Fuzzy processing method and device for elevation information of geographic data

Abstract

The present application relates to the technical field of electronic map, and provides a fuzzy processing method and device for geographic data elevation information, which comprises the following steps: selecting a plurality of shape points as reference points from each shape point of to-be-labeled elevation information, and the rest shape points are following points; determining an elevation information fuzzy value of each reference point according to an absolute adjustment value, an elevation information absolute value of each reference point and a longitudinal fine adjustment value of each reference point; calculating a longitudinal fine adjustment value of a following point between two adjacent reference points according to a path distance between the two adjacent reference points, a difference value of the longitudinal fine adjustment values of the two adjacent reference points and a path distance of the following point between the two adjacent reference points from one reference point; and determining an elevation information fuzzy value of each following point according to the absolute adjustment value, an elevation information absolute value of each following point and a longitudinal fine adjustment value of each following point. The present application can effectively fuzz the elevation information absolute value.

Description

Technical Field

[0001] This invention relates to the field of electronic map technology, and in particular to a method and apparatus for fuzzy processing of geographic data elevation information. Background Technology

[0002] For autonomous driving, changes in geographic elevation data are crucial information, aiding in better lateral and longitudinal vehicle control. For example, autonomous driving applications need to determine slope information and driving strategies based on elevation differences between adjacent features. However, the true absolute value of geographic elevation data (i.e., absolute altitude) is protected commercial information. In electronic maps, the true absolute value of geographic elevation data cannot be displayed on the front end or stored in the back end. Therefore, when applying geographic elevation data in autonomous driving within electronic maps, a pressing technical challenge is how to uniformly blur the elevation information, maintain a relatively constant gradient of elevation differences, and simultaneously avoid displaying and storing the absolute elevation values. Summary of the Invention

[0003] This invention provides a method and apparatus for fuzzy processing of geographic data elevation information, in order to solve the aforementioned technical problems existing in the prior art.

[0004] This invention provides a method for fuzzy processing of geographic data elevation information, comprising:

[0005] Select multiple shape points as reference points from the shape points of the elevation information to be marked, and use the remaining shape points as follow points;

[0006] The fuzzy value of the elevation information of each reference point is determined based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, so that the gradient of the elevation difference between the two reference points conforms to the error range allowed by the map accuracy.

[0007] The longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the path distance between two adjacent reference points, the difference in the longitudinal fine-tuning value between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points.

[0008] The fuzzy elevation value of each following point is determined based on the absolute adjustment value, the absolute elevation information value of each following point, and the longitudinal fine-tuning value of each following point, ensuring that the gradient of the elevation difference between two following points conforms to the error range allowed by map accuracy.

[0009] The elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points.

[0010] According to the present invention, a fuzzy processing method for geographic data elevation information is provided, which selects multiple shape points as reference points from the shape points of the elevation information to be labeled, and the remaining shape points as follower points, including:

[0011] The map is divided using a grid of preset size;

[0012] Define a buffer zone at the center of each grid.

[0013] Select one shape point within the buffer area as the reference point, and the remaining shape points as follow points.

[0014] According to the fuzzy processing method for geographic data elevation information provided by the present invention, the absolute adjustment value is greater than or equal to 1 / 10 of the difference between the maximum and minimum values ​​of the absolute values ​​of elevation information of all shape points.

[0015] According to the fuzzy processing method for geographic data elevation information provided by the present invention, the range of the longitudinal fine-tuning value of the reference point is [-H / 2, H / 2], and the ratio of H to the minimum horizontal distance between any two adjacent reference points does not exceed 1 / 1000.

[0016] According to a fuzzy processing method for geographic data elevation information provided by the present invention, the fuzzy value of the elevation information of each reference point is determined based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, including:

[0017] For each reference point, the absolute adjustment value and the longitudinal fine-tuning value corresponding to the reference point are added to the absolute value of its elevation information to obtain the fuzzy value of the elevation information of each reference point.

