Obstacle area pile adding method and device in road layout and computer equipment

Abstract

This application relates to a method, apparatus, and computer equipment for adding stakes in obstacle areas during road layout. The method includes: determining the construction centerline model and longitudinal profile elevation information of the road based on the original design data; determining an integrated centerline model of the road based on the construction centerline model and the longitudinal profile design elevation information; constructing a distance objective function between mileage parameter points on the integrated centerline model and corresponding reference objects in each obstacle area based on the integrated centerline model and pre-collected feature points; determining the stake points to be added based on the distance objective function; determining the engineering standard station number of each stake point based on the integrated centerline model and the location information of each stake point; and performing stake addition processing on each stake point based on the engineering standard station number of each stake point and the design elevation of each stake point determined by the longitudinal profile design elevation information. This method can reduce stake addition errors, thereby improving stake addition accuracy and efficiency.

Description

Technical Field

[0001] This application relates to the field of road engineering technology, and in particular to a method, apparatus and computer equipment for adding stakes in obstacle areas during road layout. Background Technology

[0002] In the traditional implementation process of road engineering, road surveying work can generally be divided into three stages: preliminary route survey, fixed-point survey, and construction layout. Construction layout is one of the most basic and important surveying tasks in the road construction process. It is directly related to the accurate restoration of the road centerline position and the mapping quality of the longitudinal and cross sections. Construction layout takes the road centerline layout as its core content, and the longitudinal and cross sections of the road use the road centerline station number as the index parameter.

[0003] In road construction layout, road design data is typically drawn using full-scale stake numbers (such as K0+000, K0+020, K0+040, etc.) as reference points, and corresponding center stakes are inserted on the construction site. However, in actual construction environments, the locations corresponding to full-scale stake numbers may fall in areas with complex terrain, such as ponds, ditches, collapsed farmland, steep slopes, soft soil areas, or other obstacle areas. This makes it impossible to insert wooden stakes or steel stakes at the pre-set full-scale stake numbers, thus preventing the accurate marking of the center stakes on the actual ground. Therefore, during road construction layout and longitudinal profile measurement, it is necessary to set additional stakes (additional stakes) near obstacle areas to fill the gaps where full-scale stake points cannot be laid out, ensuring that the longitudinal terrain changes along the road construction route can be completely recorded.

[0004] In traditional methods of determining pile locations, surveyors manually judge the pile positions based on the site topography and their own experience, and determine the standard engineering pile number based on the cumulative mileage of the pile points measured by a tape measure. However, this traditional method, which relies on manual judgment and distance measurement, is prone to significant pile addition errors (such as positional deviations and elevation deviations), thus failing to meet the requirements of modern construction for pile addition accuracy and efficiency. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, device, and computer equipment for adding stakes in obstacle areas during road layout, which eliminates the need for manual data processing, reduces stake addition errors, and thus improves stake addition accuracy and efficiency, in order to address the aforementioned technical problems.

[0006] Firstly, this application provides a method for adding stakes in obstacle zones during road layout, including:

[0007] Based on the original design data of the road, the construction centerline model and longitudinal profile elevation information of the road are determined, and based on the construction centerline model and longitudinal profile design elevation information, the integrated centerline model of the road is determined.

[0008] Based on the integrated centerline model and the feature points corresponding to each obstacle zone pre-collected, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone, and the points to be added are determined based on the distance objective function.

[0009] Based on the integrated centerline model and the location information of each pile to be added, the engineering standard station number of each pile to be added is determined. Based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal profile design elevation information, the pile addition process is carried out on each pile to be added.

[0010] In one embodiment, based on the integrated centerline model and the pre-collected feature points corresponding to each obstacle zone, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone. The points to be added are then determined based on the distance objective function, including:

[0011] For each obstacle region, when the number of feature points corresponding to the obstacle region is at least 3, the least squares method is used to determine the analytical function corresponding to the obstacle region, and the fitted line equation corresponding to the obstacle region is determined based on the analytical function corresponding to the obstacle region.

[0012] Based on the fitted linear equation and the integrated centerline model, the first distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference object of the obstacle zone is determined.

[0013] Based on the first distance objective function, the Brent algorithm is used to determine the number of first intersection points between the fitted straight line and the road centerline within the interval of each line element in the road.

[0014] When a first intersection point is determined to exist, that first intersection point is designated as the point to be added; when multiple first intersection points are determined to exist, the point to be added is determined based on the Euclidean distance between each first intersection point and the center point of the feature point of the obstacle; when no first intersection point is determined to exist, an early warning mechanism is triggered.

[0015] In one embodiment, the method further includes:

[0016] For each obstacle zone, when the number of feature points corresponding to the obstacle zone is 2, the virtual boundary line equation corresponding to the obstacle zone is determined based on the feature points of the obstacle zone.

[0017] Based on the virtual boundary line equation and the integrated centerline model, the second distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference object of the obstacle area is determined.

[0018] Based on the second distance objective function, it is determined whether each line element in the road meets the preset conditions. Based on the second distance objective function, the Brent algorithm is used to determine the number of second intersection points between the virtual boundary line and the road centerline within the interval of each line element that meets the preset conditions. The preset condition is that the product of the second distance objective function value corresponding to the starting point of the line element and the second distance objective function value corresponding to the ending point of the line element has a sign change.

[0019] When a second intersection point is determined to exist, that second intersection point is used as the point to be added as a stake; when multiple second intersection points are determined to exist, the point to be added as a stake is determined based on the Euclidean distance between each second intersection point and the center point of the virtual boundary line.

[0020] In one embodiment, the method further includes:

[0021] For each obstacle region, when the number of feature points corresponding to the obstacle region is 1, candidate line elements are determined based on the bounding boxes corresponding to the feature points of the obstacle region and each line element.

[0022] Based on each candidate line element and the integrated centerline model, a third distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference object of the obstacle area.

[0023] Based on the third distance objective function, the Brent algorithm is used to determine the target local mileage corresponding to each candidate line element within the interval of each candidate line element, and to determine the pile points to be added based on the target local mileage of each candidate line element.

