Digitized, standardized platform for highway infrastructure and method thereof

Abstract

The application discloses a digitalized and standardized platform for highway infrastructure and a method thereof, and belongs to the technical field of intelligent traffic control. In order to solve the problem of separation of lane-level road network and infrastructure in the digitalization of highway infrastructure, a data access module is connected with a data standardization module and a traffic element data processing module, and the data standardization module is connected with the traffic element data processing module. The data access module is used for collecting GIS data, business data and high-precision map data of the highway infrastructure. The data standardization module is used for performing data cleaning and preprocessing on the data collected by the data access module, performing coordinate system unification, element code unification and standard table and attribute creation. The traffic element data processing module is used for performing road network analysis, performing attribute mapping and correlation between the GIS data and the business data of the infrastructure, and performing conversion between stake numbers and longitude and latitude. The application realizes deep cooperation between the lane-level road network and the infrastructure.

Description

Technical Field

[0001] This invention belongs to the field of intelligent traffic control technology, specifically relating to a digital and standardized platform and method for highway infrastructure. Background Technology

[0002] The digitization of road infrastructure refers to the comprehensive information perception of road infrastructure through Geographic Information Systems (GIS), Internet of Things (IoT), and Building Information Modeling (BIM) technologies. Based on this, and according to actual business needs, the digitized road infrastructure is integrated and processed through various methods such as data storage, transmission, and visualization. Currently, the solutions for digitizing highway infrastructure are relatively simple, often separating lane-level high-precision maps from the infrastructure and performing separate digitization processes.

[0003] Although the concept of highway informatization has been proposed for many years, due to incomplete data, inaccurate records, and an incomplete standard system, data between highway platforms is not fully integrated, information standards are inconsistent, a true management and control network has not yet been formed, the degree of digitization of infrastructure and equipment is low, the degree of unification between road networks and road infrastructure is insufficient, the level of detail in the representation of facilities and equipment on maps is not high, and the degree of standardization is weak. This leads to difficulties in the subsequent operation and maintenance of highways, as well as in higher-level application scenarios. When digitizing highway networks, often only road lines at the segment level are considered, without extending to the lane level. There is a lack of research on the correspondence between lane-level data after high-precision map parsing and infrastructure. When processing roads for informatization, segment-level data can only meet display needs and cannot be used for subsequent applications requiring vehicle simulation calculations. Furthermore, due to the lack of specific lane information, roads cannot be well correlated with the locations of traffic facilities and equipment. Summary of the Invention

[0004] The problem this invention aims to solve is the separation of lane-level road networks and infrastructure in the digitalization of highway infrastructure, and provides a digital and standardized platform and method for highway infrastructure.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A digital and standardized platform for highway infrastructure includes a data access module, a data standardization module, and a traffic element data processing module. The data access module is connected to the data standardization module and the traffic element data processing module, respectively, and the data standardization module is connected to the traffic element data processing module.

[0007] The data access module is used to collect GIS data, business data, and high-precision map data of highway infrastructure.

[0008] The data standardization module is used to clean and preprocess the data collected by the data access module, and to unify the coordinate system, element coding, and create standard tables and attributes for the data.

[0009] The traffic element data processing module is used for road network analysis, attribute mapping and association between infrastructure GIS data and business data, conversion of station numbers and latitude and longitude, and digitization and display of infrastructure.

[0010] A method for digitizing and standardizing highway infrastructure, based on the aforementioned digitizing and standardizing platform for highway infrastructure, includes the following steps:

[0011] S1. Collect GIS data, business data, and high-precision map data of highway infrastructure;

[0012] S2. The GIS data and business data of the highway infrastructure collected in step S1 are cleaned and preprocessed to obtain preprocessed infrastructure data.

[0013] S3. Standardize the infrastructure data after preprocessing in step S2. The standardization methods include unifying the data coordinate system, unifying the element codes, and unifying the data attributes.

[0014] S4. Perform road network analysis on the high-precision map data collected in step S1 to obtain lane-level road network data.

[0015] S5. Map and associate the GIS data and business data in the infrastructure data after standardization in step S3 according to the device ID to obtain the associated infrastructure data.

[0016] S6. Convert the station numbers of the infrastructure association data obtained in step S5 into latitude and longitude, and match them with the latitude and longitude of the lane boundary lines of the road network data at the lane level in step S4 to obtain the final infrastructure location data.

[0017] S7. Display all the infrastructure location data obtained in step S6 through the digital and standardized platform for highway infrastructure.