[0018] According to a fuzzy processing method for geographic data elevation information provided by the present invention, the method calculates the longitudinal fine-tuning value of a follower point between two adjacent reference points based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from a follower point located between two adjacent reference points to one of the reference points, including:

[0019] Determine the path distance between two adjacent reference points, and the path distance from the following point to one of the reference points between two adjacent reference points;

[0020] The longitudinal fine-tuning value of the following point between two adjacent reference points is calculated based on the ratio of the path distance from the following point to one of the reference points to the path distance between the two adjacent reference points, and the difference in longitudinal fine-tuning values ​​between the two adjacent reference points.

[0021] According to the fuzzy processing method for geographic data elevation information provided by the present invention, after determining the fuzzy elevation information value of each following point based on the absolute adjustment value, the absolute value of the elevation information of each following point, and the longitudinal fine-tuning value of each following point, the method further includes:

[0022] Obtain the interval path distance between two adjacent following points, and determine the random fluctuation value range [-R / 2, R / 2] based on the interval path distance, where the ratio of R to the interval path distance does not exceed 1 / 1000;

[0023] A random fluctuation value is added to the fuzzy elevation information of the following point, which is then used as the final fuzzy elevation information of the following point.

[0024] A fuzzy processing device for geographic data elevation information provided by the present invention includes:

[0025] The reference point selection module is used to select multiple shape points as reference points from the shape points of the elevation information to be marked, and the remaining shape points are follow points.

[0026] The first fuzzy value determination module is used to determine the fuzzy value of the elevation information of each reference point based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, and to make the gradient of the elevation difference between the two reference points conform to the error range allowed by the map accuracy.

[0027] The fine-tuning value calculation module is used to calculate the longitudinal fine-tuning value of the follower point between two adjacent reference points based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points.

[0028] The second fuzzy value determination module is used to determine the fuzzy value of the elevation information of each following point based on the absolute adjustment value, the absolute value of the elevation information of each following point, and the longitudinal fine-tuning value of each following point, so that the gradient of the elevation difference between the two following points conforms to the error range allowed by the map accuracy.

[0029] The elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points.

[0030] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the fuzzy processing method for geographic data elevation information as described above.

[0031] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the fuzzy processing method for geographic data elevation information as described above.

[0032] The method and apparatus for fuzzy processing of geographic data elevation information provided by this invention fuzzifies the absolute values ​​of elevation information by adding a uniform absolute adjustment value and a longitudinal fine-tuning value to the absolute values ​​of the elevation information of each shape point to be marked. Because of the uniform absolute adjustment value and the fact that the longitudinal fine-tuning values ​​ensure that the gradient of the elevation difference between each shape point remains essentially unchanged, thus conforming to the error range allowed by map accuracy. The fuzzy elevation information is used for map display and storage, eliminating the need to display and store the absolute elevation values. Furthermore, the differences in the longitudinal fine-tuning values ​​prevent the absolute values ​​of the shape point elevation information from being derived through single-point or multi-point measurements, thus providing a confidentiality effect. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0034] Figure 1 This is one of the flowcharts illustrating the fuzzy processing method for geographic data elevation information provided by the present invention;

[0035] Figure 2 This is a schematic diagram of the grid-based map division method used in the fuzzy processing method for geographic data elevation information provided by the present invention;

[0036] Figure 3 Based on Figure 2 A schematic diagram illustrating the selection of reference points for map division in China;

[0037] Figure 4 This is a schematic diagram illustrating the fuzzy processing of reference point elevation information in the fuzzy processing method for geographic data elevation information provided by the present invention.