[0024] In one embodiment, the original design data for the road includes road plan drawings, longitudinal profile design data, and digital topographic maps; determining the construction centerline model and longitudinal profile elevation information of the road based on the original design data includes:

[0025] The road plan drawing is analyzed and reconstructed using geometric line extraction, line topology repair, and curvature continuity arbitration algorithms to obtain the centerline geometric model.

[0026] The centerline geometric model and digital topographic map are projected and transformed, and the coordinates of the projected centerline geometric model and digital topographic map are unified to obtain the construction centerline model.

[0027] The longitudinal profile design data is filled in for missing information, and the longitudinal profile design data after missing information filling is then standardized for accuracy to obtain the longitudinal profile elevation information.

[0028] In one embodiment, the engineering standard station number of each pile to be added is determined based on the integrated centerline model and the location information of each pile to be added, including:

[0029] For each pile to be added, the global coordinates and geometric cumulative mileage of the pile to be added are determined based on the integrated centerline model and the location information of the pile to be added.

[0030] The geometric cumulative mileage of the point to be added is matched with the pre-built chain break index table. When it is determined from the matching result that the point to be added belongs to the long chain interval or the short chain interval, the geometric cumulative mileage is corrected based on the chain break difference corresponding to the long chain interval or the short chain interval to obtain the engineering chain number mileage of the point to be added.

[0031] The engineering station number mileage is formatted to obtain the standard engineering station number of the point to be added.

[0032] In one embodiment, the method further includes:

[0033] Based on the construction centerline model, the plane analytical equations of each line element in the road are established using a geometric analytical method;

[0034] The overall plane analytical equation of the road is determined based on the plane analytical equations of each line element. Based on the longitudinal profile design elevation information and the overall plane analytical equations, the centerline integrated model of the road is determined. Specifically, when the line element is a straight line segment, the linear vector equation is used to construct the linear vector equation of the line element; when the line element is a circular curve segment, the standard circle equation is used to construct the plane analytical equation of the line element; and when the line element is a transition curve segment, the plane analytical equation of the line element is constructed based on the spiral curve formula.

[0035] Secondly, this application also provides a device for adding stakes in obstacle areas during road layout, comprising:

[0036] The first determining module is used to determine the construction centerline model and longitudinal profile elevation information of the road based on the original design data of the road, and to determine the integrated centerline model of the road based on the construction centerline model and the longitudinal profile design elevation information.

[0037] The second determination module is used to construct a distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle area based on the integrated centerline model and the pre-collected feature points of each obstacle area, and to determine the pile points to be added based on the distance objective function.

[0038] The pile addition processing module is used to determine the engineering standard station number of each pile to be added based on the integrated centerline model and the location information of each pile to be added, and to perform pile addition processing on each pile to be added based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal profile design elevation information.

[0039] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0040] Based on the original design data of the road, the construction centerline model and longitudinal profile elevation information of the road are determined, and based on the construction centerline model and longitudinal profile design elevation information, the integrated centerline model of the road is determined.

[0041] Based on the integrated centerline model and the feature points corresponding to each obstacle zone pre-collected, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone, and the points to be added are determined based on the distance objective function.

[0042] Based on the integrated centerline model and the location information of each pile to be added, the engineering standard station number of each pile to be added is determined. Based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal profile design elevation information, the pile addition process is carried out on each pile to be added.

[0043] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the following steps:

[0044] Based on the original design data of the road, the construction centerline model and longitudinal profile elevation information of the road are determined, and based on the construction centerline model and longitudinal profile design elevation information, the integrated centerline model of the road is determined.

[0045] Based on the integrated centerline model and the feature points corresponding to each obstacle zone pre-collected, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone, and the points to be added are determined based on the distance objective function.

[0046] Based on the integrated centerline model and the location information of each pile to be added, the engineering standard station number of each pile to be added is determined. Based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal profile design elevation information, the pile addition process is carried out on each pile to be added.

[0047] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, performs the following steps:

[0048] Based on the original design data of the road, the construction centerline model and longitudinal profile elevation information of the road are determined, and based on the construction centerline model and longitudinal profile design elevation information, the integrated centerline model of the road is determined.

[0049] Based on the integrated centerline model and the feature points corresponding to each obstacle zone pre-collected, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone, and the points to be added are determined based on the distance objective function.

[0050] Based on the integrated centerline model and the location information of each pile to be added, the engineering standard station number of each pile to be added is determined. Based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal profile design elevation information, the pile addition process is carried out on each pile to be added.

[0051] Traditional techniques often rely on manual experience and distance measurement for stake addition. Manual experience is highly subjective, and distance measurement is significantly limited by terrain, with issues such as inconsistent horizontality of the measurement path, limited measurement accuracy, and large operator errors, leading to substantial stake addition errors and compromising the accuracy of stake point mileage determination. The proposed method for stake addition in obstacle zones during road layout utilizes an integrated centerline model and pre-collected feature points corresponding to each obstacle zone to construct a distance objective function between mileage parameter points on the integrated centerline model and corresponding reference objects in each obstacle zone. Based on this distance objective function, the method adaptively determines the stake points to be added and calculates their engineering standard station numbers, reducing stake addition errors and improving both accuracy and efficiency. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is an application environment diagram of the obstacle zone staking method in road layout in one embodiment;

[0054] Figure 2 This is a flowchart illustrating the method for adding stakes in the obstacle zone during road layout in one embodiment;

[0055] Figure 3 This is a schematic diagram of the process for determining the piles to be added based on the number of feature points in the obstacle area in one embodiment.

[0056] Figure 4 This is a schematic diagram of obtaining the pile points to be added based on feature points in the obstacle area in one embodiment;

[0057] Figure 5 This is a structural block diagram of a staking device for obstacle zones in road layout, as shown in one embodiment.

