Line curve information checking method based on broken line

Abstract

The invention relates to a line curve information checking method based on broken lines, and belongs to the field of subway rail transit. According to the method, a broken line function set is established by adopting line curvature and gradient information existing in data sources I, II, III and IV, content comparison between different data sources is carried out based on included angles between adjacent curves and curve segment lengths, and a content comparison result is quantized by adopting a parameter of similarity; and according to the optimal overall similarity between the adjacent multiple sections of curves, carrying out position realignment on the data in the region between different data sources. According to the method, the data source 3 finally used by the equipment is taken as the center, and a new inter-equipment relative position and slope representation mode is adopted, so that the data source 3 can directly compare the equipment position information consistency with the data source 1, the data source 2 and the data source 4; the method is still suitable for the condition that the public starting point cannot be found due to the fact that the equipment name is not unique, the kilometer post is wrong and the section information is wrong.

Description

Technical Field

[0001] This invention belongs to the field of subway rail transit, specifically relating to a method for verifying line curve information based on broken lines. Background Technology

[0002] In the field of subway rail transit signaling systems, the consistency of information such as the gradient, curvature, transponders (if present), signals (if present), and switches (if present) of the line is verified by manually aligning a starting point and then checking each step according to the conversion relationship between the kilometer markers in the design drawings and the section information in the onboard electronic map data. Furthermore, the data is split into two parts: ground data is verified by manually measuring kilometer markers on the line, while the onboard electronic map data is verified by conducting consistency tests on simulated trains or real trains on the line to check the differences between the onboard and ground data.

[0003] There are four types of data sources in the existing technology: 1. Plan / longitudinal section drawings provided by the design unit (hereinafter referred to as Data Source 1); 2. Plan layout drawings modified by the equipment manufacturer (hereinafter referred to as Data Source 2); 3. Vehicle-mounted electronic map data files used by the vehicle-mounted equipment (hereinafter referred to as Data 3); 4. Relative position information of actual transponders (if present), signals (if present), and switches (if present) on the line (hereinafter referred to as Data Source 4). The location and verification of slope, curvature, transponder (if present), signal (if present), and switch (if present) position information, as well as slope and curvature information, between different data sources are required.

[0004] Because different types of data sources use different location marking methods—Data Source 1 uses only kilometer markers, Data Source 2 uses both kilometer markers and section markers, Data Source 3 uses only section markers, and Data Source 4 uses only section markers to re-mark the locations of physical equipment along the route—the verification of these commonly used data source types is centered on a plan design drawing that includes both kilometer markers and section markers. Based on kilometer marker information, the consistency of information content between Data Source 1 and Data Source 2 is manually verified. Based on section information, multiple versions of electronic map data in the same format are output through simulation testing or heterogeneous electronic map creation tools, and the consistency of the same information in Data Source 2 and Data Source 3 is verified by comparing file consistency. For equipment location information in Data Source 4, the consistency of location information is verified by manually measuring the relative distances between equipment and comparing them with the corresponding equipment information in Data Source 2.

[0005] The above method has the following drawbacks:

[0006] 1. Because the location information marking method used by the final data source three is different from that of data source one, the consistency of the data information between the two cannot be directly compared. When the information in data source two is incorrect, it is difficult to discover the error by simulation testing or by outputting multiple versions of electronic map data in the same format using heterogeneous electronic map production tools and then comparing the file consistency.

[0007] 2. Simulation testing methods are insufficient for comparing the consistency of information such as slope and curvature;

[0008] 3. On-site manual measurement can only be verified with data source two. Data source three, which is ultimately used by the equipment, cannot be compared with data source four, which is the actual location information of the equipment on site (in systems with active obstacle recognition function, camera equipment can be used to obtain the relative distance information between trackside equipment, thus forming data source four).