[0038] Figure 5 This is a schematic diagram of the elevation of each reference point before adjustment in the fuzzy processing method for geographic data elevation information provided by this invention;

[0039] Figure 6 This is a schematic diagram of the elevation during longitudinal fine-tuning of the following point in the fuzzy processing method for geographic data elevation information provided by the present invention;

[0040] Figure 7This is a schematic diagram of the structure of the fuzzy processing device for geographic data elevation information provided by the present invention;

[0041] Figure 8 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0043] The method for fuzzy processing of geographic data elevation information according to embodiments of the present invention, such as... Figure 1 As shown, it includes:

[0044] Step S110: Select multiple shape points as reference points from the shape points of the elevation information to be marked, and the remaining shape points as follower points. Shape points are points that describe changes in the geometric shape of ground features. For roads, especially curves, the points that fit the road as a polygonal line are shape points. Maps, especially autonomous driving maps, require the height information of shape points. For example, the height information of points spaced at certain intervals along a road is used to determine the road slope, so as to control the opening of the brake or accelerator pedal during autonomous driving. In this step, multiple shape points are selected as reference points, and the remaining shape points are follower points. In subsequent processing, only a small number of adjustment values ​​for the reference points need to be manually configured; the adjustment values ​​for the follower points can be automatically calculated based on the adjustment values ​​of the reference points.

[0045] Step S120: Determine the fuzzy elevation information value for each reference point based on the absolute adjustment value, the absolute elevation information value of each reference point, and the longitudinal fine-tuning value of each reference point, ensuring that the gradient of the elevation difference between two reference points conforms to the error range allowed by map accuracy. For all reference points, the absolute adjustment value is a fixed value to ensure that the elevation difference (change in elevation information) between each reference point remains unchanged after adjustment. Each reference point has its own longitudinal fine-tuning value, which is adjusted only to ensure that the gradient of the elevation difference conforms to the error range allowed by map accuracy. Moreover, the longitudinal fine-tuning value of each reference point is different and has a certain degree of randomness, preventing the absolute elevation information value of the shape point from being derived by measuring the fuzzy elevation information values ​​of single or multiple points, thus serving a confidentiality purpose.

[0046] Step S130: Calculate the longitudinal fine-tuning value of the following point between two adjacent reference points based on the path distance between them, the difference in longitudinal fine-tuning values ​​between them, and the path distance from the following point to one of the reference points. Since the longitudinal fine-tuning value of the following point is calculated based on the longitudinal fine-tuning value of the reference point, the longitudinal fine-tuning value of each following point is not identical and has a certain degree of randomness. The path distance refers to the actual distance traveled between the two reference points.

[0047] Step S140: Determine the fuzzy elevation information value of each following point based on the absolute adjustment value, the absolute elevation information value of each following point, and the longitudinal fine-tuning value of each following point, ensuring that the elevation difference gradient between two following points conforms to the allowable error range of map accuracy. Similarly, the absolute adjustment value of each following point is a fixed value, the same as the absolute adjustment value of the reference point, while the longitudinal fine-tuning values ​​of each following point are different. Therefore, after adjustment, the elevation difference between each following point remains basically unchanged, satisfying the map accuracy requirements and ensuring that the absolute elevation information value of the following points is not easily derived. The elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points. For example, if the allowable error for the elevation difference gradient is 1 / 1000, then the ratio of the elevation difference change between two shape points to the path distance between the two shape points does not exceed 1 / 1000.

[0048] The fuzzy processing method for geographic data elevation information provided in this embodiment fuzzifies the absolute values ​​of elevation information by adding a uniform absolute adjustment value and a longitudinal fine-tuning value to the absolute values ​​of the elevation information of each shape point to be marked. Because of the uniform absolute adjustment value and the fact that each shape point's longitudinal fine-tuning value ensures that the gradient of elevation difference changes remains essentially unchanged, thus meeting the allowable error range for map accuracy. For autonomous driving, since the gradient of elevation difference changes remains essentially unchanged, the slope change between two shape points caused by the adjusted elevation difference is not significant, and it will not substantially affect the opening of the brake or accelerator pedals controlled by the autonomous driving system, meeting the accuracy requirements of autonomous driving for maps. The fuzzy elevation information is used for map display and storage, eliminating the need to display and store the absolute values ​​of elevation information. Furthermore, the differences in the longitudinal fine-tuning values ​​prevent the absolute values ​​of the shape point elevation information from being derived through single-point or multi-point measurements, thus providing confidentiality.

