Line multi-mileage system accurate conversion system and method based on unified reference standard

Abstract

The invention provides a line multi-mileage system accurate conversion system based on a unified reference standard. The system comprises a line standard and data modeling module, a mileage conversion request processing module, a segmented feature driven conversion calculation module and a conversion result verification and output module. According to the method, a unified and accurate benchmark with verifiable continuity is established, the data consistency and comparability are remarkably improved, an enhanced feature classification data model is adopted, complex relations are accurately expressed and actively processed, and accurate, automatic and type-driven processing of broken links and jumps is achieved. The invention further provides a line multi-mileage system accurate conversion method based on the unified reference datum.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of rail transit and railway engineering information management, and particularly relates to a line multi-mileage system accurate conversion system and method based on a unified reference datum. BACKGROUND

[0002] As a key transportation infrastructure in modern society, the safe, punctual and efficient operation and management of rail transit and railway network largely depends on the accurate and real-time grasp and application of physical location information of the line. As a core parameter describing the longitudinal distance of any point on the rail line relative to the starting point or a specific reference point of the line, the line mileage constitutes the basis of line spatial information and is used in many core business links such as train operation control system (such as CBTC based on communication, CTCS in China), train automatic driving (ATO), operation scheduling plan, infrastructure state monitoring and maintenance decision, fixed asset life cycle management, emergency positioning and response, etc.

[0003] However, in the long life cycle of railway and rail transit lines, from planning and design, construction, to long-term operation and continuous maintenance and upgrading, various factors cause different mileage systems with different definitions and reference points to coexist on the same physical rail line. These factors include but are not limited to: historical legacy problems, differences in technical specifications adopted in different construction or reconstruction stages, line repositioning or extension, different mileage reference points or measurement methods set by multiple departments based on their respective management needs, etc. Therefore, common mileage types such as design mileage, construction mileage, operation mileage (field mileage, which may have long-short chain adjustment), signal system mileage, etc. often exist simultaneously and have complex and nonlinear relationships between each other. These mileage systems not only have different starting points and ending points, but also may have inconsistent mileage value trends, and generally have complex situations such as mileage jump (long-short chain) or mileage interruption (broken chain).

[0004] In the prior art, although the linear reference system (LRS) technology has been developed in the field of geographic information system (GIS) and some international standards and commercial implementations have been formed, providing a certain theoretical basis and tool support for managing geographic features with linear characteristics. At the same time, some patent documents also involve mileage conversion or calibration. However, these existing solutions still face significant challenges when facing the complex and discontinuous problems of multiple mileages coexisting in the railway field:

[0005] The reference benchmark lacks precision and inherent continuity: The reference benchmark or baseline of the traditional LRS has various establishment methods, which may rely on two-dimensional drawings, existing line diagrams, or measurement data with varying precision, and may not guarantee full-line, verifiable geometric continuity and high precision from the source, which poses inherent difficulties for subsequent accurate conversion.

[0006] Limitations of data models in expressing and processing complex discontinuities: Traditional LRS models or simple mileage correspondence tables often lack sufficient expression capability when facing various mileage systems and their complex nonlinear relationships, numerous mileage jump points, and broken link sections. More importantly, they usually lack a detailed, standardized discontinuity type classification mechanism and directly associated, automated, and targeted processing logic, resulting in a high degree of reliance on "manual interpretation, empirical rules, or simplified approximation processing" when dealing with these complex situations, making it difficult to ensure the accuracy and automation of the conversion results. For example, some systems may only identify "abnormalities" in general, rather than accurately classify and automatically invoke specific processing algorithms.

[0007] Precision and automation bottleneck in broken link and jump processing: Existing methods often result in precision loss and difficulty in achieving fully automated and highly reliable conversion when dealing with mileage discontinuity (long and short chain, broken link) areas due to the lack of a unified high-precision continuous reference and refined processing model. For example, GRASS GIS LRS can handle "mileage equations" through specific data structures, but its processing approach differs from the mapping based on a unified high-precision geometric reference proposed in this invention, and it may not cover all types of mileage discontinuity and provide flexible estimation options based on a unified continuous mileage (UCM).

[0008] High maintenance cost for consistency between multiple mileage systems: When the line changes or the mileage system updates, manually maintaining the complex correspondence between systems is prone to errors and inefficient.