[0058] Figure 6 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0059] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0060] The method for adding stakes in obstacle areas during road layout provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or placed on a cloud or other network server. Terminal 102 sends a request to add stakes in obstacle areas during road layout to server 104. Server 104 receives the request, determines the construction centerline model and longitudinal profile elevation information of the road based on the original road design data, and determines the integrated centerline model of the road based on the construction centerline model and the longitudinal profile design elevation information. Based on the integrated centerline model and the pre-collected feature points corresponding to each obstacle area, it constructs a distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle area, and determines the stake points to be added based on the distance objective function. Based on the integrated centerline model and the location information of each stake point to be added, it determines the engineering standard station number of each stake point to be added, and based on the engineering standard station number of each stake point to be added and the design elevation of each stake point to be added determined by the longitudinal profile design elevation information. The terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, and smart in-vehicle systems. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0061] In one exemplary embodiment, such as Figure 2 As shown, a method for adding stakes in obstacle areas during road layout is provided, and this method is applied to... Figure 1 The following steps, from step 202 to step 206, will be used as an example to illustrate the process.

[0062] Step 202: Determine the construction centerline model and longitudinal profile elevation information of the road based on the original design data of the road, and determine the integrated centerline model of the road based on the construction centerline model and the longitudinal profile design elevation information.

[0063] The construction centerline model is a planar geometric model of the road centerline established under a unified coordinate system, which can be composed of line elements such as straight lines, circular curves, and transition curves. The longitudinal profile design elevation information refers to the design elevation data of the road centerline at different mileage positions, used to describe the longitudinal elevation changes along the road direction. The integrated centerline model is a three-dimensional road centerline model.

[0064] Optionally, the original design data for the road includes road plan drawings, longitudinal profile design data, and digital topographic maps. The road plan drawings can be in DWG format. Specifically, the DWG format road design file is obtained, parsed, and the centerline vector information containing line element parameters for straight lines, circular curves, and transition curves is extracted; alternatively, the BIM / LandXML format road design file is obtained, and the data is directly extracted by parsing the XML node tree. <alignment>(Route plane) and <profile>The geometric parameters of the road under the (longitudinal profile) label are further processed by performing line topology repair and other processing based on the extracted geometric parameters to obtain the centerline geometric model. The longitudinal profile design data is an EXCEL design table including the mileage of slope change points, design elevation, longitudinal slope, and vertical curve radius. Further, the longitudinal profile design data may also include a chain break index table and survey area projection deformation parameters. Missing data is filled in and accuracy is standardized to obtain the longitudinal profile elevation information. The digital topographic map is a topographic map of the work area in TIF, SVG, or SHP format, which can overlay the road centerline with the road construction site environment.

[0065] Step 204: Based on the integrated centerline model and the feature points corresponding to each obstacle zone pre-collected, construct the distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone, and determine the pile points to be added based on the distance objective function.

[0066] In this context, the mileage parameter point in the integrated centerline model refers to the parameterized location point on the road centerline determined by mileage parameters within the integrated centerline model, which can be denoted as... For example, for the first Each line element, and the mileage parameter points on it are denoted as... , indicating line element The upper local mileage is The parameterized location point, The coordinates can be derived from the line element. The plane analytical equation is determined.

[0067] Optionally, for sheet-like obstacles such as ponds and soft soil areas, at least two feature points can be collected along the obstacle edge to determine the direction of the obstacle boundary line; for point-like obstacles such as steep slopes and isolated features, a single nearest feature point is collected. An analytical equation or objective function for the virtual obstacle boundary (i.e., the reference object corresponding to the obstacle area) is constructed based on the number of feature points corresponding to the obstacle area. The constructed analytical equation or objective function of the virtual obstacle boundary is then combined with the integrated centerline model to obtain the distance objective function between the mileage parameter points on the integrated centerline model and the reference objects corresponding to each obstacle area.

[0068] Step 206: Based on the integrated centerline model and the location information of each pile to be added, determine the engineering standard station number of each pile to be added, and based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal profile design elevation information, perform pile addition processing on each pile to be added.

[0069] Optionally, based on the objective function of the distance between the mileage parameter points on the integrated centerline model and the corresponding reference objects in each obstacle zone, mileage parameter points that satisfy the constraints are determined. Then, based on these mileage parameter points, the global coordinates and total mileage of the point to be added are determined. The engineering standard station number of the point to be added is determined according to the geometrically accumulated mileage of this point.

[0070] Traditional techniques often rely on manual experience and distance measurement for stake addition. Manual experience is highly subjective, and distance measurement is significantly limited by terrain, with issues such as inconsistent horizontality of the measurement path, limited measurement accuracy, and large operator errors, leading to substantial stake addition errors and compromising the accuracy of stake point mileage determination. The proposed method for stake addition in obstacle zones during road layout utilizes an integrated centerline model and pre-collected feature points corresponding to each obstacle zone to construct a distance objective function between mileage parameter points on the integrated centerline model and corresponding reference objects in each obstacle zone. Based on this distance objective function, the method adaptively determines the stake points to be added and calculates their engineering standard station numbers, reducing stake addition errors and improving both accuracy and efficiency.

[0071] In an exemplary embodiment, the original design data of the road includes road plan drawings, longitudinal profile design data, and digital topographic maps. Determining the construction centerline model and longitudinal profile elevation information of the road based on the original design data includes: parsing and reconstructing the road plan drawings using geometric line extraction, line topology repair, and curvature continuity arbitration algorithms to obtain a centerline geometric model; performing projection transformation on the centerline geometric model and the digital topographic map, and then performing coordinate unification processing on the projected centerline geometric model and the digital topographic map to obtain a construction centerline model; performing missing data completion processing on the longitudinal profile design data, and then performing accuracy standardization processing on the missing data completion processing to obtain longitudinal profile elevation information.

[0072] Optionally, entity extraction and preliminary cleaning are performed on the DWG format road plan drawings. Specifically, the geometric objects in the road plan drawings are traversed, non-skeleton data such as annotations and fill patterns are filtered out, and basic geometric elements such as lines, arcs, polylines and splines are extracted.

[0073] If there are minor breaks in lines in the road plan drawing due to drawing errors, a spatial neighborhood index based on a KD-Tree is established. The start and end endpoints of all line elements are traversed, and the Euclidean distance between each line element and the endpoints of other line elements is calculated. A tolerance threshold is set (e.g., 0.1m). If the determined Euclidean distance d between each line element and the endpoints of other line elements is less than the tolerance threshold, a drawing break is identified, and a virtual link is automatically generated to stitch the two together. If there is a slight overlap, an automatic trimming operation is performed to ensure that the start and end of the line elements are strictly connected, forming a simply connected topological chain.

