prediction depends largely on the quality of the input image. If the image is blurred, overexposed, or underexposed, it may affect the recognition effect of the algorithm. In addition, some slope prediction algorithms may be computationally complex and require high computing resources, which may limit their use in real-time or resource-constrained application scenarios. Summary of the invention

[0006] In view of the above problems, a method and device for predicting slope resistance is proposed to overcome the above problems or at least partially solve the above problems, including:

[0007] A method for predicting slope resistance, the method comprising:

[0008] Obtaining a navigation route; wherein the navigation route includes a plurality of waypoints;

[0009] Determine the elevation value of each waypoint according to the latitude and longitude information of each waypoint, and determine the elevation difference between two adjacent waypoints in the navigation route according to the elevation value;

[0010] Determine the interval route distance between two adjacent waypoints in the navigation route;

[0011] The slope resistance between two adjacent waypoints in the navigation route is determined according to the elevation difference and the interval route distance.

[0012] Optionally, determining the elevation value of each waypoint according to the latitude and longitude information of each waypoint includes:

[0013] Obtaining a preset elevation matrix data file; wherein the elevation matrix data file includes elevation values ​​corresponding to a plurality of longitudes and latitudes;

[0014] According to the latitude and longitude information of each waypoint, the elevation value corresponding to each waypoint is obtained from the elevation matrix data file.

[0015] Optionally, before obtaining the preset elevation matrix data file, the method further includes:

[0016] Acquire elevation data of a plurality of longitudes and latitudes, and output the elevation data of each longitude and latitude as grid data stored in a grid form;

[0017] Taking each of the grid data as a sub-matrix, sequentially superimposing multiple sub-matrices according to the longitude and latitude corresponding to each grid data to obtain an elevation matrix;

[0018] The grid data corresponding to each sub-matrix is ​​compressed to obtain a compressed matrix, and is pre-stored as an elevation matrix data file.

[0019] Optionally, the multiple longitudes and latitudes are multiple longitudes and latitudes within the actual geographical scope of the analysis.

[0020] Optionally, compressing the grid data corresponding to each of the sub-matrices includes:

[0021] According to a preset first compression ratio, average pooling is performed on each of the sub-matrices;

[0022] According to the degree of change of each of the sub-matrices, a second compression ratio of each of the sub-matrices is determined, and according to the second compression ratio, average pooling is performed again on the sub-matrices after average pooling.

[0023] Optionally, before determining the second compression ratio of each submatrix according to the degree of change of each submatrix, the method further includes:

[0024] Acquire road data information within the range corresponding to the multiple longitudes and latitudes; wherein the road data information includes the longitude and latitude information of the road;

[0025] According to the road data information and the elevation matrix, the sub-matrix that does not contain the road data information in the elevation matrix is ​​removed.

[0026] Optionally, determining the second compression ratio of each submatrix according to the degree of change of each submatrix includes:

[0027] Obtaining a change degree value of each of the submatrices; wherein the change degree value is the variance of the grid data;

[0028] The second compression ratio is determined according to the change degree value, a preset change degree threshold and a minimum compression ratio; wherein the change degree threshold includes a minimum change degree threshold and a maximum change degree threshold.

[0029] Optionally, after determining the slope resistance between two adjacent waypoints in the navigation route, the method further includes:

[0030] The additional energy consumption between two adjacent waypoints in the navigation route is predicted according to the slope resistance.

[0031] A device for predicting slope resistance, comprising:

[0032] A navigation data acquisition module, used to acquire a navigation route; wherein the navigation route includes a plurality of waypoints;

[0033] An elevation difference acquisition module, used to determine the elevation value of each waypoint according to the latitude and longitude information of each waypoint, and determine the elevation difference between two adjacent waypoints in the navigation route according to the elevation value;

[0034] An interval route distance acquisition module is used to determine the interval route distance between two adjacent waypoints in the navigation route;

[0035] The slope resistance determination module is used to determine the slope resistance between two adjacent waypoints in the navigation route according to the elevation difference and the interval route distance.

[0036] An electronic device comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the above-mentioned method for predicting slope resistance when executed by the processor.