[0009] This invention centers on data source three, the final source used by the device, and employs a new method for representing the relative positions between devices. This method allows for direct comparison of device position information consistency with data sources one, two, and four, and is applicable to situations where different data sources represent different regions with only partial overlap. Furthermore, the consistency comparison method in this invention is independent of global kilometer markers and device names, eliminating the need to select a common starting point for alignment among the four data sources. It remains applicable even in cases where device names are not unique, kilometer markers are incorrect, or segment information is incorrect. Summary of the Invention

[0010] (a) Technical problems to be solved

[0011] The technical problem to be solved by the present invention is how to provide a method for verifying line curve information based on polylines, so as to solve the above-mentioned problems existing in the verification of existing data sources.

[0012] (II) Technical Solution

[0013] To address the aforementioned technical problems, this invention proposes a method for verifying track curve information based on polylines. This method includes: realigning the positions of multiple data sources and comparing and verifying track information and trackside equipment information between different data sources.

[0014] S1. Realigning the positions of multiple data sources.

[0015] S11. Select data parameters for each data source, only selecting information content that will be involved in the verification; each data source includes: Data Source 1, Data Source 2, Data Source 3, and Data Source 4;

[0016] S12. Classify the track into two main categories: track curves and trackside equipment, and establish corresponding sets of polyline functions for each category;

[0017] S13. Calculation of the similarity of broken lines between different data sources;

[0018] S14. Node shifting operations are performed between multiple data sources based on overall similarity to find the optimal overall similarity among them. The nodes in the same group of data sources corresponding to the optimal overall similarity are the points with consistent positions.

[0019] S2. Comparison and verification of track information and trackside equipment information from different data sources.

[0020] A single line is split into main branch lines and other branch lines. A main branch curve polyline function is established for the main branch lines. The similarity of the main branch curves between two data sources is compared to find the optimal overall similarity and position alignment. Then, the information in the main branch curves is compared. Based on the two main branch lines that have been aligned, the position is realigned sequentially using the curves of each split line. The information in the two realigned curves is compared sequentially.

[0021] (III) Beneficial Effects

[0022] This invention proposes a method for verifying line curve information based on polylines. Compared with the current method centered on data source two and based on kilometer marker positions or logical segment offsets, this invention has the following advantages:

[0023] 1. Centered on data source three, which is ultimately used by the equipment, a new method of representing the relative position and slope between equipment is adopted, so that data source three can be directly compared with data sources one, two, and four to ensure consistency of equipment position information;

[0024] 2. The information comparison method in this invention is independent of global kilometer markers and device names, and there is no need to select a common starting point for alignment from the four data sources. It is still applicable even when there are situations where the device name is not unique, the kilometer marker is incorrect, or the section information is incorrect, and a common starting point cannot be found.

[0025] 3. The comparison information of the equipment is only related to the relative distance. Different data sources can use different distance representation methods to represent the location. It is still applicable even if there is no kilometer marker and logical segment location conversion information table or the conversion information is incorrect.

[0026] 4. When all data sources adopt a unified method for representing location and device information, and this method can perform bidirectional conversion between different data sources without relying on other information, verification between different data sources can also be completed. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of a broken line containing three points A1, A2, and A3 in this invention;

[0028] Figure 2This is a schematic diagram illustrating the process of pairwise comparison of single curves between different data sources in this invention. Detailed Implementation

[0029] To make the objectives, contents, and advantages of the present invention clearer, the specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0030] This invention enables automatic marking of differences in slope, curvature, transponder (if present), signal (if present), and turnout (if present) information among four types of data sources without relying on the alignment of absolute starting positions (including cases where some data sources only have data in certain areas), assisting manual verification and correction of data consistency.

[0031] This invention centers on data source three, the final source used by the device, and employs a new method for representing the relative positions between devices. This method allows for direct comparison of device position information consistency with data sources one, two, and four, and is applicable to situations where different data sources represent different regions with only partial overlap. Furthermore, the consistency comparison method in this invention is independent of global kilometer markers and device names, eliminating the need to select a common starting point for alignment among the four data sources. It remains applicable even in cases where device names are not unique, kilometer markers are incorrect, or segment information is incorrect.