[0074] When a fork occurs during the search process (i.e., one endpoint of a line element connects to multiple candidate line elements, such as ramp intersections or auxiliary line interference), the curvature continuity arbitration algorithm is activated to automatically determine the main line direction: ① Tangent angle verification (G1 continuity): Calculate the angle between the tangent vector at the end of the current line element and the tangent vector at the beginning of each candidate line element. Prioritize the line element with the smallest angle (i.e., the smoothest direction). ② Curvature abrupt change detection (G2 continuity): For cases where a straight line connects to a circular curve or a circular curve connects to a transition curve, calculate the rate of change of the curvature radius at the connection point. Using the principle of energy minimization, automatically eliminate candidate objects with abrupt changes in curvature (such as sudden right-angle bends or auxiliary lines), and lock the path with the smoothest geometric features as the unique road centerline.

[0075] For the longitudinal profile design data in an Excel spreadsheet format, this Excel spreadsheet contains fixed column names: slope change point mileage (m), design elevation (m), longitudinal slope (%), and vertical curve radius (m). Missing fields in this Excel spreadsheet are supplemented, and the data precision is ensured to retain three decimal places, ultimately yielding the longitudinal profile elevation information. Furthermore, in digital topographic maps in TIF, SVG, or SHP format, the feature coding conforms to GB / T20257.1-2017, the raster map supports GeoTIFF format, the resolution is ≥300 dpi, and the coordinate information is complete.

[0076] The centerline geometric model and the processed digital topographic map are then transformed using the Gauss-Kruger projection with 3° zones. The longitude of the central meridian is determined according to the longitude of the construction area, resulting in the projected centerline geometric model and digital topographic map. The projected centerline geometric model and digital topographic map are then subjected to a seven-parameter transformation method for coordinate unification, including translation, rotation angle, and scale factor, to obtain the construction centerline model.

[0077] In this embodiment, the DWG format road plan drawing is preprocessed to obtain the centerline geometric model; the centerline geometric model is then projected and the coordinates are unified with the digital topographic map to ensure that subsequent calculations are performed in the same coordinate system, thereby ensuring the accuracy of the stake addition.

[0078] In an exemplary embodiment, the method further includes: establishing the plane analytical equations of each line element in the road using a geometric analytical method based on the construction centerline model; determining the plane analytical equations of the entire road based on the plane analytical equations of each line element; and determining the integrated centerline model corresponding to the road based on the longitudinal profile design elevation information and the plane analytical equations of the entire road; wherein, when the line element is a straight line segment, the linear vector equation of the line element is constructed using a linear vector equation; when the line element is a circular curve segment, the plane analytical equation of the line element is constructed using a standard circle equation; and when the line element is a transition curve segment, the plane analytical equation of the line element is constructed based on the spiral curve formula.

[0079] For example, based on the construction centerline model determined above, the polyline elements of the road centerline, i.e., line elements, are read and used as the geometric basis of the road centerline. Corresponding plane analytical equations are established for each line element to eliminate the bow height error caused by the discretization of the polyline elements of the road centerline. Optionally, for line elements of straight lines, linear vector equations are constructed; for line elements of circular curves, standard circular parametric equations are constructed to ensure that any mileage point strictly falls on the circular arc trajectory; for line elements of transition curves, high-precision plane analytical equations are constructed using Fresnel integrals as follows:

[0080] In the above formula, , This indicates the local mileage on the transition curve segment. Local coordinates at that location To mitigate the local mileage parameters (length from the starting point) on the curve. The radius of the circular curve connecting the transition curves. This represents the total length of the transition curve. The variable is the integral variable, representing the change in mileage from the starting point to the calculation point. Numerical solutions are obtained through high-order expansion (keeping up to order 15 and above) to ensure that the first derivative (tangent) and second derivative (curvature) of the model remain continuous in regions with drastic curvature changes, achieving theoretical calculation accuracy at the millimeter level.

[0081] Based on the plane analytical equations corresponding to each line element, the plane analytical equations of the entire road are determined, and the longitudinal profile design elevation information is loaded onto the plane analytical equations of the entire road according to mileage, resulting in an integrated centerline model of the road. This integrated centerline model is an integrated three-dimensional centerline data structure containing "plane coordinates—mileage—design elevation". Furthermore, based on the plane analytical equations corresponding to each line element and the plane analytical equations of the entire road, the cumulative mileage of the boundary points of each line element can be calculated, constructing a dynamic topological index tree of mileage-geometric objects based on analytical length. When subsequent staking calculations are performed, the corresponding analytical equation object can be directly indexed in the dynamic topological index tree of mileage-geometric objects according to the mileage range for accurate iterative solution.

[0082] The pseudocode examples for constructing the overall planar analytical equations of the aforementioned road and modeling the integrated centerline model are as follows: FUNCTION Get_Global_Coordinate(l_local): IF Type IS "LINE": dx = l_local * cos(alpha_start) dy = l_local * sin(alpha_start) ELSE IF Type IS "SPIRAL" (Clothoid): / / Approximating Fresnel integrals using Taylor series / / Calculate the local tangent angle beta = (l_local^2) / (2 * R * Ls) / / Calculate the local coordinates (x_t, y_t) x_t = l_local - (l_local^5) / (40 * R^2 * Ls^2) y_t = (l_local^3) / (6 * R * Ls) - (l_local^7) / (336 * R^3 *Ls^3) / / Rotate and translate to global coordinate system dx = x_t * cos(alpha_start) - y_t * sin(alpha_start) dy = x_t * sin(alpha_start) + y_t * cos(alpha_start) ELSE IF Type IS "CIRCLE": / / Standard circular curve formula (not shown in the code but should usually be included) theta = l_local / R dx = R * sin(theta) dy = R * (1 - cos(theta)) / / Rotation matrix needs to be applied RETURN P_start + (dx, dy) END FUNCTION

[0083] In an exemplary embodiment, before constructing the distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle area based on the integrated centerline model and the pre-collected feature points of each obstacle area, the method further includes: collecting the three-dimensional coordinates P(x, y, z) of at least one feature point on the edge of the obstacle area (such as the waterline of a pond or the edge of a steep embankment).