[0009] Conversion efficiency and real-time performance difficult to meet specific needs: In scenarios such as real-time accurate positioning of trains, mileage conversion operations need to be highly efficient. If complex real-time calculations or extensive manual intervention are relied upon, it will be difficult to meet performance requirements.

[0010] In summary, there is an urgent need to develop an innovative technical solution, which should be able to: first, establish a unified line mileage reference datum generated by a specific high-precision three-dimensional space data processing method, with verifiable geometric continuity and high-precision characteristics; second, design a special data model that can accurately express the complex correspondence between various mileage systems and the unified datum (especially explicit classification and storage of various discontinuous features); third, provide a set of mileage conversion methods and systems that can automatically call corresponding processing rules according to the accurate classification of discontinuous features, thereby achieving accurate, efficient, and automated processing of various complex situations. This solution aims to effectively overcome the limitations of existing technologies and meet the growing demand for line space information management in modern rail transit and railway systems. SUMMARY

[0011] According to the provided line multi-mileage system accurate conversion system based on a unified reference datum,

[0012] The purpose of the present application is to provide a line multi-mileage system accurate conversion system based on a unified reference datum, characterized in that the system comprises: a line reference and data modeling module, a mileage conversion request processing module, a segmented feature driven conversion calculation module, and a conversion result verification and output module. The line reference and data modeling module constructs a data model covering the entire line based on a unified continuous mileage datum. The mileage conversion request processing module is configured to receive and process externally initiated mileage conversion requests. The segmented feature driven conversion calculation module is configured to convert the mileage conversion request. The conversion result verification and output module verifies and outputs the conversion results of the segmented feature driven conversion calculation module.

[0013] According to the provided line multi-mileage system accurate conversion system based on a unified reference datum, the unified continuous mileage datum is based on line and three-dimensional center line measurement data in a three-dimensional coordinate system and is obtained through geometric processing and topological correction algorithms.

[0014] According to the provided line multi-mileage system accurate conversion system based on a unified reference datum, the line reference and data modeling module automatically or with human assistance segments the line under the unified continuous mileage datum, forms line segments with continuous or mileage features, and fills in the segment information of the line segments.

[0015] According to the provided line multi-mileage system accurate conversion system based on a unified reference datum, the segment information includes:

[0016] a. A unique line segment identifier;

[0017] b. The identifier of the line to which it belongs;

[0018] c. Mileage value of line section boundary point;

[0019] d. Mileage value of line section of other mileage type on the same physical boundary point;

[0020] e. Mileage change trend;

[0021] f. Line section type identifier;

[0022] g. Local conversion function identifier or parameter set describing the nonlinear conversion relationship.

[0023] According to the provided line multi-mileage system accurate conversion system based on a unified reference, the line reference and data modeling module constructs a data model with line sections as the basic unit and generates a line section database.

[0024] According to the provided line multi-mileage system accurate conversion system based on a unified reference, the mileage conversion request processing module searches in the line section database according to the mileage conversion request to determine one or more line sections containing the mileage value to be converted.

[0025] According to the provided line multi-mileage system accurate conversion system based on a unified reference, the segmented feature driven conversion calculation module selects and applies a conversion strategy according to the information of the line section where the mileage to be converted is located.

[0026] According to the provided line multi-mileage system accurate conversion system based on a unified reference, the verification of the conversion result verification and output module includes boundary check, continuity check, and verification according to the section type identifier whether state identifier or warning information needs to be attached in the output result.

[0027] According to the provided line multi-mileage system accurate conversion system based on a unified reference, the output of the conversion result verification and output module includes the converted target mileage value, whether the conversion is successful, whether the conversion result is located at or adjacent to the broken link area or the mileage jump point, the conversion accuracy level, etc.

[0028] The purpose of the present application is also to provide a line multi-mileage system accurate conversion method based on a unified reference, characterized by comprising the following steps:

[0029] S1. The data model covering the entire line constructed by the line reference and data modeling module based on a unified continuous mileage reference;

[0030] S2. The line reference and data modeling module generates a line section database;

[0031] S3. The mileage conversion request processing module receives the conversion request and locates the line section on which the mileage to be converted is located in the line section database;

[0032] S4. The segmented feature driven conversion calculation module automatically selects a conversion strategy and obtains a target mileage value according to the information of the line section on which the mileage to be converted is located;

[0033] S5. The conversion result verification and output module verifies the validity of the result and outputs the final result. BRIEF DESCRIPTION OF DRAWINGS

[0034] Figure 1 is a flowchart of a line multi-mileage system accurate conversion method based on a unified reference provided by an embodiment of the application.