[0049] The method in this embodiment, when applied to autonomous driving maps, not only hides the absolute values ​​of the elevation information of each shape point, but also keeps the elevation difference between each shape point basically unchanged, thus providing relatively accurate road slope information for the autonomous driving system.

[0050] In step S110, the reference points can be selected randomly or according to certain rules. The selected reference points should be distributed as evenly as possible on the map to avoid two reference points being too close horizontally and two other reference points being too far horizontally, which would cause the range of vertical fine-tuning values ​​to be too different and result in excessive elevation differences between different reference points and subsequent shape points.

[0051] like Figure 2 As shown, this embodiment adopts the following selection method:

[0052] The map is divided using a grid of preset size. For example, the entire map area (3600km×4800km) is divided into 602km×602km grids, for a total of 6×8 grids.

[0053] Determine a buffer zone at the center of each grid, for example: create a 2km × 2km buffer zone at the center of each grid. Figure 2 The inner box further ensures the uniform distribution of reference points, and the reference points will be selected within this 2km×2km buffer zone.

[0054] Select one shape point within the buffer area as the reference point, and the remaining shape points as follow points. For example... Figure 3 As shown, if there are multiple shape points in the buffer, the shape point closest to a corner of the buffer (the top left corner in this example) is selected as the reference point. For example, points B and b1 are both in the buffer, and points C and c1 are both in the buffer, but points B and C are both closest to the top left corner, so points B and C are selected as reference points. If there are no shape points in the buffer, they are not selected. For example, points d1 and a1 are not in the buffer and are follow points, so they cannot be used as reference points.

[0055] In this embodiment, the absolute adjustment value is a fixed value, and all shape points use the same absolute adjustment value to ensure that the elevation difference between the shape points remains unchanged. To better conceal the absolute value of the elevation information, a larger adjustment is needed. Therefore, the absolute adjustment value is greater than or equal to 1 / 10 of the difference between the maximum and minimum absolute values ​​of the elevation information of all shape points. For example, if the elevation difference between the highest and lowest points among all shape points is 5000m, then the absolute adjustment value must be greater than or equal to 500m.

[0056] The main function of the vertical fine-tuning value is to prevent the absolute value of the elevation information from being calculated backwards. Because the randomness of the vertical fine-tuning value alters the elevation difference between shape points, the change in elevation difference is caused by the different vertical fine-tuning values ​​of each shape point. The difference between the vertical fine-tuning values ​​of two shape points is the amount of elevation difference change between them. Therefore, by limiting the range of the vertical fine-tuning value, the gradient of the elevation difference change between two reference points can be ensured to conform to the allowable error range of map accuracy. Specifically, the range of the vertical fine-tuning value for the reference point is [-H / 2, H / 2]. The ratio of H to the minimum horizontal distance between any two adjacent reference points does not exceed 1 / 1000. Since the horizontal distance between reference points is less than or equal to the path distance between reference points, the ratio of H to the path distance between any two adjacent reference points also does not exceed 1 / 1000, thus ensuring that the gradient of the elevation difference change between two reference points conforms to the allowable error range of map accuracy. For example: Figure 2 If the minimum horizontal distance between two reference points is 600 km, then the random range of the longitudinal fine-tuning value I of the reference point is (-300 m, 300 m).

[0057] In this embodiment, step S120 includes: for each reference point, adding the absolute adjustment value and the longitudinal fine-tuning value corresponding to the reference point to the absolute value of its elevation information to obtain the fuzzy elevation information value of each reference point. For example... Figure 4 As shown, H A H B H C and H D Let A, B, C, and D represent the absolute elevation values ​​of reference points A, B, C, and D, respectively. The absolute elevation values ​​of A, B, C, and D are 60m, 60m, 40m, and 50m, respectively, with an absolute adjustment value of 500m for each. The longitudinal fine-tuning values ​​of reference points A, B, C, and D are 40m, 50m, -50m, and 60m, respectively. Finally, let H represent the fuzzy elevation values ​​of reference points A, B, C, and D. A’ H B’ H C’ and H D’ The m lengths are 600m, 610m, 490m, and 610m respectively.