[0018] Furthermore, the GIS data for highway infrastructure in step S1 includes road network-related data, ancillary facility data, other highway-related data, and administrative boundary data;

[0019] The road network-related data includes highway link data, 100-meter marker data, interchange data, hub data, bridge data, and tunnel data;

[0020] The ancillary facility data includes toll station data, service area data, ETC gantry data, variable message sign data, sign data, and monitoring point data;

[0021] Other highway-related data include emergency center data, rescue vehicle data, and road network center data;

[0022] The administrative boundary data includes province, city, and district / county layers;

[0023] The types of GIS data include shp files, geojson files, excel files, and CAD drawings;

[0024] The business data includes the physical structure, service life, and technical rating attributes of bridges and tunnels.

[0025] The high-precision map data is an OpenDRIVE format XML text file obtained from the map provider that collects road information.

[0026] Furthermore, the data cleaning and preprocessing methods in step S2 include data cleaning, repair, deduplication, field correction, and storage.

[0027] Furthermore, the specific implementation method of step S3 includes the following steps:

[0028] S3.1 Unify the data coordinate system: Transform the GIS data with latitude and longitude through the coordinate transformation function between WGS-84 and GCJ-02, and convert it into the UTM projection coordinate system under WGS84.

[0029] S3.2 Unify the element encoding: Use the UUID method to generate the primary key of all infrastructure data, which is a 36-bit string type, and use a 36-byte string to represent the elements of the infrastructure data;

[0030] S3.3 Unify data attributes: The creation of standard tables and attributes is carried out in accordance with the standard fields of infrastructure data. Specifically, the unit of the field of the preprocessed infrastructure data is converted into the unit of the standard attribute; the geographic information field of the preprocessed infrastructure data is represented by three attribute fields, namely the highway number field, the station number field, and the direction field.

[0031] Furthermore, the specific implementation method of step S4 includes the following steps:

[0032] S4.1 Parsing of header files in high-precision map data: Using PROJ-based projection strings to determine the coordinate system information data of the high-precision map;

[0033] S4.2 Analysis of road information in high-precision map data: including road reference line information and lane information;

[0034] S4.2.1, Analysis of Road Reference Line Information:

[0035] S4.2.1.1 First, determine the coordinate values ​​in the u / v coordinate system of the geographic elements of the road reference line, expressed as a parametric trinomial, then the formula is:

[0036] u(p) = aU + bU*p + cU*p 2 +dU*p 3

[0037] v(p)=aV+bV*p+cV*p 2 +dV*p 3

[0038] Where u(p) is the coordinate value in the u direction of the u / v coordinate system, v(p) is the coordinate value in the v direction of the u / v coordinate system, aU is the first parameter in the parametric polynomial describing the u coordinate value, bU is the second parameter in the parametric polynomial describing the u coordinate value, cU is the third parameter in the parametric polynomial describing the u coordinate value, dU is the fourth parameter in the parametric polynomial describing the u coordinate value, aV is the first parameter in the parametric polynomial describing the v coordinate value, bV is the second parameter in the parametric polynomial describing the v coordinate value, cV is the third parameter in the parametric polynomial describing the v coordinate value, dV is the fourth parameter in the parametric polynomial describing the v coordinate value, and p is the interpolation parameter, which is in the range [0, 1].

[0039] S4.2.1.2. Convert the u / v coordinate system to the x / y coordinate system. The conversion formula is as follows:

[0040] x(u,v)=(coshdg*u-coshdg*v)+x0

[0041] y(u,v)=(sinhdg*u-coshdg*v)+y0

[0042] Where x(u,v) is the coordinate value in the x direction of the x / y coordinate system, y(u,v) is the coordinate value in the y direction of the x / y coordinate system, hdg is the starting direction of the reference line, u and v are the distances in the u and v directions of the calculated u / v coordinate system, and x0 and y0 are the distances in the x and y directions of the starting position in the x / y coordinate system, respectively.

[0043] S4.2.2, Analysis of Lane Level Data:

[0044] S4.2.2.1 Calculate the lane displacement offset(s) of the center lane on the road reference line, and the lane width (s'). The calculation formula is as follows:

[0045] offset(s) = a + b*s + c*s 2 +d*s 3

[0046] Where a is the first parameter of the polynomial, b is the second parameter of the polynomial, c is the third parameter of the polynomial, d is the fourth parameter of the polynomial, and s is the distance generated along the road reference line between the starting point of the road offset element and the given position.

[0047] width(s') = a + b * s' + c * s' 2 +d*s' 3

[0048] Wherein, s' is the distance generated along the road reference line between the starting point of the road width element and the given position;

[0049] S4.2.2.2 Based on the lane width and lane displacement obtained in step S4.2.2.1, the lane centerline is obtained, and then the lane boundary line is obtained;

[0050] S4.2.2.3. Based on the lane centerline and lane boundary line data obtained from the analysis, connect the first and last nodes of each lane to the boundary line in sequence to obtain lane surface information. Connect the innermost and outermost lane boundary lines of each road in sequence to obtain road surface information.