[0037] A computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the slope resistance prediction method as described above

[0038] The embodiments of the present invention have the following advantages:

[0039] In an embodiment of the present invention, by obtaining a navigation route of the current trip, the navigation route includes a plurality of waypoints, determining an elevation value of each waypoint according to the longitude and latitude information of each waypoint, determining an elevation difference between two adjacent waypoints in the navigation route according to the elevation value, determining an interval route distance between two adjacent waypoints in the navigation route, and determining a slope resistance between two adjacent waypoints in the navigation route according to the elevation difference and the interval route distance, the longitude and latitude of navigation data are converted into elevation data to predict the slope resistance, which is independent of the architecture of the Internet of Vehicles and the end-cloud integration, and is obtained in a relatively low-cost manner, avoiding dependence on expensive network infrastructure, reducing the cost of system implementation and operation, simplifying the data acquisition path, and making the process of predicting the slope resistance more flexible and convenient, which is particularly suitable for scenarios with limited network conditions or cost sensitivity. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0041] Figure 1 is a flow chart of steps of a method for predicting slope resistance provided by some embodiments of the present invention;

[0042] Figure 2 is a schematic diagram of grid data provided by some embodiments of the present invention;

[0043] Figure 3 is a flowchart of steps for compressing submatrices corresponding to grid data provided by some embodiments of the present invention;

[0044] Figure 4 is a schematic diagram of navigation route information provided by some embodiments of the present invention;

[0045] Figure 5 It is a structural block diagram of a device for predicting slope resistance provided by some embodiments of the present invention. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] Reference Figure 1 , shows a flow chart of the steps of a method for predicting slope resistance provided by some embodiments of the present invention, which may specifically include the following steps:

[0048] Step 101, obtaining a navigation route; wherein the navigation route includes a plurality of waypoints.

[0049] When a car user drives a car, navigation data of the user's trip, that is, a navigation route, can be obtained. The navigation route may include multiple waypoints, and the waypoints may be sites on the navigation route that include latitude and longitude information.

[0050] Step 102: determining the elevation value of each waypoint according to the latitude and longitude information of each waypoint, and determining the elevation difference between two adjacent waypoints in the navigation route according to the elevation value.

[0051] In some embodiments of the present invention, determining the elevation value of each waypoint according to the latitude and longitude information of each waypoint includes:

[0052] Sub-step 11, obtaining a preset elevation matrix data file; wherein the elevation matrix data file includes elevation values ​​corresponding to a plurality of longitudes and latitudes.

[0053] After obtaining the navigation route, a preset elevation matrix data file may be obtained, wherein the elevation matrix data file includes elevation values ​​corresponding to a plurality of longitudes and latitudes.

[0054] Sub-step 12, obtaining the elevation value corresponding to each waypoint from the elevation matrix data file according to the latitude and longitude information of each waypoint.

[0055] Through the navigation route, the longitude and latitude information of each waypoint in the navigation route can be obtained, so that the elevation value corresponding to each waypoint in the navigation route can be obtained from the elevation matrix data file based on the longitude and latitude information.

[0056] In some embodiments of the present invention, before obtaining the preset elevation matrix data file, the method further includes:

[0057] Sub-step 21, obtaining elevation data of a plurality of longitudes and latitudes, and outputting the elevation data of each longitude and latitude as grid data stored in a grid form.

[0058] Before obtaining the preset elevation matrix data file, the elevation data of each degree in the plurality of longitudes and latitudes may be obtained, and the elevation data of each degree may be output as grid data stored in a grid form.

[0059] In practical applications, this stage can be called the offline processing stage. After obtaining the elevation data of each degree in multiple longitudes and latitudes, the elevation data of each degree can be output as an hgt elevation data file for each degree in the longitude and latitude coordinates, where hgt is a file format of SRTM (Shuttle Radar Topography Mission) data, which is used to store elevation data in the form of grids. Each grid point has a corresponding elevation value in meters.

[0060] For example, see Attachment Figure 2 , showing a schematic diagram of the grid data provided by some embodiments of the present invention, the figure shows a ght elevation data file with the file name N27E086.ght and longitude and latitude of 27 degrees north latitude and 86 degrees east longitude. The file divides the entire space into 1201*1201 grids with a resolution of 90 meters, and each grid has an elevation value.

[0061] Sub-step 22, taking each of the grid data as a sub-matrix, and sequentially superimposing multiple sub-matrices according to the longitude and latitude corresponding to each grid data to obtain an elevation matrix.

[0062] Specifically, after obtaining multiple grid data, longitude and latitude boundary values ​​can be obtained according to the multiple longitudes and latitudes corresponding to the multiple grid data, so that each of the grid data can be orderly superimposed as a submatrix according to the longitude and latitude boundary values ​​to obtain an elevation matrix.