[0058] In this embodiment, step S130 includes:

[0059] Determine the path distance between two adjacent reference points, and the path distance from the following point to one of the reference points between two adjacent reference points.

[0060] The longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the ratio of the path distance from the follower point to one of the reference points to the path distance between the two adjacent reference points, and the difference in longitudinal fine-tuning values ​​between the two adjacent reference points.

[0061] Specifically, the longitudinal fine-tuning value of the following point between two adjacent reference points is calculated using the following formula:

[0062]

[0063] Where I1 and I2 are the longitudinal fine-tuning values ​​of two adjacent reference points, S is the path distance between two adjacent reference points, and S′ is the path distance from the following point to one of the reference points between two adjacent reference points.

[0064] When calculating the longitudinal fine-tuning value of the following points between two adjacent reference points, one reference point is determined as the starting reference point, and the other adjacent reference point is determined as the ending reference point. The longitudinal fine-tuning value of the following points along the path from the starting reference point to the ending reference point is calculated using the formula described above. Then, this ending reference point is used as the starting point, and the process continues to the next adjacent reference point until all reference points are covered. Clearly, after calculating the longitudinal fine-tuning value of each following point, the gradient of the elevation difference between the two following points also conforms to the allowable error range of map accuracy. For example, the ratio of the elevation difference change of the fuzzy elevation information values ​​of two shape points to the path distance between the two shape points does not exceed 1 / 1000.

[0065] like Figure 5 and 6 As shown, for following points a, b, c, and d between two reference points, the formulas for calculating their respective longitudinal fine-tuning values ​​are as follows:

[0066] I a =[(I D -I A ) / S AD ]×S Aa

[0067] I b =[(I B -I A ) / S AB ]×S Ab

[0068] I c =[(I C -I B ) / S BC ]×S Bc

[0069] I d =[(I D -I C ) / S CD ]×S Cd

[0070] Among them, I A I B IC and I D These represent the longitudinal fine-tuning values ​​for reference points A, B, C, and D, respectively. a I b I c and I d These represent the longitudinal fine-tuning values ​​for following points a, b, c, and d, respectively. AD S represents the path distance from reference point A to reference point D. Aa S represents the path distance from reference point A to following point a; AB S represents the path distance from reference point A to reference point B. Ab S represents the path distance from reference point A to following point b; BC S represents the path distance from reference point B to reference point C. Bc S represents the path distance from reference point B to following point c; CD S represents the path distance from reference point C to reference point D. Cd This represents the path distance from reference point C to following point d.

[0071] In step S140, the fuzzy elevation information values ​​obtained after adjusting each following point with absolute adjustment values ​​and longitudinal fine-tuning values ​​are as follows:

[0072] H' a =H a +Absolute value adjustment+[(I D -I A ) / S AD ]*S Aa

[0073] H' b =H b +Absolute value adjustment+[(I B -I A ) / S AB ]*S Ab

[0074] H' c =H c +Absolute value adjustment+[(I C -I B ) / S BC ]*S Bc

[0075] H' d =H d +Absolute value adjustment+[(I D -I C ) / S CD ]*S Cd

[0076] Among them, H a Hb H c and H d H' represents the absolute values ​​of the elevation information of points a, b, c, and d, respectively. a H' b H' c and H' d These represent the fuzzy values ​​of elevation information for following points a, b, c, and d, respectively.

[0077] Furthermore, to increase the difficulty of retrieving the absolute value of the elevation information, after step S140, the following steps are also included:

[0078] Obtain the interval path distance between two adjacent following points, and determine the random fluctuation value range [-R / 2, R / 2] based on the interval path distance. The ratio of R to the interval path distance shall not exceed 1 / 1000, that is, the adjustment of the random fluctuation value shall also meet the range of map accuracy error. For example, when the interval path distance between point a and its adjacent point on one side (the side in the direction from the starting reference point to the ending reference point) is 10m (generally, the distance between two adjacent points is less than 10m), the random adjustment value of point a shall be in the range of [-0.005m, 0.005m].