[0084] Different acquisition strategies are employed for feature points in obstacle areas of different shapes. For example, for sheet-like obstacle areas (such as ponds), multiple feature points P1, P2…Pn are sampled at safe locations along the waterline on both sides of the obstacle area. A virtual boundary line is then defined based on these feature points for intersection method solution or least squares solution fitting. For point-like obstacle areas (such as steep banks), a single feature point P0 is acquired at the nearest safe point in the obstacle area and identified as the target point for geometric projection for projection method solution. The coordinates of the corresponding feature points in each obstacle area are obtained, ensuring that the horizontal precision factor HDOP of the feature point coordinates is ≤1.5.

[0085] In this embodiment, obstacle areas of different shapes (such as linear boundaries, isolated point objects, and surface areas) have different geometric features. By selecting the appropriate sampling strategy to extract feature points based on the physical morphology of the obstacle area, feature points that can characterize the boundary or center position of the obstacle area can be extracted more accurately. This improves the rationality of the objective function construction of the distance between the mileage parameter points on the centerline integrated model and the corresponding reference objects of each obstacle area, as well as the accuracy of the calculation of the pile points to be added, and enhances the adaptability of the method to different construction environments.

[0086] In an exemplary embodiment, based on the integrated centerline model and the pre-collected feature points corresponding to each obstacle zone, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone. Based on the distance objective function, the following steps are taken to determine the additional stake points: For each obstacle zone, when the number of feature points corresponding to the obstacle zone is at least three, the least squares method is used to determine the analytical function corresponding to the obstacle zone, and the fitted line equation corresponding to the obstacle zone is determined based on the analytical function; based on the fitted line equation and the integrated centerline model, a first distance objective function is determined between the mileage parameter points on the integrated centerline model and the corresponding reference objects of the obstacle zone; based on the first distance objective function, the Brent algorithm is used to determine the number of first intersection points between the fitted line and the centerline of the road within the interval of each line element in the road; when a first intersection point is determined to exist, this first intersection point is used as the additional stake point; when multiple first intersection points are determined to exist, the additional stake point is determined based on the Euclidean distance between each first intersection point and the center point of the feature point of the obstacle; when no first intersection point is determined to exist, an early warning mechanism is triggered.

[0087] For example, the process of determining the number of stakes to be added based on the number of feature points in each obstacle zone is as follows: Figure 3 As shown; when there exists an obstacle region Q with a number of feature points greater than or equal to 3 (such as for the edge of an irregular pond), the least squares method is used to construct the analytical function J corresponding to the obstacle region Q, so that the sum of squared longitudinal residuals from all feature points of the obstacle region Q to its fitted line is minimized. The corresponding analytical function J is as follows:

[0088]

[0089] In the above formula, and The parameters of the fitted line corresponding to the obstacle region Q are... The slope The intercept is... and Let N be the coordinates of the i-th feature point in obstacle region Q, and N be the number of feature points corresponding to obstacle region Q.

[0090] Solving for parameters using partial derivatives of zero , The subsequent line-path simultaneous solution is performed. The specific process is as follows:

[0091] a) Equation standardization transformation: The fitted straight line corresponding to the barrier region... general form of the equation of a straight line .in , , .

[0092] b) Intersection of all line elements: Based on the fitted line, traverse all geometric line elements (straight lines, circular curves, transition curves) of the road centerline. For each line element, establish an algebraic distance function (i.e., the first distance objective function). The Brent algorithm is used to search for zero points in the interval [0, L] of the line element, that is, to determine the number of the first intersection points between the fitted line and the centerline of the road.

[0093] c) Multiple-solution arbitration logic (exception handling):

[0094] ① No solution case: If no intersection point is found after traversing all geometric elements of the road centerline ( If there are no real roots, that is, the number of the first intersection points is 0, it is determined that the feature point corresponding to the obstacle area Q is located outside the road range or the fitted line is parallel to the road. The anomaly handling mechanism is triggered and an anomaly warning is sent to the terminal. The terminal prompts "No valid intersection points were detected. Please check whether the sampling position deviates from the road design range" and the current fitting result is automatically discarded.

[0095] ② Multiple solutions: If multiple intersection points P'1, P'2, etc., are found after traversing all geometric elements of the road centerline (common in hairpin bends or ramp areas), i.e., there are multiple first intersection points, the nearest neighbor principle arbitration is initiated. The Euclidean distance from the center point of the obstacle area Q feature point to each first intersection point P'i is calculated, and the first intersection point corresponding to the shortest distance among the above Euclidean distances is selected as the unique valid pile point to be added, ensuring that the layout position is consistent with the construction intention. Figure 1 To.

[0096] In this embodiment, the pseudocode implementation of determining the first intersection point of the fitted line and the road centerline within the interval of each line element in the road using the multi-point fitting method is as follows: ALGORITHM Mode_A_Linear_Fitting_And_Solving INPUT: PointStream: Real-time input point stream (x, y) Threshold_Num: Trigger threshold (CONST = 3) Road_Model: Analytical model of road centerline - integrated centerline model OUTPUT: Target_Point: Final staking point coordinates (P_prime) Target_S: The corresponding geometric mileage (S_geo) STATIC Buffer points_buffer = [] BEGIN LOOP new_pt = Read(PointStream) Append new_pt to points_buffer IF Count(points_buffer) >= Threshold_Num THEN / / --- Phase 1: Least Squares Fitting --- sum_x = 0, sum_y = 0, sum_xx = 0, sum_xy = 0 n = Count(points_buffer) FOR each pt in points_buffer DO sum_x += pt.x sum_y += pt.y sum_xx += (pt.x * pt.x) sum_xy += (pt.x * pt.y) END FOR det_N = (n * sum_xx) - (sum_x * sum_x) / / Special handling of vertical lines IF Abs(det_N) < 1e-9 THEN A_val = 1.0 B_val = 0.0 C_val = -(sum_x / n) ELSE k_val = ((n * sum_xy) - (sum_x * sum_y)) / det_N b_val = ((sum_xx * sum_y) - (sum_x * sum_xy)) / det_N A_val = k_val B_val = -1.0 C_val = b_val END IF / / Goodness-of-fit (RMSE) check sse = 0 FOR each pt in points_buffer DO dist = Abs(A_val*pt.x + B_val*pt.y + C_val) / Sqrt(A_val^2+ B_val^2) sse += dist * dist END FOR rmse = Sqrt(sse / (n - 2)) IF rmse > 0.15 THEN RETURN Warning("Fit Error Too High") / / --- Phase Two: Solving Line-Path Simultaneous Problems --- Line_Eq = Structure(A: A_val, B: B_val, C: C_val) / / Call the core engine to solve for intersection points Intersection_List = Core_Geometric_Solver(Line_Eq, Road_Model) / / --- Phase Three: Multiple Solution Arbitration --- Final_Result = NULL IF Count(Intersection_List) == 0 THEN RETURN Error("No Intersection Found") ELSE IF Count(Intersection_List) == 1 THEN Final_Result = Intersection_List[0] ELSE / / Proximity principle arbitration (among multiple solutions, the nearest one is chosen) Center_X = sum_x / n Center_Y = sum_y / n Min_Dist = Infinity FOR each candidate in Intersection_List DO d = Distance(candidate.Coord, (Center_X, Center_Y)) IF d < Min_Dist THEN Min_Dist = d Final_Result = candidate END IF END FOR END IF RETURN Final_Result.Coord, Final_Result.S_geo END IF END LOOP END ALGORITHM