[0063] In practical applications, after obtaining multiple hgt elevation data files, each hgt elevation data file can be used as a sub-matrix, so that the longitude and latitude boundary values ​​can be obtained according to the longitude and latitude information corresponding to each sub-matrix, and each sub-matrix can be superimposed in order according to the longitude and latitude boundary values ​​to form a large elevation matrix.

[0064] In one example, if the hgt elevation data file is M, taking the i-row and j-column submatrix as an example, after orderly superposition, the following matrix can be formed:

[0065]

[0066] Sub-step 23, compressing the grid data corresponding to each sub-matrix to obtain a compressed matrix, and pre-storing it as an elevation matrix data file.

[0067] Specifically, each sub-matrix in the elevation matrix can be compressed to obtain a compressed matrix, and the compressed matrix is ​​pre-stored as an elevation matrix data file. The elevation matrix data file is used to obtain the corresponding elevation value through the pre-stored elevation matrix data file when performing slope resistance prediction.

[0068] In some embodiments of the present invention, the multiple longitudes and latitudes are multiple longitudes and latitudes within the actual geographical scope of the analysis.

[0069] Specifically, the multiple longitudes and latitudes may be multiple longitudes and latitudes contained in the actual analyzed geographical scope, wherein the actual analyzed geographical scope may be a geographical scope selected for actual slope resistance prediction analysis.

[0070] As an example, the administrative scope of Yunnan, Guizhou and Sichuan can be selected as an example, so that 141 ght elevation data files can be obtained through the longitude and latitude within the administrative scope of Yunnan, Guizhou and Sichuan.

[0071] In some embodiments of the present invention, compressing the grid data corresponding to each of the sub-matrices includes:

[0072] Sub-step 31: performing average pooling on each of the sub-matrices according to a preset first compression ratio.

[0073] Specifically, a first compression ratio may be preset for preliminary compression of the sub-matrix, and the sub-matrix may be average pooled according to the first compression ratio.

[0074] In practical applications, grid data, i.e., the resolution of the submatrix corresponding to the ght elevation data file is 30 meters, can be used as an example. Through matrix sparse technology, the submatrix can be compressed to a resolution of 900 meters, with a compression ratio of 1 / 30. The matrix sparse technology can be average pooling, so that each submatrix can be average pooled, sliding with a 30*30 window sliding window, and a step length of 30 meters.

[0075] Sub-step 32, determining a second compression ratio of each of the sub-matrices according to the degree of change of each of the sub-matrices, and performing average pooling again on the sub-matrices after average pooling according to the second compression ratio.

[0076] Specifically, after average pooling is performed on each sub-matrix using the first compression ratio, a compression ratio, i.e., a second compression ratio, can be determined according to the degree of change of each sub-matrix, and the sub-matrix after average pooling using the first compression ratio can be compressed again according to the second compression ratio, and the compression can also use the average pooling technology.

[0077] Generally speaking, the relative height of urban roads changes more slowly, while the relative height of rural roads changes more dramatically. Therefore, when compressing the submatrix after average pooling using the first compression ratio again, it is necessary to consider the degree of change of each submatrix to avoid excessive compression, that is, excessive pooling, and loss of too much elevation feature information in the submatrix. Therefore, the second compression ratio is determined according to the degree of change of each submatrix.

[0078] In some embodiments of the present invention, before determining the second compression ratio of each submatrix according to the degree of change of each submatrix, the method further includes:

[0079] Sub-step 41, obtaining road data information within the range corresponding to the multiple longitudes and latitudes; wherein the road data information includes the longitude and latitude information of the road.

[0080] Specifically, the corresponding road space data within the actual analysis geographic scope can be obtained, and the road space data includes the latitude and longitude information of the roads within the actual analysis geographic scope. However, the actual roads include urban roads, rural roads, ramps, highways, etc., and the latitude and longitude data may have certain positioning errors. Therefore, a buffer zone can be constructed with the line data in the road space data as the boundary, such as a 500-meter buffer zone, to form surface data, which is the road data information.

[0081] In one example, the road spatial data corresponding to the actual analysis geographic scope is obtained, and the road spatial data can be stored in a GeoJSON file, where GeoJSON is an open standard format for representing geographic spatial data, based on JSON (JavaScript Object Notation). GeoJSON files can represent geographic elements such as points, lines, polygons, and their attributes and spatial relationships. GeoJSON is widely used in geographic information systems (GIS), map services, spatial data analysis and other fields.