[0032] This invention establishes a set of broken line functions using the line curvature and slope information that exist in data sources one, two, three, and four. It compares the content between different data sources based on the angle between adjacent curves and the length of the curve segments. It uses the similarity parameter to quantify the content comparison results and realigns the data in this region between different data sources according to the optimal overall similarity between adjacent curve segments.

[0033] This invention provides a method for verifying track curve information based on polylines, including two aspects: realignment of positions among multiple data sources and comparison and verification of track information and trackside equipment information among different data sources.

[0034] S1. Realigning the positions of multiple data sources.

[0035] Not all information types are the same across different data sources, and information verification can only verify the parts common to at least two data sources. Therefore, realignment involves the following steps.

[0036] Step S11: Select data parameters for each data source, selecting only the information content involved in the verification.

[0037] Step S12: Classify the track into two main categories: track curves and trackside equipment, and establish corresponding polyline function sets for each category;

[0038] Step S13: Calculation of the similarity of broken lines between different data sources;

[0039] Step S14: Perform node shifting operations among multiple data sources based on overall similarity to find the optimal overall similarity among them. The nodes in the same group of data sources corresponding to the optimal overall similarity are the points with consistent positions.

[0040] 1) Selection of data parameters from different data sources

[0041] Data selection among data sources adopts the method of extracting information common to at least two data sources. The data parameters selected from each data source are as follows.

[0042] (1) Data source one

[0043] The information shared by data source 1 and other data sources is concentrated in the left / right track longitudinal profile and the signal equipment layout diagram. Track curve information is mainly extracted from the left / right track longitudinal profile, and the relative positional information of trackside equipment is mainly extracted from the signal equipment layout diagram.

[0044] The information on the track curves includes: vertical curves, track surface design gradient, and track mileage.

[0045] The relative positional information of trackside equipment includes: signal name, turnout name, turnout name, and the order in which these devices are located.

[0046] (2) Data source two

[0047] The information from data source two is concentrated in the signal layout diagram. The information to be obtained includes: curvature, gradient, mileage markers, signal names, turnout names, track section names, transponder names, and the order of these elements.

[0048] (3) Data source three

[0049] Data source three extracts information from vehicle-mounted electronic map data files that conform to interoperability standards and from a table mapping device names and numbers.

[0050] The information required for the vehicle-mounted electronic map data file includes: gradient, curvature, a list of track section numbers and their associated transponder numbers, signal numbers, and turnout numbers.

[0051] The equipment name and number correspondence table needs to obtain the correspondence between the names and numbers of equipment such as track sections, transponders, signals, and switches.

[0052] (4) Data source four

[0053] Data source four uses the relative distance information between trackside equipment calculated by the vehicle-mounted speed sensor and the position information read by the transponder.

[0054] The relative distance information between trackside equipment is obtained in the following way: when the vehicle is running, it identifies transponders, signals, and switches (or turnouts) and records the distance between the current trackside equipment and the previous trackside equipment.

[0055] The location information read by the transponder is obtained by intercepting the communication packets between the onboard automatic train protection system (ATP) and the obstacle detection equipment.

[0056] 2) Establishment of the set of polyline functions corresponding to track curves and trackside equipment

[0057] Based on information type, information related to gradient and curvature is reflected in the set of broken line functions corresponding to the track curves, while information about transponders, signals, and switches is reflected in the set of broken line functions corresponding to trackside equipment. Information such as kilometer markers or track section lengths will be reflected as relative lengths in all sets.

[0058] To unify the direction of line calculations across different data sources, the content corresponding to the left line is made consistent with the content corresponding to the upward direction, and the content corresponding to the right line is made consistent with the content corresponding to the downward direction.

[0059] Because track lines often branch into multiple branches at turnouts (both forward and lateral), curve creation requires retaining the forward branch within the main branch and removing the lateral branch as a separate branch. The turnout's location and equipment information serve as the starting point for these other branch lines and are also present in the curve information of the main branch. For the initial positioning of a single track curve, the main branch with the most nodes after splitting is used for initial alignment. Even if there are no changes in gradient or curvature, new nodes need to be added at the intersections of the main branch with other branch lines.