[0035] Figure 2 is a functional architecture diagram of a line multi-mileage system accurate conversion method based on a unified reference provided by an embodiment of the application. DETAILED DESCRIPTION

[0036] In order to make the purposes, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be described in more detail below with reference to the drawings in the embodiments of the present application. In the drawings, the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions. The described embodiments are part of the embodiments of the present application, not all embodiments. The embodiments described below by reference to the drawings are exemplary and are intended to explain the present application, and cannot be understood as limiting the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0037] An accurate conversion system of a line multi-mileage system based on a unified reference according to an embodiment of the application comprises: a line reference and data modeling module, a mileage conversion request processing module, a segmented feature driven conversion calculation module, and a conversion result verification and output module.

[0038] The line reference and data modeling module is based on high-precision line three-dimensional center line measurement data (for example, centimeter-level precision point cloud data or trajectory data obtained by 360° laser section instrument scanning technology) in a precise three-dimensional coordinate system, and calculates through specific geometric processing and topological correction algorithm to establish a verifiable unified continuous mileage (UCM) reference covering the entire line.

[0039] The specific geometry processing and topology correction algorithm includes: 1. Topology correction of three-dimensional center line using graph-based analysis to identify and correct incorrect node connection degree at locations such as turnouts and intersections; 2. Mathematical verification of the generated unified continuous mileage to ensure that the mileage value is strictly monotonic within the entire line range.

[0040] The mathematical verification here is guaranteed by an explicit multi-step algorithm:

[0041] 1. Data injection and filtering: inject high-precision three-dimensional point cloud data and apply specific filters (such as statistical outlier removal) to eliminate noise.

[0042] 2. Center line fitting: use algorithms such as moving window-based principal component analysis to derive the initial three-dimensional center line.

[0043] 3. Topology correction: use a graph-based analysis algorithm to abstract the line network (including turnouts, intersections, etc.) into a graph structure. This algorithm automatically detects and corrects topology errors.

[0044] 4. Monotonicity verification: after UCM calculation is completed, a final traversal algorithm will travel along the corrected center line geometry to check and mathematically prove that the calculated mileage value is strictly monotonically increasing within the entire domain. Any section that violates monotonicity will be marked and corrected,

[0045] Thus fundamentally guaranteeing the absolute continuity and reliability of the UCM benchmark.

[0046] In addition, the line benchmark and data modeling module can also automatically or with minimal manual assistance, segment the line under the unified continuous mileage benchmark based on the input line basic data (such as high-precision survey data, completed design drawings, signal system layout drawings, operational mileage change records, etc.) and a set of pre-set segmentation rules (for example, forced segmentation at bridge, tunnel start and end points, major turnout areas, station center points, known milestone locations, signal equipment key points, and all known mileage jump or interruption points, etc.), segment the continuous or mileage-characteristic line to form line sections, and fill in the section information of the line sections.