[0051] S4.3, Analysis of intersection information in high-precision map data: Obtain road connection point information, turning information, and lane connection information within each intersection based on the connecting roads;

[0052] S4.4. Check the parsed road, including whether the node and lane information corresponds or is repeated, and whether the connecting lines and the number of lanes are normal.

[0053] Furthermore, the specific implementation method of step S5 includes the following steps:

[0054] S5.1 For each type of infrastructure data, construct a GIS data matrix as G. k Construct the business data matrix Y k ,but:

[0055]

[0056]

[0057] Among them, G mgY is the g-th attribute of the m-th data in the GIS data. ny The y-th attribute of the nth data item in the business data;

[0058] S5.2. Connect the two matrices constructed in step S5.1 to obtain the overall correlation data matrix C. k :

[0059]

[0060] Among them, C m(g+y-1) This refers to the g+y-1th attribute of the m-th data in the associated data.

[0061] Furthermore, the specific implementation method of step S6 includes the following steps:

[0062] S6.1 Determine whether the highway number field, station number field, and direction field in the infrastructure association data obtained in step S5 are complete. If yes, proceed to step S6.2 to convert the station number and latitude and longitude. If no, proceed to step S6.3.

[0063] S6.2 The method for converting station numbers and latitude and longitude is as follows:

[0064] S6.2.1. Based on the standard attributes obtained in step S3, set S as the distance from the infrastructure point by station number, and S0 and S1 as the distance from the two nearest 100-meter station numbers to the infrastructure point by station number. Then, perform interpolation between the two points based on the 100-meter station data. The interpolation formula is as follows:

[0065] S0 = SS%100

[0066] S1 = S0 + 100

[0067] S6.2.2, Set the interpolation point in the 100-meter stake data as P. c P c The coordinates in the WGS84 / UTM coordinate system are (x c y c Then we have:

[0068]

[0069]

[0070] Where x0, y0 and x1, y1 are the coordinates of S0 and S1 in the WGS84 / UTM coordinate system, respectively;

[0071] S6.2.3, Set P in step S6.2.2 c Based on the lane boundary line data, offset to the outermost lane boundary line of the road, that is, calculate P. cProjection point P on the outermost lane line b First, find the distance from P on the boundary line. c Find the nearest line segment L to the point and calculate P. c After P c And the distance on the line segment parallel to L, and then the interpolation on the line segment L according to the interpolation in S6.2.1, the resulting coordinates are the final infrastructure location data;

[0072] S6.3 Determine whether latitude and longitude data exist in the infrastructure data. If yes, project the latitude and longitude data in the data onto the outermost lane boundary of the nearest road according to the steps in S6.2.3 to obtain the final infrastructure location data. If no, mark it as erroneous data by manual processing.

[0073] S6.4. Convert the coordinates of the points in the final infrastructure point data under WGS84 / UTM into latitude and longitude coordinates under WGS84 to obtain the latitude and longitude of all infrastructure points.

[0074] Furthermore, the specific implementation method of step S7 includes the following steps:

[0075] S7.1 Upload all data to the PostgreSQL space database and name them according to the standard table naming convention;

[0076] S7.2 Configure the data style according to the icons designed for different types of infrastructure;

[0077] S7.3 Publish data layers and styles through Geoserver and display them on the digital and standardized platform for highway infrastructure.

[0078] The beneficial effects of this invention are:

[0079] The present invention provides a digital and standardized method for highway infrastructure, which enables deep collaboration between lane-level road networks and infrastructure, and can connect data stored on different platforms, making it easier to manage and update highway infrastructure throughout its entire life cycle.

[0080] This invention discloses a method for digitizing and standardizing highway infrastructure. After data processing, the processed data can be displayed more intuitively on a map, providing better data support for upper-level applications. Data analyzed from high-precision maps provides detailed lane-level road network information, an indispensable data source for simulation calculations and visualization. By establishing the correspondence between the high-precision map data and infrastructure equipment, a better representation of the real world can be achieved. This invention provides a complete process and standardized solution for infrastructure digitization in all similar scenarios.

[0081] The present invention describes a method for digitizing and standardizing highway infrastructure. By developing a mapping algorithm between station numbers and latitude and longitude, the present invention establishes database standards and attributes for various types of GIS data, and can integrate GIS data of all infrastructure equipment.