[0060] (1) Establishment of the broken line function for a single line curve

[0061] The route curves are created separately for the left and right lines (or up and down lines), and the multiple branch lines are also created separately. Slope and curvature are also used to create separate curves. Moving from left to right, each point where the slope or curvature changes is abstracted as a node (the start and end points of the route are the default two nodes). The distance between two nodes is the length of the polyline, and the slope or curvature value is converted into the polyline slope. Taking slope information as an example, the process of converting the slope from data sources one, two, and three into a curve is as follows:

[0062] Assume a route is selected with 3 points where the gradient changes, using the starting point as the origin of the coordinate system. Point 1 (denoted as A1, gradient K1 degrees, kilometer standard deviation of point 1 from point 2 is L1), point 2 (denoted as A2, gradient K2 degrees, kilometer standard deviation of point 2 from point 3 is L2), and point 3 (denoted as A3) are the ending points. The corresponding gradient and kilometer standard deviation values ​​are not required in the calculation; all parameters related to the ending points in the formula use fixed, specific values.

[0063] The line graph A1A2A3 is represented as:

[0064]

[0065] The general formula for converting to multiple points:

[0066]

[0067] Where x≥0, n represents the total number of nodes. In this example, i=[1,3], n=3, x i+1 =x i +L i L i For A i Point to A i+1 The distance between points (km standard deviation or section offset), a i This represents the slope of the broken line. Specifically, A1 is point 1, corresponding to i=1. Since point 1 is the starting point and serves as the origin of the coordinate system, x1=0, and a1 is the slope calculated based on K1. A2 is point 2, corresponding to i=2, i.e., x2=x1+L1, and a2 is the slope calculated based on K2. A3 is point 3, corresponding to i=3, i.e., x3=x2+L2, and a3 corresponds to the ending point, using a fixed value of 1 in the calculation. For example... Figure 1 As shown.

[0068] (2) Establishment of trackside equipment information breakpoints on a single line

[0069] The method for establishing the polyline information for trackside equipment is similar to that for establishing the track curve information in the previous section. The track curves are established separately for the left and right lines (or up and down lines), and curves are established separately for the multiple branch lines after splitting. From left to right, each trackside device is abstracted as a point, and the distance between two points is the length L of the polyline. i Different types of trackside equipment use natural numbers such as 1, 2, 3, etc., as the slope 'a' of the broken line. i Different natural numbers represent different types of equipment, while the same natural number represents the same type of equipment. That is, the same type of trackside equipment uses the same slope of the broken line. The general expression formula is the same as that in equation (1), except that a i and L i Although the meanings differ, the calculation methods described below are consistent.

[0070] 3) Calculation of similarity between different data sources using broken lines

[0071] To calculate similarity, we first need to select feature quantities. Based on the characteristics of equation (1), we select the slope 'a' in the function. i The distance L between adjacent points i (i.e. L) i =x i+1 -x i The two parameters are eigenvalues.

[0072] Based on the characteristic that slope is more concerned with directionality, cosine similarity is used to calculate slope similarity.

[0073]

[0074] In equation (2), the parameters marked by the superscripts j and k represent data from different data sources, i represents the index of the point, n represents the total number (when the total number of data from different data sources is inconsistent, the smallest total number value among the data sources is selected as the total number n for comparison between different data sources), and S1 represents the first similarity.

[0075] S1, calculated using cosine similarity, has a value range of [-1, 1], with a larger value indicating a higher similarity.

[0076] Based on the characteristic that distance between adjacent points is more concerned with length, Euclidean distance is used to calculate distance similarity. Since the result of Euclidean distance calculation is in the range of [0, +∞], and the smaller the value, the higher the similarity, the calculation formula is optimized to limit the value of the calculation result to a fixed range.