[0097] In the previous exemplary embodiment, the method further includes: for each obstacle zone, when the number of feature points corresponding to the obstacle zone is 2, determining the virtual boundary line equation corresponding to the obstacle zone based on the feature points of the obstacle zone; determining the second distance objective function between the mileage parameter points on the integrated centerline model and the reference object corresponding to the obstacle zone based on the virtual boundary line equation and the integrated centerline model; determining whether each line element in the road meets the preset conditions based on the second distance objective function, and determining the number of second intersection points between the virtual boundary line and the centerline of the road in the interval of each line element that meets the preset conditions using the Brent algorithm based on the second distance objective function; wherein, the preset condition is that the product of the second distance objective function value corresponding to the starting point of the line element and the second distance objective function value corresponding to the ending point of the line element has a sign change; when it is determined that there is a second intersection point, the second intersection point is used as a stake point to be added; when it is determined that there are multiple second intersection points, the stake point to be added is determined according to the Euclidean distance between each second intersection point and the center point of the virtual boundary line.

[0098] Optionally, such as Figure 4 The diagram illustrates the acquisition of additional stakes based on feature points within an obstacle zone. When an obstacle zone W corresponds to two feature points, a two-point intersection method is used: the linear equations of feature points P1 and P2 are constructed, i.e., the equation of the virtual boundary line corresponding to the obstacle zone is constructed; and the intersection point (i.e., the second intersection point) between this virtual boundary line and the integrated centerline model is calculated. The specific solution process is as follows:

[0099] a) Constructing the virtual boundary line equation: Based on the coordinates of the feature points P1 and P2 corresponding to the obstacle area W, construct the general equation of the straight virtual boundary line L: Ax + By + C = 0.

[0100] like =0.01m (determining the virtual boundary line to be a straight line perpendicular to the road centerline), then , , If it is a straight line with a normal slope, then:

[0101]

[0102] , , ;in, , and , These are the horizontal and vertical coordinates of two feature points corresponding to obstacle zone B.

[0103] b) Establish the distance objective function: For each line element (Line / Curve / Spiral) in the road, define any point on that line element. The algebraic distance function (i.e., the second distance objective function) to the virtual boundary line L is:

[0104]

[0105] c) Line element traversal and root value solution: Traverse all line elements of the road centerline and perform a zero-point search for each line element. Interval check: Based on the second distance objective function, calculate the starting point of each line element. and the end point function value at and .like Furthermore, if the line element is a monotonic geometric body (such as a straight line), that is, if the preset condition is not met, it is skipped (indicating no zero point, i.e., no second intersection point). For precise solution: if there is a sign change (i.e., crossing a zero point), that is, if the preset condition is met, then the Brent algorithm is called to solve the equation within the line element interval [0, L] that satisfies the preset condition. root The maximum number of iterations is 50.

[0106] d) Validity verification and coordinate output: If the solution is successful ( Then calculate the corresponding global coordinates P' and the total mileage St. If there are multiple second intersection points (such as ramps or hairpin bends) on the centerline of the entire road, calculate the distance from the center point of the virtual boundary line to each second intersection point, and take the second intersection point with the closest distance as the valid stake point.

[0107] The pseudocode implementation of the above intersection algorithm is as follows: FUNCTION Solve_Intersection_Two_Points(P1, P2, Segments): / / 1. Construct the virtual boundary equation Ax + By + C = 0 IF |P2.x - P1.x| < epsilon THEN / / Vertical line case A = 1, B = 0, C = -P1.x ELSE k = (P2.y - P1.y) / (P2.x - P1.x) A = k, B = -1, C = P1.y - k * P1.x END IF / / 2. Traverse line elements to find intersection points FOR EACH segment IN Segments DO: / / Define the algebraic distance function: the "distance" from a point on a road to a line. DEFINE function Dist_Func(l): P_road = segment.Get_Global_Coordinate(l) RETURN A * P_road.x + B * P_road.y + C / / Sign test: Check whether the two ends of the line element cross a straight line (whether they have opposite signs). val_start = Dist_Func(0) val_end = Dist_Func(segment.Length) IF val_start * val_end <= 0 THEN / / There is a zero point; use Brent's method to find the root. l_root = Brent_Solver(Dist_Func, Range=[0,segment.Length]) / / Calculation results P_prime = segment.Get_Global_Coordinate(l_root) S_total = segment.Start_Mileage + l_root RETURN (P_prime, S_total) END IF END FOR RETURN NULL / / No intersection found END FUNCTION

[0108] In the previous exemplary embodiment, the method further includes: for each obstacle zone, when the number of feature points corresponding to the obstacle zone is 1, determining candidate line elements based on the feature points of the obstacle zone and the bounding boxes corresponding to each line element; constructing a third distance objective function between the mileage parameter points on the integrated centerline model and the reference object corresponding to the obstacle zone based on each candidate line element and the integrated centerline model; and using the third distance objective function, determining the target local mileage corresponding to each candidate line element within the interval of each candidate line element using the Brent algorithm, and determining the stake points to be added based on the target local mileage of each candidate line element.