[0047] The segment information includes the following key information: a. a unique segment identifier (Segment ID); b. an identifier of the line to which the segment belongs (Line ID); c. the mileage values corresponding to the segment boundary points (start and end) of the segment, which precisely locate the range of the segment on the UCM reference; d. the precise mileage values of one or more other service-related mileage types at the same physical boundary points of the segment (TypeA_Start, TypeA_End, TypeB_Start, TypeB_End,...), which must accurately correspond to the UCM boundary points; e. for each recorded mileage type, the trend of the mileage change within the segment (e.g., increasing, decreasing, or remaining unchanged); f. a key segment type identifier (SegmentType Identifier), which is selected from a predefined class hierarchy with properties and inheritance relationships that can comprehensively describe the state of railway mileage continuity, used to explicitly distinguish and uniquely identify the mileage characteristics of the segment. The class hierarchy at least includes: a base class "Segment", from which "Normal Continuity Segment" (all mileages are continuous within the segment and the relationship is simple, which can be interpolated linearly) and "Discontinuity Segment" are derived; the "Discontinuity Segment" subclass can further derive more specific subclasses, such as: "Long Chain Transition Segment" (a certain mileage jumps positively in this segment), "Short Chain Transition Segment" (a certain mileage jumps negatively), "Chain Start Segment" (a certain mileage starts to be interrupted in this segment), "Chain End Segment" (a certain mileage ends to be interrupted in this segment), "Chain Internal Segment" (the physical line exists but a certain mileage is undefined), "Mileage Overlapping Segment" (different locations have the same mileage value, or vice versa), etc. This identifier is the core basis for subsequent automatic selection and invocation of specific, predefined conversion processing rules or algorithms, aiming to replace manual interpretation and general approximation rules; g. optionally, to deal with cases where the conversion relationship between mileages within certain segments is not simply linear (such as the non-linear change of the mileage to UCM projection length ratio due to complex curves), the model allows storing local conversion function identifiers or parameter sets (e.g., storing fitted polynomial coefficients or pointers to specific algorithm modules) to describe such non-linear conversion relationships.

[0048] The line reference and data modeling module finally constructs the data model with line segments as the basic unit and generates a line segment database.

[0049] The mileage conversion request processing module, as the entrance of the system, is configured to receive mileage conversion requests initiated by external applications or users. After receiving the request, the core task of this module is to perform an efficient retrieval operation (for example, using a spatial index or B-tree index based on line ID and mileage range) in the line section database to quickly and accurately locate one or more line sections containing the mileage to be converted according to the line identifier and source mileage value provided in the request.

[0050] The segmented feature-driven conversion calculation module is the core that performs the actual mileage conversion calculation. After receiving the relevant line section information located by the mileage conversion request processing module, it first reads the "section type identifier" of the section.

[0051] According to the "line section type identifier", the module will automatically select and apply the most suitable strategy from a predefined library containing various targeted conversion strategies:

[0052] For "normal continuous sections": apply linear interpolation based on normalized relative offset to calculate the preliminary target mileage value.

[0053] For sections involving mileage jumps or discontinuities (such as "long / short chain transition sections", "discontinuity start / end / interior sections", etc.): the module will call predefined discontinuity / jump processing rule sets or segmented functions corresponding to the specific section type identifier. These rules or functions are customized according to the practices of the railway industry and specific business needs, and can accurately handle various discontinuities, such as:

[0054] For long or short chain transition sections, the conversion rules will perform precise proportional mapping or conformal mapping based on a unified continuous mileage reference with high precision, to ensure the true correspondence and continuity of spatial positions, rather than simply adjusting the mileage value;

[0055] For points requesting conversion falling within identified discontinuity sections, the rules will identify the conversion result within the discontinuity according to system configuration and specific discontinuity type (start, end, interior), and may return the nearest valid mileage value before / after the discontinuity, a specific error code or status identifier, or a virtual mileage value based on UCM and adjacent valid mileage sections;

[0056] For sections marked as requiring nonlinear conversion (and the corresponding local conversion functions or parameter sets are stored in the data model): the module will call these specific functions or use these parameters for calculation.

[0057] The conversion result verification and output module is responsible for the final validity verification and formatted output of the preliminary target mileage values generated by the segment feature driven conversion calculation module. The verification process includes boundary check, continuity check (optional), and according to whether the calculation process involves a broken link or jump section (indicated by the section type identifier), confirming whether to need to attach the corresponding explicit state identifier or warning information in the output result. The output content usually includes: the converted target mileage value, and state information indicating whether the conversion is successful, whether the conversion result is located at or adjacent to the broken link area or mileage jump point, the estimated conversion accuracy level, etc.

[0058] Referring to Figure 1 Another embodiment of the present application is a unified reference-based line multi-mileage system accurate conversion method, comprising the following steps:

[0059] S1. The line reference and data modeling module constructs a data model covering the entire line based on the unified continuous mileage reference.