[0077]

[0078] In equation (3), the meanings of j, k, i, and n are the same as in equation (2). This represents the i-th node. and The maximum value in the range is S2, which represents the second similarity. S2 is calculated using Euclidean distance and ranges from [0,1]. The smaller the value, the higher the similarity.

[0079] 4) Calculation of optimal overall similarity among multiple data sources and determination of location consistency points

[0080] Alignment of multiple data sources is performed by pairwise comparison and similarity calculation.

[0081] When the positions of different data sources are perfectly aligned, if the content of the two data sources being compared is correct, the comparison will be consistent, i.e., the similarity S1 = 1 and S2 = 0. If one or both of the content of the two data sources being compared contain some errors, the comparison will be inconsistent. The greater the difference, the smaller S1 and the larger S2.

[0082] The overall similarity S is calculated as follows:

[0083]

[0084] In equation (4), S is the total similarity, which ranges from [0, +∞]. The smaller the value, the higher the total similarity. When either S1 = 1 or S2 = 0 occurs, the result will be S = 0. The higher the similarity, the closer the values ​​of (1-S1) and S2 will be to zero. B1, B2, B3, and B4 are the adjustment parameters for the weights of S1 and S2. When the adjustment factor is up to 10 times (the adjustment factor must be an integer, and the corresponding value is selected according to the specific scenario), the range of the four adjustment parameters is [1, 10].

[0085] When calculating the overall similarity of a curve, the value of slope or curvature (S1) is more important than the value of relative distance between points of change (S2). In this case, the values ​​of B2 and B3 will be increased, while the values ​​of B1 and B4 will be decreased. Since the range of (1-S1) and S2 is [0,1], when they are 0 or 1, B2 and B4 have no moderating effect. B1 and B3 have no moderating effect on the highest similarity value of 0, but they amplify the value of 1 corresponding to the greatest difference. When (1-S1) and S2 are decimals, increasing the exponents B2 and B4 will make the total value smaller and closer to 0, thus increasing the similarity weight. Conversely, if the exponents decrease to the minimum value of 1, they have no effect on increasing or decreasing the original values ​​of (1-S1) and S2. B1 and B3 are parameters for the product method. The logic for increasing / decreasing them is different from that of B2 and B4 (when (1-S1) and S2 are decimals). If B1 and B3 are increased, the final total value will be larger and further away from 0, and the total similarity value S will be smaller. Conversely, if B1 and B3 are decreased to the minimum value of 1, they will have no effect on increasing / decreasing the original values ​​of (1-S1) and S2.

[0086] When calculating the total similarity of the trackside equipment information polyline, since different equipment types have different slope values ​​and equipment of the same type has the same slope value, the importance of the slope S1 is less than that of the distance between equipment S2. In this case, the values ​​of B2 and B3 will be reduced, and the values ​​of B1 and B4 will be increased.

[0087] To calculate the curve f of the two lines 1 (x) and f 2 Taking (x) as an example, the calculation process is explained (superscripts 1 and 2 represent curve 1 and curve 2). Based on f...1 (x) and f 2 (x) The size of the number of nodes n, choose the curve with the smaller value of n (let's assume it's f). 2 (x)), fixed use The point (the subscript value indicates the node number on the curve from left to right) is the curve f. 2 The starting point of (x) is respectively with the curve f 1 (x) When a point is used as the starting point, the total similarity is calculated according to equation (4). (Superscript 12 indicates the result of comparing curve 1 and curve 2), select the smallest value from the list. As a temporary optimal overall similarity, considering the possibility of two curves representing different regions with no common information, a judgment threshold needs to be set. Since the value range of S is [0, +∞], the higher the similarity, the closer the values ​​of (1-S1) and S2 will be to zero. When S≥1, both are judged as extremely different, so the effective judgment range of S becomes [0,1]. Therefore, a percentage-based judgment method is adopted, and a threshold T is set. 12 ,but When the optimal overall similarity is found, it is determined that... Time corresponding and A point is a point whose location is consistent across two data sources.