[0082] Sub-step 42, based on the road data information and the elevation matrix, removing the sub-matrix that does not contain the road data information in the elevation matrix.

[0083] Specifically, according to the road data information and the elevation matrix, the sub-matrix that does not contain the road data information in the elevation matrix is ​​removed, which can be achieved by intersecting the road data information with the elevation matrix.

[0084] In some embodiments of the present invention, determining the second compression ratio of each submatrix according to the degree of change of each submatrix includes:

[0085] Sub-step 51, obtaining a variation degree value of each of the sub-matrices; wherein the variation degree value is the variance of the grid data.

[0086] Specifically, the variation degree value of each submatrix may be obtained, and the variation degree value may be the variance of the grid data, that is, the variance of the submatrix is ​​introduced to quantify the variation degree of the element values ​​in the submatrix.

[0087] In one example, for example, the submatrix after average pooling using the first compression ratio is Aij , for the submatrix A ij The degree of change can be measured by the variance To express:

[0088]

[0089] Among them, x represents the elevation value corresponding to each grid element in the submatrix, and u represents the average value of all elevation values ​​in the submatrix.

[0090] Sub-step 52, determining the second compression ratio according to the change degree value, a preset change degree threshold and a minimum compression ratio; wherein the change degree threshold includes a minimum change degree threshold and a maximum change degree threshold.

[0091] Specifically, if the change degree value is small, a larger compression ratio is applied, otherwise, a smaller compression ratio is applied. The change degree threshold and the minimum compression ratio C can be set in advance. min , the change degree threshold may include a minimum change degree threshold T min and the maximum change threshold T max At the same time, all sub-matrices can be traversed to calculate the change degree value of each sub-matrix, and the change degree value can be compared with the preset change degree threshold and the minimum compression ratio C. min , determine the second compression ratio of each sub-matrix.

[0092] As an example, the second compression ratio may be set to C, and the following calculation formula for the second compression ratio may be used:

[0093]

[0094] Then, the change degree value and the preset change degree threshold and the minimum compression ratio C can be used. min Calculation is performed to determine the second compression ratio. It should be noted that, by introducing the minimum compression ratio, it can be ensured that even if the value of the variation degree is large, there will not be no compression at all.

[0095] Reference Figure 3 , shows a flowchart of the steps of compressing the sub-matrix corresponding to the grid data provided by some embodiments of the present invention. It can be seen from the accompanying drawings that the compression of the sub-matrix corresponding to the grid data in the present invention can be generally summarized into three steps:

[0096] (1) Global average pooling, that is, average pooling of all sub-matrices;

[0097] (2) Take the intersection of the elevation matrix and the road data information and remove the redundant sub-matrices;

[0098] (3) Based on the degree of change of each sub-matrix, compression is performed using a corresponding compression ratio.

[0099] Step 103: determine the interval route distance between two adjacent waypoints in the navigation route.

[0100] Specifically, the interval route distance between two adjacent waypoints in the navigation route can be obtained according to the distance from the car to two adjacent waypoints in the navigation route.

[0101] As an example, see the attached Figure 4 , shows a schematic diagram of navigation route information provided by some embodiments of the present invention. In the figure, a site adjacent to the starting point can be used as a waypoint, and a site adjacent to the waypoint can be used as another waypoint. The distances from the starting point to these two waypoints are 300m and 700m respectively, so the interval route distance is 400m.

[0102] Step 104: Determine the slope resistance between two adjacent waypoints in the navigation route according to the elevation difference and the interval route distance.

[0103] Specifically, after the elevation difference and the corresponding interval route distance are obtained, the slope resistance between two adjacent waypoints in the navigation route can be determined according to the elevation difference and the interval route distance.

[0104] As an example, two adjacent points can be selected to calculate the elevation difference between them. Assuming that the elevation of the first point is h1 and the elevation of the second point is h2, the elevation difference △h = h2-h1; then the interval route distance can be determined as s, so the slope S and slope resistance coefficient C can be calculated according to the following formula: r and slope resistance F slope :

[0105]

[0106] C r = sin(arctan(S / 100))

[0107] F slope =m·g·C r

[0108] In the above formula, m is the mass of the car and g is the acceleration due to gravity.

[0109] In some embodiments of the present invention, after determining the slope resistance between two adjacent waypoints in the navigation route, the method further includes:

[0110] The additional energy consumption between two adjacent waypoints in the navigation route is predicted according to the slope resistance.