[0109] When there is one feature point corresponding to an obstacle zone E, the perpendicular projection method is used. For example, when there is one feature point corresponding to obstacle zone E, nearest neighbor reference positioning is initiated. This mode is suitable for scenarios where precise boundary orientation is not required, but only the centerline station corresponding to the current location needs to be obtained (such as a rough reconnaissance or assuming the obstacle boundary is perpendicular to the centerline). Through a geometric projection algorithm, the shortest Euclidean distance from the feature point corresponding to obstacle zone E to the centerline and its corresponding perpendicular mileage are calculated as the reference benchmark for the station to be added. The specific calculation process is as follows:

[0110] a) Line element traversal and initial screening: Each line element object in the integrated midline model is read sequentially. To improve computational efficiency, the feature points corresponding to obstacle region E are first calculated. If the distance to the bounding box or start / end point of a line element is significantly greater than the currently known minimum distance threshold, then skip that line element. Iterate through all line elements and assign the feature points corresponding to the obstacle region E. Line elements whose distance to the bounding box or start and end points is less than a distance threshold are considered as candidate line elements, and only candidate line elements are subjected to fine calculation.

[0111] b) Construct the distance objective function: For each candidate line element, define the objective function (i.e., the third distance objective function). , representing the feature points corresponding to obstacle region E The mileage to the candidate line element is point Squared Euclidean distance:

[0112]

[0113] in, For the integrated model of the centerline at local mileage The coordinate function at that location The mileage parameters are determined based on the integrated centerline model and are to be determined. The corresponding road centerline coordinate vector.

[0114] c) Perform bounded extremum search: Call the minimize_scalar function in the scipy.optimize library and use the Brent algorithm to search for the minimum value within the mileage domain [0, Ls] defined by each candidate line element. Minimum local mileage That is, to determine the target local mileage corresponding to each candidate line element.

[0115] d) Determining the optimal solution across the entire line: Compare the target local mileage calculated from all candidate line elements, and select the line element with the smallest target local mileage and its corresponding local mileage. As a final result, the global coordinates of the perpendicular point P' are calculated using the analytical equation of the line element corresponding to the local minimum mileage of the target.

[0116] The pseudocode implementation of the perpendicular projection algorithm described above is as follows: FUNCTION Find_Projection_Point(P0, Segments): Global_Min_Dist = Infinity Best_Result = NULL FOR EACH segment IN Segments DO: / / Define the objective function: the squared Euclidean distance from the feature point to the road point DEFINE function Objective_Func(l): P_road = segment.Get_Global_Coordinate(l) RETURN (P_road.x - P0.x)^2 + (P_road.y - P0.y)^2 / / Use a bounded extremum search algorithm to find a local minimum distance / / bounds are limited to the current line element length. Result = Bounded_Minimization(Objective_Func, Bounds=[0,segment.Length]) IF Result.Value < Global_Min_Dist THEN Global_Min_Dist = Result.Value l_opt = Result.Location P_prime = segment.Get_Global_Coordinate(l_opt) S_total = segment.Start_Mileage + l_opt Best_Result = (P_prime, S_total, Sqrt(Global_Min_Dist)) END IF END FOR RETURN Best_Result END FUNCTION

[0117] In this embodiment, the reference object corresponding to each obstacle zone is determined based on the number of feature points corresponding to each obstacle zone, and the objective function of the distance between the mileage parameter points on the integrated centerline model and the reference objects corresponding to each obstacle zone is determined. This makes the expressive power of the distance objective function match the geometric information dimension of the obstacle zone, improves the accuracy of the obstacle zone representation, and enables the optimal mileage parameter points obtained from the solution to more accurately reflect the spatial relationship between the road centerline and the obstacle zone. This ensures the rationality of the location of the pile to be added, reduces pile addition errors, and improves pile addition accuracy and efficiency.

[0118] In an exemplary embodiment, the engineering standard station number of each station to be added is determined based on the integrated centerline model and the location information of each station to be added, including: for each station to be added, determining the global coordinates and geometric cumulative mileage of the station to be added based on the integrated centerline model and the location information of the station to be added; matching the geometric cumulative mileage of the station to be added with a pre-built chain break index table; when it is determined based on the matching result that the station to be added belongs to a long chain interval or a short chain interval, correcting the geometric cumulative mileage based on the chain break difference corresponding to the long chain interval or the short chain interval to obtain the engineering station number mileage of the station to be added; and performing station number formatting processing on the engineering station number mileage to obtain the engineering standard station number of the station to be added.

[0119] Mileage value extraction and validity verification: After determining the points to be added in the previous embodiment, St is determined for each point to be added. St is a double-precision floating-point number (float64), representing the absolute cumulative mileage of the point to be added relative to the starting point of the entire road. The entire mileage range of the integrated centerline model is automatically read and boundary verification is performed. If St < 0 or St is greater than the entire mileage of the integrated centerline model, the point to be added is marked as mileage overflow (Out of Bounds), and resampling is prompted.

[0120] For example, due to road design changes often resulting in station equivalence, the geometric cumulative mileage S of the points to be added is often not equal to the design station number. The database stores a broken chain table, which contains the geometric mileage, preceding station number, and following station number of the broken chain point.

[0121] a) Chain break interval location: For each pile to be added, the geometric mileage S of the pile to be added is compared with the chain break index table to determine the chain number interval to which the pile to be added belongs.

[0122] b) Calculation of long and short chains:

[0123] ① If the point to be added belongs to a long chain section (chainage number after chain break < chainage number before chain break): ;

[0124] ②If the point to be added belongs to a short chain interval (chainage number after chain break > chainage number before chain break): .

[0125] in, It is the search step increment, which refers to the unit of length by which the mileage increases in each iteration; This represents the total cumulative offset, which is the algebraic sum of all step increments.

[0126] c) Uniqueness verification: If the geometric mileage S of the point to be added falls into the overlapping interval (caused by a short chain), a second verification is performed based on the geometric coordinates of the corresponding feature point of the point to be added and the spatial relationship between the broken chain point to ensure the uniqueness of the output station number.