[0060] Specifically, first, based on high-precision line three-dimensional space measurement data (such as centimeter-level three-dimensional coordinate sequences), through specific geometric processing and topological correction algorithms, a unified continuous mileage (UCM) reference covering the entire line is calculated and established, which has verifiable geometric continuity, strict monotonicity, and no any engineering jump or interruption. Second, according to the input line basic data (such as high-precision survey data, as-built design drawings, signal system layout drawings, operation mileage change records, etc.) and a set of pre-defined segmentation rules (for example, forced segmentation at bridge, tunnel start and end points, major turnout area, station center point, known milestone position, signal equipment key point, and all known mileage jump or interruption points), the line under the unified continuous mileage reference is segmented automatically or with a small amount of manual assistance, the continuous or mileage feature line is segmented to form line sections, and the section information of the line section is filled. Finally, the data model is constructed with line sections as basic units.

[0061] S2. The line reference and data modeling module generates a line section database.

[0062] The line section database is generated with line sections as basic units. The core is the line section, and the section information that each section needs to record includes: its unique identifier, the line identification it belongs to, the start and end mileage on the UCM, the accurate boundary value of at least one other business mileage type at the same point, the change trend of each mileage in the section, a section type identifier selected from a pre-defined class hierarchy, which explicitly indicates the mileage characteristics of the section (such as normal continuity, specific long-short chain type, broken link start-end / interior, etc.), and optional local conversion function or parameter set for handling non-linear relationship.

[0063] S3. The mileage conversion request processing module receives the conversion request and locates the line section where the mileage to be converted is located in the line section database.

[0064] Specifically, the mileage conversion request processing module listens to and receives the mileage conversion request, which needs to specify the source mileage value to be converted, the source mileage type, the line identity to which it belongs, and the target mileage type expected to be obtained. Using the request information, an efficient search is performed in the line section database established in step S2 to accurately locate one or more line section records containing the mileage value to be converted.

[0065] S4. The segmented feature-driven conversion calculation module automatically selects a conversion strategy according to the information of the line section where the mileage to be converted is located and obtains the target mileage value.

[0066] Specifically, after obtaining the line section record located in S3, its core attribute "line section type identifier" is read. According to the identifier, the most suitable strategy is automatically selected from the preset library containing various targeted conversion algorithms. The main strategies include: a) applying linear interpolation method based on normalized relative offset to "normal continuous section"; b) applying specially designed link processing rule set or segmented function corresponding to the line section type identifier for sections involving mileage jump or link breakage (such as "long / short link transition section", "link breakage start / end / interior section"); c) applying specified nonlinear conversion function for sections marked as "nonlinear section" and providing conversion function / parameters. The parameters required for applying the selected strategy are prepared, and the final calculation is performed based on the boundary mileage value of the target mileage type in the section record, the mileage change trend, and the local conversion function or parameters stored in the section, to obtain the preliminary target mileage value.

[0067] S5. The conversion result verification and output module verifies the validity of the result and outputs the final result.

[0068] Specifically, the preliminary target mileage value calculated in S4 is verified for validity. After verification, the calculated target mileage value is taken as the final conversion result. At the same time, according to the section type identifier involved in the conversion process and the system configuration, the corresponding state information (such as success / failure flag, explicit link / breakage area indication, precision description, etc.) is attached, and the complete result containing the mileage value and state information is output to the requester.

[0069] The following will take a newly built high-speed railway line L1 as an example for further illustration.

[0070] Reference Figure 2First, after the track design is completed and passed the precision engineering survey (e.g. 3D point cloud data of the track centerline is acquired by a 360° laser profiler. After the point cloud data is denoised, filtered, fitted centerline algorithm, and strictly checked and corrected for geometric topology (e.g. handling switch areas, intersections, etc.) to ensure no self-intersection or unreasonable inflection points, the track reference and data modeling module uses these high-precision 3D coordinate data to calculate and generate a unified continuous mileage reference covering the entire L1 line. Then, various mileage data related to the line are collected, including design mileage, construction adjustment records, operation mileage (especially the known accurate positions of long and short chains, original jump variables, and mileage values before and after the jump), and signal system related signal mileage data.

[0071] Then, the track reference and data modeling module segments the line L1 according to a set of predefined segmentation rules. Forced segmentation points include: all points where the known mileage jumps or breaks, points where the main geometric features of the line change, the start and end points of important structures, the center of the station or the ends of the platform, the boundaries of the main switch throat area, the positions of known mileposts or key signal equipment.