[0111] Specifically, after obtaining the slope resistance, the additional energy consumption between two adjacent waypoints in the navigation route can be predicted by the slope resistance. It should be added that in practical applications, by combining the navigation route, it is possible to know in advance how much additional energy consumption is caused by the slope change ahead, which not only improves the calculation method, but also allows the car to generate more electricity in advance to reduce energy consumption.

[0112] In an embodiment of the present invention, a navigation route is obtained by acquiring multiple first driving routes of the trip, the navigation route including multiple waypoints, and the elevation value of each waypoint is determined according to the longitude and latitude information of each waypoint, and the elevation difference between two adjacent waypoints in the navigation route is determined according to the elevation value, and the interval route distance between two adjacent waypoints in the navigation route is determined, and the slope resistance between two adjacent waypoints in the navigation route is determined according to the elevation difference and the interval route distance, so that the longitude and latitude of navigation data are converted into elevation data to predict the slope resistance, which is independent of the Internet of Vehicles and the terminal-cloud integrated architecture, and the slope resistance is obtained in a relatively low-cost manner, avoiding dependence on expensive network infrastructure, reducing the cost of system implementation and operation, simplifying the data acquisition path, and making the process of predicting the slope resistance more flexible and convenient, which is particularly suitable for scenarios with limited network conditions or cost sensitivity.

[0113] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0114] Reference Figure 5 , shows a schematic diagram of the structure of a device for predicting slope resistance provided by some embodiments of the present invention, which may specifically include the following modules:

[0115] The navigation data acquisition module 501 is used to acquire a navigation route; wherein the navigation route includes a plurality of waypoints;

[0116] The elevation difference acquisition module 502 is used to determine the elevation value of each waypoint according to the latitude and longitude information of each waypoint, and determine the elevation difference between two adjacent waypoints in the navigation route according to the elevation value;

[0117] The interval route distance acquisition module 503 is used to determine the interval route distance between two adjacent waypoints in the navigation route;

[0118] The slope resistance determination module 504 is used to determine the slope resistance between two adjacent waypoints in the navigation route according to the elevation difference and the interval route distance.

[0119] In some embodiments of the present invention, the elevation difference acquisition module 502 includes:

[0120] The elevation matrix data file acquisition submodule is used to acquire a preset elevation matrix data file; wherein the elevation matrix data file includes elevation values ​​corresponding to a plurality of longitudes and latitudes;

[0121] The elevation value acquisition submodule is used to obtain the elevation value corresponding to each of the waypoints from the elevation matrix data file according to the latitude and longitude information of each of the waypoints.

[0122] In some embodiments of the present invention, the device further comprises:

[0123] A grid data acquisition module is used to acquire elevation data of multiple longitudes and latitudes, and output the elevation data of each longitude and latitude as grid data stored in a grid form;

[0124] The elevation matrix acquisition module is used to take each of the grid data as a sub-matrix, and sequentially superimpose multiple sub-matrices according to the longitude and latitude corresponding to each grid data to obtain an elevation matrix;

[0125] The elevation matrix data file acquisition module is used to compress the grid data corresponding to each sub-matrix to obtain a compressed matrix, and preset and store it as an elevation matrix data file.

[0126] In some embodiments of the present invention, the multiple longitudes and latitudes are multiple longitudes and latitudes within the actual geographical scope of the analysis.

[0127] In some embodiments of the present invention, the elevation matrix data file acquisition module includes:

[0128] A first pooling submodule, configured to perform average pooling on each of the submatrices according to a preset first compression ratio;

[0129] The second pooling submodule is used to determine a second compression ratio of each submatrix according to the degree of change of each submatrix, and perform average pooling again on the submatrix after average pooling according to the second compression ratio.

[0130] In some embodiments of the present invention, the grid data pooling module further includes:

[0131] A road data information acquisition submodule, used to acquire road data information within the range corresponding to the plurality of longitudes and latitudes; wherein the road data information includes the longitude and latitude information of the road;

[0132] The sub-matrix removal sub-module is used to remove the sub-matrix that does not contain the road data information in the elevation matrix according to the road data information and the elevation matrix.

[0133] In some embodiments of the present invention, the second pooling submodule includes:

[0134] A variation degree value acquisition unit, used to acquire a variation degree value of each of the sub-matrices; wherein the variation degree value is the variance of the grid data;

[0135] The second compression ratio determination unit is used to determine the second compression ratio according to the change degree value, a preset change degree threshold and a minimum compression ratio; wherein the change degree threshold includes a minimum change degree threshold and a maximum change degree threshold.