[0079] A random fluctuation value is added to the fuzzy elevation information of the following point, which is then used as the final fuzzy elevation information of the following point.

[0080] H' a =H a +Absolute value adjustment+[(I D -I A ) / S AD ]*S Aa +R a

[0081] H' b =H b +Absolute value adjustment+[(I B -I A ) / S AB ]*S Ab +R b

[0082] H' c =H c +Absolute value adjustment+[(I C -I B ) / S BC ]*S Bc +R c

[0083] H' d =H d +Absolute value adjustment+[(I D -IC ) / S CD ]*S Cd +R d

[0084] Among them, R a R b R c and R d These represent the random fluctuation values ​​following points a, b, c, and d, respectively.

[0085] It should be noted that although adding random fluctuation values ​​further increases the difficulty of back-calculating the absolute value of elevation information, the error of the gradient of elevation difference change between each following point increases from 1 / 1000 to 2 / 1000 (one 1 / 1000 comes from the vertical fine-tuning value, and the other 1 / 1000 comes from the random fluctuation value), but the error of 2 / 1000 is still within the range of map accuracy error.

[0086] The following describes the fuzzy processing device for geographic data elevation information provided by the present invention. The fuzzy processing device for geographic data elevation information described below and the fuzzy processing method for geographic data elevation information described above can be referred to in correspondence with each other.

[0087] The fuzzy processing device for geographic data elevation information provided by this invention, such as... Figure 7 As shown, it includes:

[0088] The reference point selection module 710 is used to select multiple shape points as reference points from the shape points of the elevation information to be marked, and the remaining shape points are follow points.

[0089] The first fuzzy value determination module 720 is used to determine the fuzzy value of the elevation information of each reference point based on the absolute adjustment value, the absolute value of the elevation information of each reference point and the longitudinal fine-tuning value of each reference point, and to make the gradient of the elevation difference between the two reference points conform to the error range allowed by the map accuracy.

[0090] The fine-tuning value calculation module 730 is used to calculate the longitudinal fine-tuning value of the following point between two adjacent reference points based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from the following point located between two adjacent reference points to one of the reference points.

[0091] The second fuzzy value determination module 740 is used to determine the fuzzy value of the elevation information of each following point based on the absolute adjustment value, the absolute value of the elevation information of each following point and the longitudinal fine-tuning value of each following point, and to make the gradient of the elevation difference between the two following points conform to the error range allowed by the map accuracy.

[0092] The elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points.

[0093] The fuzzy processing device for geographic data elevation information provided by this invention fuzzifies the absolute values ​​of elevation information by adding a uniform absolute adjustment value and a longitudinal fine-tuning value to the absolute values ​​of the elevation information of each shape point to be marked. Because of the uniform absolute adjustment value and the fact that the individual longitudinal fine-tuning values ​​ensure that the gradient of the elevation difference between each shape point remains essentially unchanged, i.e., it conforms to the error range allowed by map accuracy. The fuzzy elevation information is used for map display and storage, eliminating the need to display and store the absolute elevation values. Furthermore, the differences in the individual longitudinal fine-tuning values ​​prevent the absolute values ​​of the shape point elevation information from being derived through single-point or multi-point measurements, thus achieving a confidentiality effect.

[0094] Optionally, the reference point selection module 710 is specifically used to divide the map using a grid of preset size; determine a buffer area at the center of each grid; select a shape point within the buffer area as a reference point, and the remaining shape points as follow points.

[0095] Optionally, the absolute adjustment value is greater than or equal to 1 / 10 of the difference between the maximum and minimum absolute values ​​of the elevation information of all shape points.

[0096] Optionally, the range of the longitudinal fine-tuning value of the reference point is [-H / 2, H / 2], and the ratio of H to the minimum horizontal distance between any two adjacent reference points does not exceed 1 / 1000.

[0097] Optionally, the first fuzzy value determination module 720 is specifically used to add the absolute adjustment value and the longitudinal fine-tuning value corresponding to the reference point to the absolute value of the elevation information of each reference point to obtain the fuzzy elevation information value of each reference point.