[0072] For each segment (e.g. S1, S2,..., Sn) divided, the track reference and data modeling module performs the following operations:

[0073] The UCM values corresponding to the exact start and end points of the section (UCM_Start, UCM_End) are calculated and recorded. The exact mileage values and trends of each known mileage type at the same physical start and end points are found and recorded. According to the characteristics of the various mileage data within the section, a clear "section type identifier" is assigned to it from a predefined class hierarchy. For example: if all the mileages within section S5 are continuous and approximately linear with respect to each other, it is marked as a "normal continuous section". If section S12 exactly crosses a long chain adjustment point of the operating mileage (for example, the physical position is continuous, but the operating mileage jumps directly from K10+000 to K10+500, while the UCM is continuously increasing at this point), S12 is marked as a "long chain transition section", and the operating mileage values before and after the jump (10000m -> 10500m) and the corresponding UCM values are recorded. If section S20 corresponds to a section of physical line, but the operating mileage is interrupted at this point, this area can be divided into "chain break start section", "chain break internal section", "chain break end section", and the UCM and other valid mileage values corresponding to the chain break start and end points are recorded. The "section type identifier" clearly distinguishes the three states. If section S35 is located in a complex spiral transition curve, causing the relationship between the operating mileage and the UCM to exhibit obvious nonlinearity, S35 is marked as a "nonlinear section (requires special function)", and the coefficients of the polynomial or the function pointer is stored in the data model as a local conversion parameter. All this information is stored in the line section database in a structured manner.

[0074] Further explanation is made by taking the example of receiving a request to convert the operating mileage K15+250 (15250m) on line L1 into signal mileage.

[0075] Referring to Figure 2 , the mileage conversion request processing module receives and parses the request, and the mileage conversion request processing module queries and locates to section S10 containing operating mileage 15250m in the line section database.

[0076] The section feature driven conversion calculation module reads the section S10 record from the database. Assume that the record shows that the "section type identifier" of S10 is "normal continuous section". The record contains the operating mileage range K15+000 to K16+000, and the signal mileage range SG15+100 to SG16+150, both of which are increasing.

[0077] Since the "line section type identifier" is "normal continuous section", the section feature driven conversion calculation module automatically selects the linear interpolation strategy. The normalized relative offset is calculated: Offset = (15250-15000) / (16000-15000) = 0.25.

[0078] Apply this offset to the target mileage (signal mileage) range for linear interpolation: Target_Signal_Mileage = 15100 + 0.25*(16150-15100) = 15362.5 meters.

[0079] After the conversion result verification and output module verification are passed, the output result is as follows: {"status":"success","target_mileage_type":"Signal mileage","value":15362.5,"formatted_value":"SG15+362.5","segment_type_processed":"Normal continuous segment","in_discontinuity":false}.

[0080] The following is further explained by taking the conversion involving mileage jump (long chain) as an example.

[0081] Assume that a request is received: convert the operating mileage K10+200 on line L1 (located in the long chain transition section S12 in Example 1, the operating mileage of this section jumps from K10+000 to K10+500, and the corresponding UCM is assumed to be UCM_A to UCM_B) to UCM.

[0082] The mileage conversion request processing module receives the request and locates segment S12.

[0083] The segment-feature-driven conversion calculation module reads an S12 record with a "Long Chain Transition Section" identifier. The record contains information about K10+000 (before the operating mileage change) corresponding to UCM_A, K10+500 (after the change) corresponding to UCM_A (the same physical point), and K10+X (at the other end) corresponding to UCM_B.

[0084] Because the "Line Section Type Identifier" is "Long Chain Transition Section," the segment-feature-driven conversion calculation module automatically invokes the predefined "UCM-based Exact Proportional Mapping Algorithm" for this type. This algorithm utilizes the relative position of the source mileage value (K10+200) within the nominal operating mileage length (for example, if the nominal operating mileage length of the long chain section is Y meters, the actual physical length is determined by UCM_B-UCM_A) and accurately maps it to the interval between UCM_A and UCM_B to ensure true spatial correspondence. For example, if K10+200 is nominally at 40% of the operating mileage of this "Long Chain" section, the target UCM value would be UCM_A+0.40*(UCM_B-UCM_A).