[0136] In some embodiments of the present invention, the device further comprises:

[0137] The extra energy consumption prediction module is used to predict the extra energy consumption between two adjacent waypoints in the navigation route according to the slope resistance.

[0138] Some embodiments of the present invention further provide an electronic device, comprising a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the above slope resistance prediction method when executed by the processor.

[0139] Some embodiments of the present invention further provide a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the slope resistance prediction method as described above.

[0140] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0141] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0142] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0143] Those skilled in the art will appreciate that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0144] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0145] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0146] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0147] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0148] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the above elements.

[0149] The above is a detailed introduction to a method and device for predicting slope resistance. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for predicting slope resistance, characterized in that: The method comprises: Obtaining a navigation route; wherein the navigation route includes a plurality of waypoints; Determine the elevation value of each waypoint according to the latitude and longitude information of each waypoint, and determine the elevation difference between two adjacent waypoints in the navigation route according to the elevation value; Determine the interval route distance between two adjacent waypoints in the navigation route; The slope resistance between two adjacent waypoints in the navigation route is determined according to the elevation difference and the interval route distance.

2. The method according to claim 1, characterized in that Determining the elevation value of each waypoint according to the latitude and longitude information of each waypoint includes: Obtaining a preset elevation matrix data file; wherein the elevation matrix data file includes elevation values ​​corresponding to a plurality of longitudes and latitudes; According to the latitude and longitude information of each waypoint, the elevation value corresponding to each waypoint is obtained from the elevation matrix data file.

3. The method according to claim 2, characterized in that Before obtaining the preset elevation matrix data file, the method further includes: Acquire elevation data of a plurality of longitudes and latitudes, and output the elevation data of each longitude and latitude as grid data stored in a grid form; Taking each of the grid data as a sub-matrix, sequentially superimposing multiple sub-matrices according to the longitude and latitude corresponding to each grid data to obtain an elevation matrix; The grid data corresponding to each sub-matrix is ​​compressed to obtain a compressed matrix, and is pre-stored as an elevation matrix data file.

4. The method according to claim 3, characterized in that The multiple longitudes and latitudes are multiple longitudes and latitudes within the actual geographical scope of the analysis.

5. The method according to claim 3, characterized in that: The compressing the grid data corresponding to each of the sub-matrices includes: Performing average pooling on each of the sub-matrices according to a preset first compression ratio; According to the degree of change of each of the sub-matrices, a second compression ratio of each of the sub-matrices is determined, and according to the second compression ratio, average pooling is performed again on the sub-matrices after average pooling.

6. The method according to claim 5, characterized in that Before determining the second compression ratio of each submatrix according to the degree of change of each submatrix, the method further includes: Acquire road data information within the range corresponding to the multiple longitudes and latitudes; wherein the road data information includes the longitude and latitude information of the road; According to the road data information and the elevation matrix, the sub-matrix that does not contain the road data information in the elevation matrix is ​​removed.

7. The method according to claim 5, characterized in that Determining the second compression ratio of each submatrix according to the degree of change of each submatrix includes: Obtaining a change degree value of each of the submatrices; wherein the change degree value is the variance of the grid data; The second compression ratio is determined according to the change degree value, a preset change degree threshold and a minimum compression ratio; wherein the change degree threshold includes a minimum change degree threshold and a maximum change degree threshold.

8. The method according to claim 1, characterized in that After determining the slope resistance between two adjacent waypoints in the navigation route, the method further includes: The additional energy consumption between two adjacent waypoints in the navigation route is predicted according to the slope resistance.

9. A device for predicting slope resistance, characterized in that: The device comprises: A navigation data acquisition module, used to acquire a navigation route; wherein the navigation route includes a plurality of waypoints; An elevation difference acquisition module, used to determine the elevation value of each waypoint according to the latitude and longitude information of each waypoint, and determine the elevation difference between two adjacent waypoints in the navigation route according to the elevation value; An interval route distance acquisition module is used to determine the interval route distance between two adjacent waypoints in the navigation route; The slope resistance determination module is used to determine the slope resistance between two adjacent waypoints in the navigation route according to the elevation difference and the interval route distance.

10. An electronic device, characterized in that: The invention comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the method for predicting slope resistance according to any one of claims 1 to 8 is implemented.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for predicting slope resistance according to any one of claims 1 to 8 is implemented.

Images