[0088] S2. Comparison and verification of track information and trackside equipment information from different data sources.

[0089] A single line is split into main branch lines and other branch lines. A main branch curve polyline function is established for the main branch lines. The similarity of the main branch curves between two data sources is compared to find the optimal overall similarity and position alignment. Then, the information in the main branch curves is compared. Based on the two main branch lines that have been aligned, the position is realigned sequentially using the curves of each split line. The information in the two realigned curves is compared sequentially. The parameters of equation (1) are compared sequentially for each line. i and x i The parameter n is the minimum number of nodes between the two curves.

[0090] The specific process is as follows:

[0091] The positioning of a single line curve is initially aligned using the main branch line with the most nodes after splitting. After the main branch line completes its repositioning, the information of the main branch curves is compared.

[0092] Other branch curves that are split are established as independent line functions in sequence. Since the starting point of each branch line exists in other lines, we first compare the two main branch lines that have been repositioned between the two data sources, and then find other branch lines whose starting points exist in the main branch lines. Based on the intersection points that have been repositioned on the main branch lines, we realize the position alignment of the starting points of the two other branch lines in different data sources. The subsequent nodes on other branch lines correspond to each other in sequence according to the node number. After the repositioning of the secondary branch curves is completed, the information of the secondary branch curves is compared.

[0093] Then, other branches that are not yet aligned can be found in the secondary branch lines where the starting point can be found, and the indirect alignment of the tertiary branch lines is completed. Then, the information of the tertiary branch curves is compared.

[0094] This process is repeated to compare and verify all line information and trackside equipment information that have common parts across different data sources.

[0095] Key points and areas to be protected in this invention:

[0096] 1. Conversion methods between slope, curvature, trackside equipment related information and polyline functions;

[0097] 2. The calculation method for the total similarity between two curves and the determination of the optimal overall similarity;

[0098] 3. A method for comparing and verifying track information and trackside equipment information from different data sources based on the sequential realignment of multiple branch lines.

[0099] Compared with the current method that centers on data source two and is based on kilometer marker positions or logical segment offsets, the present invention has the following advantages:

[0100] 1. Centered on data source three, which is ultimately used by the equipment, a new method of representing the relative position and slope between equipment is adopted, so that data source three can be directly compared with data sources one, two, and four to ensure consistency of equipment position information;

[0101] 2. The information comparison method in this invention is independent of global kilometer markers and device names, and there is no need to select a common starting point for alignment from the four data sources. It is still applicable even when there are situations where the device name is not unique, the kilometer marker is incorrect, or the section information is incorrect, and a common starting point cannot be found.

[0102] 3. The comparison information of the equipment is only related to the relative distance. Different data sources can use different distance representation methods to represent the location. It is still applicable even if there is no kilometer marker and logical segment location conversion information table or the conversion information is incorrect.

[0103] 4. When all data sources adopt a unified method for representing location and device information, and this method can perform bidirectional conversion between different data sources without relying on other information, verification between different data sources can also be completed.

[0104] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for verifying line curve information based on polylines, characterized in that, This method includes: realigning the positions between multiple data sources and comparing and verifying the line information and trackside equipment information between different data sources; S1. Realigning the positions of multiple data sources. S11. Select data parameters for each data source, only selecting information content that will be involved in the verification; each data source includes: Data Source 1, Data Source 2, Data Source 3, and Data Source 4; S12. Classify the track into two main categories: track curves and trackside equipment, and establish corresponding sets of polyline functions for each category; S13. Calculation of the similarity of broken lines between different data sources; S14. Node shifting operations are performed between multiple data sources based on overall similarity to find the optimal overall similarity among them. The nodes in the same group of data sources corresponding to the optimal overall similarity are the points with consistent positions. S2. Comparison and verification of track information and trackside equipment information from different data sources. A single line is split into main branch lines and other branch lines. A main branch curve polyline function is established for the main branch lines. The similarity of the main branch curves between two data sources is compared to find the optimal overall similarity and position alignment. Then, the information in the main branch curves is compared. Based on the two main branch lines that have been aligned, the position is realigned sequentially using the curves of each split line. The information in the two realigned curves is compared sequentially.