[0082] The present invention describes a method for digitizing and standardizing highway infrastructure. By analyzing high-precision map data, it can provide detailed lane-level road network information, providing an indispensable data source for simulation calculation and display.

[0083] The present invention provides a method for digitizing and standardizing highway infrastructure. By analyzing the data from high-precision maps and establishing a correspondence between the data and infrastructure equipment, a better representation of the real world can be obtained. The present invention provides a complete process and standardized solution for digitizing infrastructure in all similar scenarios. Attached Figure Description

[0084] Figure 1 This is a schematic diagram of the structure of a digital and standardized platform for highway infrastructure according to the present invention;

[0085] Figure 2 This is a schematic diagram of the data acquisition module described in this invention.

[0086] Figure 3 This is a schematic diagram of the high-definition map parsing in step S4 of the present invention;

[0087] Figure 4 This is a flowchart of a method for digitizing and standardizing highway infrastructure according to the present invention. Detailed Implementation

[0088] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described specific embodiments are merely a part of the embodiments of the invention, and not all of them. The components of the specific embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations, and the invention may also have other embodiments.

[0089] Therefore, the following detailed description of specific embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected specific embodiments of the invention. All other specific embodiments obtained by those skilled in the art based on these specific embodiments without inventive effort are within the scope of protection of this invention.

[0090] To further understand the invention's content, features, and effects, the following specific embodiments are provided, along with detailed descriptions in conjunction with the accompanying drawings: Specific implementation method one:

[0092] A digital and standardized platform for highway infrastructure includes a data access module 1, a data standardization module 2, and a traffic element data processing module 3. The data access module 1 is connected to the data standardization module 2 and the traffic element data processing module 3, respectively, and the data standardization module 2 is connected to the traffic element data processing module 3.

[0093] The data access module 1 is used to collect GIS data, business data, and high-precision map data of highway infrastructure;

[0094] The data standardization module 2 is used to clean and preprocess the data collected by the data access module 1, and to unify the coordinate system, element coding, standard tables and attributes of the data.

[0095] The traffic element data processing module 3 is used to perform road network analysis, map and associate the attributes of infrastructure GIS data and business data, convert station numbers to latitude and longitude, and digitize and display infrastructure. Specific Implementation Method Two:

[0097] A method for digitizing and standardizing highway infrastructure, based on a digitizing and standardizing platform for highway infrastructure as described in Specific Implementation Method 1, includes the following steps:

[0098] S1. Collect GIS data, business data, and high-precision map data of highway infrastructure;

[0099] Furthermore, the GIS data for highway infrastructure in step S1 includes road network-related data, ancillary facility data, other highway-related data, and administrative boundary data;

[0100] The road network-related data includes highway link data, 100-meter marker data, interchange data, hub data, bridge data, and tunnel data;

[0101] The high-speed link data describes the road boundary line data of the highway, the 100-meter stake data is the point marker every 100m in the highway, and the interchanges, hubs, bridges and tunnels are all line data, consistent with the high-speed link data, and are a partial extraction of road information;

[0102] The ancillary facility data includes toll station data, service area data, ETC gantry data, variable message sign data, sign data, and monitoring point data;

[0103] Other highway-related data include emergency center data, rescue vehicle data, and road network center data;

[0104] The administrative boundary data includes province, city, and district / county layers;

[0105] The types of GIS data include shp files, geojson files, excel files, and CAD drawings;

[0106] The business data includes the physical structure, service life, and technical rating attributes of bridges and tunnels.

[0107] The business data refers to data that does not have spatial information but has physical and business attributes.

[0108] The high-precision map data is an OpenDRIVE format XML text file obtained from the map provider that collects road information.

[0109] S2. The GIS data and business data of the highway infrastructure collected in step S1 are cleaned and preprocessed to obtain preprocessed infrastructure data.

[0110] Furthermore, the data cleaning and preprocessing methods in step S2 include data cleaning, repair, deduplication, field correction, and storage;

[0111] S3. Standardize the infrastructure data after preprocessing in step S2. The standardization methods include unifying the data coordinate system, unifying the element codes, and unifying the data attributes.

[0112] Furthermore, the specific implementation method of step S3 includes the following steps:

[0113] S3.1 Unify the data coordinate system: Transform the GIS data with latitude and longitude through the coordinate transformation function between WGS-84 and GCJ-02, and convert it into the UTM projection coordinate system under WGS84.