[0098] Optionally, the fine-tuning value calculation module 730 includes:

[0099] The path distance determination module is used to determine the path distance between two adjacent reference points, and the path distance from the following point to one of the reference points between two adjacent reference points;

[0100] The calculation module is used to calculate the longitudinal fine-tuning value of the follower point between two adjacent reference points based on the ratio of the path distance from the follower point to one of the reference points to the path distance between the two adjacent reference points, and the difference in longitudinal fine-tuning values ​​between the two adjacent reference points.

[0101] Optionally, the fuzzy processing device for geographic data elevation information of the present invention further includes:

[0102] The random value range determination module is used to obtain the interval path distance between two adjacent following points, and determine the random fluctuation value range [-R / 2, R / 2] based on the interval path distance, and the ratio of R to the interval path distance does not exceed 1 / 1000.

[0103] The random addition module is used to add random fluctuation values ​​to the fuzzy elevation information of the following points, which serve as the final fuzzy elevation information of the following points.

[0104] Figure 8 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 8 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other via the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute a fuzzy processing method for geographic data elevation information, the method including:

[0105] Select multiple shape points from the shape points of the elevation information to be marked as reference points, and the remaining shape points as follow points.

[0106] The fuzzy value of the elevation information of each reference point is determined based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, so that the gradient of the elevation difference between the two reference points conforms to the error range allowed by the map accuracy.

[0107] The longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points.

[0108] The fuzzy value of the elevation information of each following point is determined based on the absolute adjustment value, the absolute value of the elevation information of each following point, and the longitudinal fine-tuning value of each following point, so that the gradient of the elevation difference between the two following points conforms to the error range allowed by the map accuracy.

[0109] The elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points.

[0110] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, essentially, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0111] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program that can be stored on a non-transitory computer-readable storage medium, wherein when the computer program is executed by a processor, the computer is capable of executing the fuzzy processing method for geographic data elevation information provided by the above methods, the method comprising:

[0112] Select multiple shape points from the shape points of the elevation information to be marked as reference points, and the remaining shape points as follow points.

[0113] The fuzzy value of the elevation information of each reference point is determined based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, so that the gradient of the elevation difference between the two reference points conforms to the error range allowed by the map accuracy.

[0114] The longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points.

[0115] The fuzzy value of the elevation information of each following point is determined based on the absolute adjustment value, the absolute value of the elevation information of each following point, and the longitudinal fine-tuning value of each following point, so that the gradient of the elevation difference between the two following points conforms to the error range allowed by the map accuracy.

[0116] The elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points.

[0117] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a fuzzy processing method for geographic data elevation information provided by the methods described above, the method comprising:

[0118] Select multiple shape points from the shape points of the elevation information to be marked as reference points, and the remaining shape points as follow points.

[0119] The fuzzy value of the elevation information of each reference point is determined based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, so that the gradient of the elevation difference between the two reference points conforms to the error range allowed by the map accuracy.

[0120] The longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points.

[0121] The fuzzy value of the elevation information of each following point is determined based on the absolute adjustment value, the absolute value of the elevation information of each following point, and the longitudinal fine-tuning value of each following point, so that the gradient of the elevation difference between the two following points conforms to the error range allowed by the map accuracy.

[0122] The elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points.

[0123] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0124] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0125] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A fuzzy processing method for elevation information in geographic data, characterized in that, include: Select multiple shape points as reference points from the shape points of the elevation information to be marked, and use the remaining shape points as follow points; The fuzzy value of the elevation information of each reference point is determined based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, and the gradient of the elevation difference between two reference points conforms to the error range allowed by the map accuracy. The range of the longitudinal fine-tuning value of the reference point is [-H / 2, H / 2], and the ratio of H to the minimum horizontal distance between any two adjacent reference points does not exceed 1 / 1000. The longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the path distance between two adjacent reference points, the difference in the longitudinal fine-tuning value between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points. The fuzzy elevation value of each following point is determined based on the absolute adjustment value, the absolute elevation information value of each following point, and the longitudinal fine-tuning value of each following point, ensuring that the gradient of the elevation difference between two following points conforms to the error range allowed by map accuracy. Wherein, the elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points; Specifically, the longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points. This includes: Determine the path distance between two adjacent reference points, and the path distance from the following point to one of the reference points between two adjacent reference points; The longitudinal fine-tuning value of the follower point between two adjacent reference points is calculated based on the ratio of the path distance from the follower point to one of the reference points to the path distance between the two adjacent reference points, and the difference in longitudinal fine-tuning values ​​between the two adjacent reference points.