2. The method for verifying line curve information based on polylines as described in claim 1, characterized in that, In S11, the information from data source one is concentrated in the left / right track longitudinal profile and the signal equipment plan layout diagram. The information obtained includes: track curve information and the relative positional relationship information of the trackside equipment; the track curve information includes: vertical curve, track surface design gradient and mileage; the relative positional relationship information of the trackside equipment includes: signal name, turnout name, turnout name and the order of these devices. The information from data source two is concentrated in the signal layout diagram. The information obtained includes: curvature, gradient, mileage markers, signal names, turnout names, track section names, transponder names, and the order of these elements. Data source three extracts information from vehicle-mounted electronic map data files that conform to interoperability standards and from the device name and number correspondence table. The information to be obtained from the vehicle-mounted electronic map data files includes: gradient, curvature, a list of track section numbers and their associated transponder numbers, signal numbers, and turnout numbers. The device name and number correspondence table needs to obtain the correspondence between the names and numbers of track sections, transponders, signals, and turnouts. Data source four uses the relative distance information between trackside equipment calculated by the vehicle-mounted speed sensor and the position information read by the transponder; the relative distance information between trackside equipment is obtained in the following ways: when the vehicle is running, it identifies the transponder, signal, and turnout and records the distance between the current trackside equipment and the previous trackside equipment; the position information read by the transponder is obtained by intercepting the communication information packets between the on-board automatic train protection system and the obstacle detection equipment.

3. The method for verifying line curve information based on polylines as described in claim 1, characterized in that, In S12, according to the information type, information related to gradient and curvature is reflected in the set of broken line functions corresponding to the track curve, and the information of equipment such as transponders, signals, and switches is reflected in the set of broken line functions corresponding to the trackside equipment; the kilometer marker or track section length information will be reflected as a relative length in all sets.

4. The method for verifying line curve information based on polylines as described in claim 1, characterized in that, In S12, since the track line has multiple branches at the turnout, the curve needs to be established by keeping the forward line in the main branch line and removing the lateral line from the main branch line to form another branch line. The position information and equipment information of the turnout serve as the starting point of the other branch line and also exist in the curve information of the main branch line. The positioning of a single line curve is based on the main branch line with the most nodes after splitting for the first position alignment. Even if there is no change in slope or curvature, the intersection of the main branch line and other branch lines needs to be newly added with corresponding nodes.

5. The method for verifying line curve information based on polylines as described in claim 1, characterized in that, In step S12, a set of polyline functions corresponding to a single line curve is established, specifically including: The system uses left and right lines to create curves, and multiple branch lines to create curves separately. It also uses slope and curvature to create curves separately. From left to right, each point where the slope or curvature changes is encountered is abstracted as a node. The starting point and ending point of the line are the two default nodes. The distance between the two nodes is the length of the polyline. The slope or curvature value is converted into the slope of the polyline. Suppose we select a route with 3 points where the gradient changes. We take the starting point as the origin of the coordinate system, which are point 1, point 2 and point 3. Point 1 is denoted as A1, with a gradient of K1 degrees. The kilometer standard deviation of point 1 from point 2 is L1. Point 2 is denoted as A2, with a gradient of K2 degrees. The kilometer standard deviation of point 2 from point 3 is L2. Point 3 is denoted as A3, which is the termination point. All parameters related to the termination point in the formula use fixed special values ​​for calculation. The line graph A1A2A3 is represented as: The general formula for converting to multiple points: Where x≥0, n represents the total number of nodes, x i+1 =x i +L i L i For A i Point to A i+1 The distance between points, i.e., kilometer standard deviation or section offset, a i The slope of the broken line.