[0085] The conversion result verification and output module verifies and outputs the result, such as: {"status":"success","target_mileage_type":"UCM","value":calculated_UCM_value,"segment_type_processed":"long-chain transition segment","in_discontinuity":true,"discontinuity_info":"Processed as long-chain transition using UCM-based proportional mapping"}.

[0086] Further explanation is made by taking the processing of the conversion involving mileage discontinuity as an example.

[0087] Suppose a request is received: query the UCM corresponding to the operating mileage K20+100 of the line L2 (known to be located after a section of operating mileage discontinuity, the physical range of the discontinuity corresponds to UCM_C to UCM_D, and the first valid operating mileage after the discontinuity is K20+000, which corresponds to UCM_D).

[0088] The mileage conversion request processing module receives the request and locates to the section S25 containing the operating mileage K20+100.

[0089] The segment feature driven conversion calculation module reads the record of S25. Suppose its "line section type identifier" is "normal segment after discontinuity termination segment". Its operating mileage start point K20+000 corresponds to UCM_D, and its end point K21+000 corresponds to UCM_E.

[0090] The segment feature driven conversion calculation module applies linear interpolation according to the identifier of the "normal segment" (within S25). The operating mileage offset is calculated: Offset = (20100-20000) / (21000-20000) = 0.1.

[0091] Apply the offset to the UCM range: Target_UCM = UCM_D + 0.1*(UCM_E-UCM_D).

[0092] The conversion result is verified by the output module. Since the conversion point is followed by a broken link (known by S25 and the type and connection relationship of its preceding section), the output can contain: {"status":"success","target_mileage_type":"UCM","value":calculated_UCM_value,"segment_type_processed":"normal section after broken link ending section","in_discontinuity":true,"discontinuity_info":"Located after operational mileage discontinuity ending at K20+000(UCM_D)"}. If the request point K19+XXX falls into a section S24 with "line section type identifier" as "broken link internal section" (its UCM range is UCM_C to UCM_D, but no operational mileage defined), the segment feature driven conversion calculation module will call the rule for "broken link internal section". The rule can be configured as:

[0093] Return a specific status code indicating "located in broken link".

[0094] Return the nearest valid operational mileage before the broken link (e.g. K19+000, corresponding to UCM_C) and the nearest valid operational mileage after the broken link (K20+000, corresponding to UCM_D).

[0095] Estimate a virtual operational mileage value based on the relative position of the point within the range of UCM_C to UCM_D.

[0096] The present application has the following beneficial effects:

[0097] Establish a unified, accurate and verifiable continuous reference, significantly improve data consistency and comparability: by introducing and forcing the use of a unified continuous mileage reference based on high-precision three-dimensional spatial data, processed by a specific algorithm, with verifiable geometric continuity, a stable, accurate and unambiguous conversion reference system is provided for all coexisting mileage systems. This fundamentally solves the problem of data confusion caused by different reference systems or discontinuous reference systems, greatly improving the consistency, comparability and interoperability between different mileage data.

[0098] The enhanced feature classification data model accurately expresses and actively handles complex relationships. The proposed segmented multi-dimensional mileage correlation and feature classification data model, especially the "segment type identifier" selected from the predefined class hierarchy and the optional "local conversion function / parameter set", can more accurately and flexibly describe the complex correspondence between various mileage systems than traditional models. It can explicitly capture, classify and store key features such as mileage jumps and link breaks, and automatically trigger corresponding processing logic based on this classification, significantly improving the expression and automated processing capability of special segments and complex situations on the line.

[0099] Implement accurate, automated, and type-driven processing of link breaks and jumps: With clear and detailed "segment type identifiers" and strictly corresponding predefined and targeted conversion strategies (including UCM-based accurate mapping algorithms, special rule sets, or segmented functions), the present application can systematically and automatically process conversion requests for various types of mileage jumps (long and short links) and link break areas, replacing the reliance on manual interpretation or general approximate rules in traditional methods, significantly improving conversion accuracy and processing reliability in difficult situations.

[0100] Balancing conversion accuracy and efficiency through a hierarchical strategy: By intelligently combining efficient linear interpolation (for "normal continuous segments"), UCM-based accurate mapping algorithms (for specific types of jumps), and optional local nonlinear conversion functions (for geometrically complex segments), the present application can significantly improve the overall accuracy of mileage conversion while ensuring overall conversion efficiency to meet real-time requirements, especially in segments with complex geometry or special mileage relationships.