[0114] S3.2 Unify the element encoding: Use the UUID method to generate the primary key of all infrastructure data, which is a 36-bit string type, and use a 36-byte string to represent the elements of the infrastructure data;

[0115] S3.3 Unify data attributes: The creation of standard tables and attributes is carried out in accordance with the standard fields of infrastructure data to unify attributes. Specifically, the field units of the preprocessed infrastructure data are converted to the units of the standard attributes; the geographic information fields of the preprocessed infrastructure data are represented by three attribute fields, namely the highway number field, the station number field, and the direction field.

[0116] Furthermore, the station number field is uniformly represented as Kxx+xxx, for example, K5+100, which means the position is 5×1000+100=5100 meters away from the starting point. The direction field is up or down, with "A" representing up and "B" representing down.

[0117] S4. Perform road network analysis on the high-precision map data collected in step S1 to obtain lane-level road network data.

[0118] Furthermore, the specific implementation method of step S4 includes the following steps:

[0119] S4.1 Parsing of header files in high-precision map data: Using PROJ-based projection strings to determine the coordinate system information data of the high-precision map;

[0120] S4.2 Analysis of road information in high-precision map data: including road reference line information and lane information;

[0121] S4.2.1, Analysis of Road Reference Line Information:

[0122] S4.2.1.1 First, determine the coordinate values ​​in the u / v coordinate system of the geographic elements of the road reference line, expressed as a parametric trinomial, then the formula is:

[0123] u(p) = aU + bU*p + cU*p 2 +dU*p 3

[0124] v(p)=aV+bV*p+cV*p 2+dV*p 3

[0125] Where u(p) is the coordinate value in the u direction of the u / v coordinate system, v(p) is the coordinate value in the v direction of the u / v coordinate system, aU is the first parameter in the parametric polynomial describing the u coordinate value, bU is the second parameter in the parametric polynomial describing the u coordinate value, cU is the third parameter in the parametric polynomial describing the u coordinate value, dU is the fourth parameter in the parametric polynomial describing the u coordinate value, aV is the first parameter in the parametric polynomial describing the v coordinate value, bV is the second parameter in the parametric polynomial describing the v coordinate value, cV is the third parameter in the parametric polynomial describing the v coordinate value, dV is the fourth parameter in the parametric polynomial describing the v coordinate value, and p is the interpolation parameter, which is in the range [0, 1].

[0126] S4.2.1.2. Convert the u / v coordinate system to the x / y coordinate system. The conversion formula is as follows:

[0127] x(u,v)=(coshdg*u-coshdg*v)+x0

[0128] y(u,v)=(sinhdg*u-coshdg*v)+y0

[0129] Where x(u,v) is the coordinate value in the x direction of the x / y coordinate system, y(u,v) is the coordinate value in the y direction of the x / y coordinate system, hdg is the starting direction of the reference line, u and v are the distances in the u and v directions of the calculated u / v coordinate system, and x0 and y0 are the distances in the x and y directions of the starting position in the x / y coordinate system, respectively.

[0130] S4.2.2, Analysis of Lane Level Data:

[0131] S4.2.2.1 Calculate the lane displacement offset(s) of the center lane on the road reference line, and the lane width (s'). The calculation formula is as follows:

[0132] offset(s) = a + b*s + c*s 2 +d*s 3

[0133] Where a is the first parameter of the polynomial, b is the second parameter of the polynomial, c is the third parameter of the polynomial, d is the fourth parameter of the polynomial, and s is the distance generated along the road reference line between the starting point of the road offset element and the given position.

[0134] width(s') = a + b * s' + c * s' 2 +d*s' 3

[0135] Wherein, s' is the distance generated along the road reference line between the starting point of the road width element and the given position;

[0136] S4.2.2.2 Based on the lane width and lane displacement obtained in step S4.2.2.1, the lane centerline is obtained, and then the lane boundary line is obtained;

[0137] S4.2.2.3. Based on the lane centerline and lane boundary line data obtained from the analysis, connect the first and last nodes of each lane to the boundary line in sequence to obtain lane surface information. Connect the innermost and outermost lane boundary lines of each road in sequence to obtain road surface information.

[0138] S4.3, Analysis of intersection information in high-precision map data: Obtain road connection point information, turning information, and lane connection information within each intersection based on the connecting roads;

[0139] S4.4. Check the parsed road, including whether the node and lane information corresponds or is repeated, and whether the connecting lines and the number of lanes are normal.

[0140] S5. Map and associate the GIS data and business data in the infrastructure data after standardization in step S3 according to the device ID to obtain the associated infrastructure data.