6. The method for verifying line curve information based on polylines as described in claim 5, characterized in that, In step S12, establishing a polyline of trackside equipment information for a single line specifically includes: establishing line curves for the left and right lines respectively, establishing curves for the multiple branch lines after splitting, and abstracting each trackside device encountered from left to right as a point. The distance between two points is the length L of the polyline. i Different types of trackside equipment use natural numbers as the slope 'a' of the broken line. i Different natural numbers represent different types of equipment, while the same natural number represents the same type of equipment. That is, the same type of trackside equipment uses the same slope of the broken line.

7. The method for verifying line curve information based on polylines as described in claim 5 or 6, characterized in that, S13 includes: When calculating similarity, the slope 'a' in the function is selected. i The distance L between adjacent points i The two parameters are eigenvalues; Cosine similarity is used to calculate slope similarity; In equation (2), the parameters marked by superscript j and k represent data from different data sources, i represents the index of the point, n represents the total number, and when the total number of data from different data sources is inconsistent, the smallest total number value among the data sources is selected as the total number n for comparison between different data sources. S1 represents the first similarity. Euclidean distance is used to calculate distance similarity. In equation (3), This represents the i-th node. and The maximum value in S1, S2 represents the second similarity.

8. The method for verifying line curve information based on polylines as described in claim 7, characterized in that, S14 includes: The overall similarity S is calculated as follows: In equation (4), S is the total similarity, which ranges from [0, +∞]. The smaller the value, the higher the total similarity. When either S1 = 1 or S2 = 0 occurs, the result will be S = 0. The higher the similarity, the closer the values ​​of (1-S1) and S2 will be to zero. B1, B2, B3, and B4 are the adjustment parameters for the weights of S1 and S2. When calculating the curves f of two lines 1 (x) and f 2 When calculating the overall similarity of (x), the superscripts 1 and 2 represent curve 1 and curve 2; according to f 1 (x) and f 2 (x) The size of the number of nodes n, choose the curve with the smaller value of n, let's say it's f. 2 (x), fixed usage Point is curve f 2 The starting point of (x) is respectively with the curve f 1 (x) When a point is used as the starting point, the total similarity is calculated according to equation (4). Select the smallest value in the list As a temporary optimal overall similarity, a threshold T is set. 12 ,but When the optimal overall similarity is found, it is determined that... Time corresponding and A point is a point whose location is consistent across two data sources.

9. The method for verifying line curve information based on polylines as described in claim 8, characterized in that, In S14, when calculating the total similarity of the track curves, the importance of S1 (responding to the slope or curvature value) is greater than that of S2 (responding to the relative distance between change points). In this case, the values ​​of B2 and B3 will be increased, and the values ​​of B1 and B4 will be decreased. When calculating the total similarity of the trackside equipment information polyline, since different equipment types are fixed with different slope values, and equipment of the same type has the same slope value, the importance of S1 (responding to the slope) is less than that of S2 (responding to the distance between equipment). In this case, the values ​​of B2 and B3 will be decreased, and the values ​​of B1 and B4 will be increased.

10. The method for verifying line curve information based on polylines as described in claim 1, characterized in that, S2 includes: The positioning of a single line curve is initially aligned using the main branch line with the most nodes after splitting. After the main branch line completes its repositioning, the information of the main branch curves is compared. Other branch curves that are split are established as independent polyline functions in sequence. Since the starting point of each branch line exists in other lines, we first compare the two main branch lines that have been repositioned between the two data sources, and then find other branch lines whose starting points exist in the main branch lines. Based on the intersection points that have been repositioned on the main branch lines, we realize the position alignment of the starting points of the two other branch lines in different data sources. The subsequent nodes on other branch lines correspond to each other in sequence according to the node number. After the repositioning of the secondary branch curves is completed, the information of the secondary branch curves is compared. Then, find other unaligned branches that can find the starting point of the secondary branch line that has been indirectly aligned, and then complete the indirect alignment of the tertiary branch line. After that, compare the information of the tertiary branch curves. This process is repeated to compare and verify all line information and trackside equipment information that have common parts across different data sources.

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