[0101] Improve system maintainability and scalability: The data model based on segments and explicit type identification has good modular characteristics. When the line is locally changed, a certain mileage system needs to be updated, or a new type of mileage needs to be introduced or new discontinuous features need to be processed, usually only a few data records of the segments involved in the change range (including their type identification) need to be modified or added, or new processing logic needs to be supplemented in the rule library, without the need for large-scale adjustment of the entire system. This greatly simplifies the maintenance work of the system and improves the scalability of the system to future development.

[0102] The above-described embodiments are only further descriptions of the present application and do not limit the present application in other forms. The present application can have other various embodiments. Those skilled in the art can make various corresponding modifications and changes to the present application without departing from the spirit and essence of the present application, and these corresponding modifications and changes should fall within the protection scope of the present application.

Claims

1. A multi-mileage accurate conversion system based on a unified reference benchmark, characterized by: The system includes: a route benchmark and data modeling module, a mileage conversion request processing module, a segmented feature-driven conversion calculation module, and a conversion result verification and output module. The route benchmark and data modeling module constructs a data model covering the entire route based on a unified continuous mileage benchmark. The mileage conversion request processing module is configured to receive and process mileage conversion requests initiated externally. The segmented feature-driven conversion calculation module is configured to convert mileage conversion requests. The conversion result verification and output module verifies and outputs the conversion results of the segmented feature-driven conversion calculation module.

2. The multi-mileage accurate conversion system based on a unified reference standard according to claim 1 is characterized in that: The unified continuous mileage benchmark is based on the route and three-dimensional centerline measurement data in a three-dimensional coordinate system, and is calculated through geometric processing and topological correction algorithms.

3. The method for converting a multi-mileage line system based on a unified reference benchmark according to claim 1, characterized in that: The route benchmark and data modeling module automatically or with manual assistance segments the route under the unified continuous mileage benchmark, separates the continuous or mileage-featured routes into route segments, and fills in the segment information of the route segments.

4. The multi-mileage accurate conversion system based on a unified reference standard according to claim 3 is characterized in that: The segment information includes: a. Unique line section identifier; b. Identifier of the line to which it belongs; c. Mileage values ​​of line section boundary points; d. Mileage values ​​of line sections of other mileage types at the same physical boundary point; e. Mileage change trend; f. Line section type identifier; g. Local transformation function identifier or parameter set that describes the nonlinear transformation relationship.

5. The multi-mileage accurate conversion system based on a unified reference standard according to claim 4 is characterized in that: The line benchmark and data modeling module constructs a data model using line sections as basic units and generates a line section database.

6. The multi-mileage accurate conversion system based on a unified reference standard according to claim 5 is characterized in that: The mileage conversion request processing module searches a route segment database according to the mileage conversion request to determine one or more route segments containing the mileage value to be converted.

7. The multi-mileage accurate conversion system based on a unified reference standard according to claim 6 is characterized in that: The segment feature driven conversion calculation module selects and applies a conversion strategy based on information about the route section where the mileage to be converted is located.

8. The line multi-mileage system precise conversion system based on a unified reference benchmark according to claim 7 is characterized in that: The conversion result verification and output module verification include boundary checking, continuity checking, and verifying whether it is necessary to add status identification or warning information to the output result based on the segment type identifier.

9. The line multi-mileage system precise conversion system based on a unified reference benchmark according to claim 8, characterized in that: The output of the conversion result verification and output module includes the target mileage value after conversion, whether the conversion is successful, whether the conversion result is located in or near a broken link area or a mileage jump point, and the conversion accuracy level.

10. A method for accurate conversion of multi-mileage line systems based on a unified reference benchmark, characterized in that: The following steps are involved: S1. The route benchmark and data modeling module builds a data model covering the entire route based on a unified continuous mileage benchmark; S2. The line benchmark and data modeling module generates a line section database; S3 mileage conversion request processing module receives the conversion request and locates the line segment to be converted mileage in the line segment database; S4. The segment feature-driven conversion calculation module automatically selects the conversion strategy and obtains the target mileage value based on the information of the route segment to be converted; S5. The conversion result verification and output module verifies the validity of the result and outputs the final result.

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