[0141] Furthermore, the specific implementation method of step S5 includes the following steps:

[0142] S5.1 For each type of infrastructure data, construct a GIS data matrix as G. k Construct the business data matrix Y k ,but:

[0143]

[0144]

[0145] Among them, G mg Y is the g-th attribute of the m-th data in the GIS data. ny The y-th attribute of the nth data item in the business data;

[0146] S5.2. Connect the two matrices constructed in step S5.1 to obtain the overall correlation data matrix C. k :

[0147]

[0148] Among them, C m(g+y-1) This refers to the g+y-1th attribute of the m-th data in the associated data.

[0149] S6. Convert the station numbers of the infrastructure association data obtained in step S5 into latitude and longitude, and match them with the latitude and longitude of the lane boundary lines of the road network data at the lane level in step S4 to obtain the final infrastructure location data.

[0150] Furthermore, the specific implementation method of step S6 includes the following steps:

[0151] S6.1 Determine whether the highway number field, station number field, and direction field in the infrastructure association data obtained in step S5 are complete. If yes, proceed to step S6.2 to convert the station number and latitude and longitude. If no, proceed to step S6.3.

[0152] S6.2 The method for converting station numbers and latitude and longitude is as follows:

[0153] S6.2.1. Based on the standard attributes obtained in step S3, set S as the distance from the infrastructure point by station number, and S0 and S1 as the distance from the two nearest 100-meter station numbers to the infrastructure point by station number. Then, perform interpolation between the two points based on the 100-meter station data. The interpolation formula is as follows:

[0154] S0 = SS%100

[0155] S1 = S0 + 100

[0156] S6.2.2, Set the interpolation point in the 100-meter stake data as P. c P c The coordinates in the WGS84 / UTM coordinate system are (x c y c Then we have:

[0157]

[0158]

[0159] Where x0, y0 and x1, y1 are the coordinates of S0 and S1 in the WGS84 / UTM coordinate system, respectively;

[0160] S6.2.3, Set P in step S6.2.2 c Based on the lane boundary line data, offset to the outermost lane boundary line of the road, that is, calculate P. c Projection point P on the outermost lane line b First, find the distance from P on the boundary line. c Find the nearest line segment L to the point and calculate P. c After P c And the distance on the line segment parallel to L, and then the interpolation on the line segment L according to the interpolation in S6.2.1, the resulting coordinates are the final infrastructure location data;

[0161] S6.3 Determine whether latitude and longitude data exist in the infrastructure data. If yes, project the latitude and longitude data in the data onto the outermost lane boundary of the nearest road according to the steps in S6.2.3 to obtain the final infrastructure location data. If no, mark it as erroneous data by manual processing.

[0162] S6.4. Convert the coordinates of the points in WGS84 / UTM in the final infrastructure point data into latitude and longitude coordinates in WGS84 to obtain the latitude and longitude of all infrastructure points.

[0163] S7. Display all the infrastructure location data obtained in step S6 through the digital and standardized platform for highway infrastructure.

[0164] Furthermore, the specific implementation method of step S7 includes the following steps:

[0165] S7.1 Upload all data to the PostgreSQL space database and name them according to the standard table naming convention;

[0166] S7.2 Configure the data style according to the icons designed for different types of infrastructure;

[0167] S7.3 Publish data layers and styles through Geoserver and display them on the digital and standardized platform for highway infrastructure.

[0168] Furthermore, the data after element processing can be displayed more intuitively on the map, providing better data support for upper-level applications. Data parsed from high-precision maps can provide detailed lane-level road network information, offering an indispensable data source for simulation calculations and visualizations. By establishing the correspondence between the data parsed from high-precision maps and infrastructure equipment, a better reconstruction of the real world can be achieved. This invention provides a complete process and standardized solution for infrastructure digitization in all similar scenarios.

[0169] The key technical points and intended protection points of this invention are: a method for the digitization and standardization of infrastructure and equipment, achieving the fusion of all data related to highway ancillary facilities to obtain a consistent representation of all elements of the highway network and infrastructure equipment. Based on this invention, it is possible to break down the barriers between data from various platforms, improve the efficiency and accuracy of infrastructure digitization, and provide strong data support for subsequent maintenance and management.