2. The fuzzy processing method for geographic data elevation information according to claim 1, characterized in that, From the various shape points of the elevation information to be marked, select multiple shape points as reference points, and the remaining shape points as follower points, including: The map is divided using a grid of preset size; Define a buffer zone at the center of each grid. Select one shape point within the buffer area as the reference point, and the remaining shape points as follow points.

3. The fuzzy processing method for geographic data elevation information according to claim 1, characterized in that, The absolute adjustment value is greater than or equal to 1 / 10 of the difference between the maximum and minimum absolute values ​​of the elevation information of all shape points.

4. The fuzzy processing method for geographic data elevation information according to claim 1, characterized in that, The fuzzy elevation information value of each reference point is determined based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, including: For each reference point, the absolute adjustment value and the longitudinal fine-tuning value corresponding to the reference point are added to the absolute value of its elevation information to obtain the fuzzy value of the elevation information of each reference point.

5. The method for fuzzy processing of geographic data elevation information according to any one of claims 1 to 4, characterized in that, After determining the fuzzy elevation information value of each following point based on the absolute adjustment value, the absolute value of the elevation information of each following point, and the longitudinal fine-tuning value of each following point, the process also includes: Obtain the interval path distance between two adjacent following points, determine the random fluctuation value range [-R / 2, R / 2] based on the interval path distance, and the ratio of R to the interval path distance does not exceed 1 / 1000; A random fluctuation value is added to the fuzzy elevation information of the following point, which is then used as the final fuzzy elevation information of the following point.

6. A fuzzy processing device for geographic data elevation information, characterized in that, include: The reference point selection module is used to select multiple shape points as reference points from the shape points of the elevation information to be marked, and the remaining shape points are follow points. The first fuzzy value determination module is used to determine the fuzzy value of the elevation information of each reference point based on the absolute adjustment value, the absolute value of the elevation information of each reference point, and the longitudinal fine-tuning value of each reference point, and to make the gradient of the elevation difference between two reference points conform to the error range allowed by the map accuracy. The range of the longitudinal fine-tuning value of the reference point is [-H / 2, H / 2], and the ratio of H to the minimum horizontal distance between two adjacent reference points does not exceed 1 / 1000. The fine-tuning value calculation module is used to calculate the longitudinal fine-tuning value of the follower point between two adjacent reference points based on the path distance between two adjacent reference points, the difference in longitudinal fine-tuning values ​​between two adjacent reference points, and the path distance from the follower point located between two adjacent reference points to one of the reference points. The second fuzzy value determination module is used to determine the fuzzy value of the elevation information of each following point based on the absolute adjustment value, the absolute value of the elevation information of each following point, and the longitudinal fine-tuning value of each following point, so that the gradient of the elevation difference between the two following points conforms to the error range allowed by the map accuracy. Wherein, the elevation difference gradient is the ratio of the elevation difference change between two shape points to the path distance between the two shape points; The fine-tuning value calculation module includes: The path distance determination module is used to determine the path distance between two adjacent reference points, and the path distance from the following point to one of the reference points between two adjacent reference points; The calculation module is used to calculate the longitudinal fine-tuning value of the follower point between two adjacent reference points based on the ratio of the path distance from the follower point to one of the reference points to the path distance between the two adjacent reference points, and the difference in longitudinal fine-tuning values ​​between the two adjacent reference points.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the fuzzy processing method for geographic data elevation information as described in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the fuzzy processing method for geographic data elevation information as described in any one of claims 1 to 5.

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