[0170] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0171] Although this application has been described above with reference to specific embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of this application. In particular, as long as there is no structural conflict, the features in the specific embodiments disclosed in this application can be combined with each other in any way. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, this application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A digitalization and standardization method for highway infrastructure, based on a digitalization and standardization platform for highway infrastructure, comprising a data access module (1), a data standardization module (2), and a traffic element data processing module (3), wherein the data access module (1) is connected to the data standardization module (2) and the traffic element data processing module (3), and the data standardization module (2) is connected to the traffic element data processing module (3); The data access module (1) is used to collect GIS data, business data, and high-precision map data of highway infrastructure; The data standardization module (2) is used to clean and preprocess the data collected by the data access module (1), and to perform coordinate system unification, element coding unification, standard table and attribute creation. The traffic element data processing module (3) is used to perform road network analysis, map and associate the GIS data of infrastructure with business data, convert station numbers and latitude and longitude, and digitize and display infrastructure. Its features are: Includes the following steps: S1. Collect GIS data, business data, and high-precision map data of highway infrastructure; S2. The GIS data and business data of the highway infrastructure collected in step S1 are cleaned and preprocessed to obtain preprocessed infrastructure data. S3. Standardize the infrastructure data after preprocessing in step S2. The standardization methods include unifying the data coordinate system, unifying the element codes, and unifying the data attributes. S4. Perform road network analysis on the high-precision map data collected in step S1 to obtain lane-level road network data. The specific implementation method of step S4 includes the following steps: S4.1 Parsing of header files in high-precision map data: Using PROJ-based projection strings to determine the coordinate system information data of the high-precision map; S4.2 Analysis of road information in high-precision map data: including road reference line information and lane information; S4.2.1, Analysis of Road Reference Line Information: S4.2.1.1 First, determine the coordinate values ​​in the u / v coordinate system of the geographic elements of the road reference line, expressed as a parametric trinomial, then the formula is: u(p)=aU+bU*p+cU*p 2 +dU*p 3 v(p)=aV+bV*p+cV*p 2 +dV*p 3 Where u(p) is the coordinate value in the u direction of the u / v coordinate system, v(p) is the coordinate value in the v direction of the u / v coordinate system, aU is the first parameter in the parametric polynomial describing the u coordinate value, bU is the second parameter in the parametric polynomial describing the u coordinate value, cU is the third parameter in the parametric polynomial describing the u coordinate value, dU is the fourth parameter in the parametric polynomial describing the u coordinate value, aV is the first parameter in the parametric polynomial describing the v coordinate value, bV is the second parameter in the parametric polynomial describing the v coordinate value, cV is the third parameter in the parametric polynomial describing the v coordinate value, dV is the fourth parameter in the parametric polynomial describing the v coordinate value, and p is the interpolation parameter, which is in the range [0, 1]. S4.2.1.

2. Convert the u / v coordinate system to the x / y coordinate system. The conversion formula is as follows: x(u,v)=(coshdg*u-coshdg*v)+x0 y(u,v)=(sinhdg*u-coshdg*v)+y0 Where x(u,v) is the coordinate value in the x direction of the x / y coordinate system, y(u,v) is the coordinate value in the y direction of the x / y coordinate system, hdg is the starting direction of the reference line, u and v are the distances in the u and v directions of the calculated u / v coordinate system, and x0 and y0 are the distances in the x and y directions of the starting position in the x / y coordinate system, respectively. S4.2.2, Analysis of Lane Level Data: S4.2.2.1 Calculate the lane displacement offset(s) of the center lane on the road reference line, and the lane width (s'). The calculation formula is as follows: offset(s)=a+b*s+c*s 2 +d*s 3 Where a is the first parameter of the polynomial, b is the second parameter of the polynomial, c is the third parameter of the polynomial, d is the fourth parameter of the polynomial, and s is the distance generated along the road reference line between the starting point of the road offset element and the given position. width(s')=a+b*s'+c*s' 2 +d*s '3 Wherein, s' is the distance generated along the road reference line between the starting point of the road width element and the given position; S4.2.2.2 Based on the lane width and lane displacement obtained in step S4.2.2.1, the lane centerline is obtained, and then the lane boundary line is obtained; S4.2.2.

3. Based on the lane centerline and lane boundary line data obtained from the analysis, connect the first and last nodes of each lane to the boundary line in sequence to obtain lane surface information. Connect the innermost and outermost lane boundary lines of each road in sequence to obtain road surface information. S4.3, Analysis of intersection information in high-precision map data: Obtain road connection point information, turning information, and lane connection information within each intersection based on the connecting roads; S4.

4. Check the parsed road, including whether the node and lane information corresponds or is repeated, and whether the connecting lines and the number of lanes are normal. S5. Map and associate the GIS data and business data in the infrastructure data after standardization in step S3 according to the device ID to obtain the associated infrastructure data. S6. Convert the station numbers of the infrastructure association data obtained in step S5 into latitude and longitude, and match them with the latitude and longitude of the lane boundary lines of the road network data at the lane level in step S4 to obtain the final infrastructure location data. S7. Display all the infrastructure location data obtained in step S6 through the digital and standardized platform for highway infrastructure.

2. The method for digitizing and standardizing highway infrastructure according to claim 1, characterized in that: The GIS data for highway infrastructure in step S1 includes road network-related data, ancillary facility data, other highway-related data, and administrative boundary data; The road network-related data includes highway link data, 100-meter marker data, interchange data, hub data, bridge data, and tunnel data; The ancillary facility data includes toll station data, service area data, ETC gantry data, variable message sign data, sign data, and monitoring point data; Other highway-related data include emergency center data, rescue vehicle data, and road network center data; The administrative boundary data includes province, city, and district / county layers; The types of GIS data include shp files, geojson files, excel files, and CAD drawings; The business data includes the physical structure, service life, and technical rating attributes of bridges and tunnels. The high-precision map data is an OpenDRIVE format XML text file obtained from the map provider that collects road information.

3. The method for digitizing and standardizing highway infrastructure according to claim 2, characterized in that: The data cleaning and preprocessing methods in step S2 include data cleaning, repair, deduplication, field correction, and storage.

4. The method for digitizing and standardizing highway infrastructure according to claim 3, characterized in that: The specific implementation method of step S3 includes the following steps: S3.1 Unify the data coordinate system: Transform the GIS data with latitude and longitude through the coordinate transformation function between WGS-84 and GCJ-02, and convert it into the UTM projection coordinate system under WGS84. S3.2 Unify the element encoding: Use the UUID method to generate the primary key of all infrastructure data, which is a 36-bit string type, and use a 36-byte string to represent the elements of the infrastructure data; S3.3 Unify data attributes: The creation of standard tables and attributes is carried out in accordance with the standard fields of infrastructure data. Specifically, the unit of the field of the preprocessed infrastructure data is converted into the unit of the standard attribute; the geographic information field of the preprocessed infrastructure data is represented by three attribute fields, namely the highway number field, the station number field, and the direction field.

5. The method for digitizing and standardizing highway infrastructure according to claim 4, characterized in that: The specific implementation method of step S5 includes the following steps: S5.1 For each type of infrastructure data, construct a GIS data matrix as G. k Construct the business data matrix Y k ,but: Among them, G mg Y is the g-th attribute of the m-th data in the GIS data. ny The y-th attribute of the nth data item in the business data; S5.

2. Connect the two matrices constructed in step S5.1 to obtain the overall correlation data matrix C. k : Among them, C m(g+y-1) This refers to the g+y-1th attribute of the m-th data in the associated data.

6. The method for digitizing and standardizing highway infrastructure according to claim 5, characterized in that: The specific implementation method of step S6 includes the following steps: S6.1 Determine whether the highway number field, station number field, and direction field in the infrastructure association data obtained in step S5 are complete. If yes, proceed to step S6.2 to convert the station number and latitude and longitude. If no, proceed to step S6.

3. S6.2 The method for converting station numbers and latitude and longitude is as follows: S6.2.

1. Based on the standard attributes obtained in step S3, set S as the distance from the infrastructure point by station number, and S0 and S1 as the distance from the two nearest 100-meter station numbers to the infrastructure point by station number. Then, perform interpolation between the two points based on the 100-meter station data. The interpolation formula is as follows: S0 = SS%100 S1 = S0 + 100 S6.2.2, Set the interpolation point in the 100-meter stake data as P. c P c The coordinates in the WGS84 / UTM coordinate system are (x c y c Then we have: Where x0, y0 and x1, y1 are the coordinates of S0 and S1 in the WGS84 / UTM coordinate system, respectively; S6.2.3, Set P in step S6.2.2 c Based on the lane boundary line data, offset to the outermost lane boundary line of the road, that is, calculate P. c Projection point P on the outermost lane line b First, find the distance from P on the boundary line. c Find the nearest line segment L to the point and calculate P. c After P c And the distance on the line segment parallel to L, and then the interpolation on the line segment L according to the interpolation in S6.2.1, the resulting coordinates are the final infrastructure location data; S6.3 Determine whether latitude and longitude data exist in the infrastructure data. If yes, project the latitude and longitude data in the data onto the outermost lane boundary of the nearest road according to the steps in S6.2.3 to obtain the final infrastructure location data. If no, mark it as erroneous data by manual processing. S6.

4. Convert the coordinates of the points in the final infrastructure point data under WGS84 / UTM into latitude and longitude coordinates under WGS84 to obtain the latitude and longitude of all infrastructure points.

7. A method for digitizing and standardizing highway infrastructure according to claim 6, characterized in that: The specific implementation method of step S7 includes the following steps: S7.1 Upload all data to the PostgreSQL space database and name them according to the standard table naming convention; S7.2 Configure the data style according to the icons designed for different types of infrastructure; S7.3 Publish data layers and styles through Geoserver and display them on the digital and standardized platform for highway infrastructure.

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