[0127] Formatting of station number strings: For each station to be added It calls the string formatting algorithm and executes the thousands truncation algorithm.

[0128] a) Rounding down: For Round down to the nearest 1000 to get the kilometer number K.

[0129] b) Modulo: For Taking the remainder of 1000, we get the distance in meters, M.

[0130] c) Concatenation: Concatenate K and M (keeping 3 decimal places) into the standard format string K+M to obtain the standard station number of the pile to be added.

[0131] In this embodiment, the pseudocode for determining the engineering standard station number of the pile to be added is implemented as follows: / / Global Configuration: Projection Overall Deformation Scale Factor (set according to the altitude of the survey area, default 1.0) CONST PROJECT_SCALE_FACTOR = 1.000345 FUNCTION Generate_Stake_Task(P_prime, S_geo_total, BrokenChainTable): / / 1. Projection distortion correction (critical repair point) / / Convert analytical geometric mileage (map distance) to measured ground mileage (ground distance) S_Ground_Corrected = S_geo_total * PROJECT_SCALE_FACTOR / / 2. Broken link correction (Station Equation) / / Use corrected ground mileage to determine chain break intervals / / BrokenChainTable: {Geo_Mileage, Ahead_Station, Back_Station} Total_Shift = 0.0 FOR each Eq in BrokenChainTable DO / / Determine if the link has been broken IF S_Ground_Corrected >= Eq.Geo_Mileage THEN / / Calculate the displacement: (Rear station number - Front station number) / / Long chains (Gap) are negative values, short chains (Overlap) are positive values. Shift = Eq.Back_Station - Eq.Ahead_Station Total_Shift += Shift END IF END FOR / / Obtain the final engineering station number value used for display Final_Station_Val = S_Ground_Corrected + Total_Shift / / 3. String Formatting (K+M) KM_Part = Floor(Final_Station_Val / 1000) M_Part = Final_Station_Val MOD 1000 Str_Stn = Sprintf("K%d+%07.3f", KM_Part, M_Part) / / 4. Task Package Construction Task_Payload = { "id": Generate_UUID(), "type": "OBSTACLE_STAKE", "station_label": Str_Stn, "geo_mileage": Round(S_geo_total, 4), / / Internal geometry reference "ground_mileage": Round(S_Ground_Corrected, 4), / / Actual ground reference "coordinate": { "x": Round(P_prime.x, 4), "y": Round(P_prime.y, 4) } } RETURN Task_Payload END FUNCTION

[0132] Lofting Task Construction and Queue Push: The calculation results are encapsulated into a standard lofting task object. This object contains a unique task ID, station string, theoretical coordinates (x', y'), design elevation index key, and other information. This object is pushed into the runtime task queue, and a corresponding list of items to be lofted is generated, marked as pending execution, and sent to the terminal interface for display.

[0133] In this embodiment, by matching the geometric cumulative mileage of the point to be added with the chainage index table, and correcting the geometric cumulative mileage of the point to be added according to the matching result, the accurate mapping between the geometric cumulative mileage of the point to be added and the engineering chainage system can be achieved, thereby ensuring the consistency between the mileage of the added point and the standard chainage of the project, and improving the accuracy and generalization ability of the determination of the added point under complex chainage conditions.

[0134] In an exemplary embodiment, the method further includes guided stakeout and ground elevation measurement. In this step, the server receives real-time location information uploaded by the terminal, generates navigation instructions for each stake point to be added based on the coordinates of the stake point, the engineering standard station number, and the real-time location information of the terminal, and sends the navigation instructions to the terminal; when the terminal reaches the target location (i.e., the stake point to be added), the server receives real-time ground elevation information uploaded by the terminal, determines the design elevation of the stake point to be added based on the longitudinal profile design elevation information and the real-time ground elevation information, and sends the determined design elevation of the stake point to the terminal to complete the stake addition process of the stake point to be added.

[0135] Alternatively, this step can also be performed collaboratively by the terminal's guidance and interaction module and the longitudinal elevation interpolation and cut-and-fill analysis unit. For example, the server transmits the determined coordinates of the points to be added and the engineering standard station number to the terminal. The terminal generates navigation instructions based on these coordinates, the engineering standard station number, and the terminal's current location, completing the closed-loop operation of measurement-calculation-storage. Specifically, this includes:

[0136] 1) Polar coordinate navigation calculation and visualization guidance:

[0137] a) The current rover coordinates Pc are output by the GNSS module built into the terminal at a frequency of 5Hz.

[0138] b) The central processing module inside the terminal calculates in real time the navigation vector pointing from the current position Pc to the point P'(x', y') to be added as a stake:

[0139]

[0140]

[0141] c) The terminal combines the built-in electronic compass and IMU attitude data to draw dynamic guide arrows on the terminal screen.

[0142] d) Interaction logic: When the distance D > 2.0m, a thick guide arrow is displayed (indicating the general direction); when D ≤ 0.5m, it automatically switches to the target fine-tuning mode, displaying centimeter-level deviation values. .

[0143] 2) Ground Elevation Measurement and Ephemeris Smoothing: After the personnel move the handheld terminal into position and level the centering pole, they click the [Measure] button. The terminal automatically executes the elevation smoothing acquisition logic: it continuously reads the elevation data Hi of 10 fixed solution epochs, removes the maximum and minimum values, and takes the arithmetic mean to obtain the high-precision measured ground elevation Ha.

[0144] 3) Design Elevation Interpolation and Automatic Cut / Fill Calculation: The terminal retrieves adjacent slope change points in the longitudinal profile design model based on the mileage K+M (standard engineering station number) of the point to be added. Vertical Curve Correction Logic: If the mileage K+M of the point to be added is within the vertical curve range, the quadratic parabola correction formula is called to calculate the elevation correction. Differential Calculation: The final cut / fill volume ΔH = Hb - Ha is calculated.

[0145] 4) Results Data Encapsulation and Persistent Storage: The terminal encapsulates the calculation results into a JSON object, including the status bit is_filled (whether the square is filled), and generates a standard stakeout record to be stored in the SQLite database. A highlighted prompt box pops up on the screen: Recommendation: Enter 0.85m.

[0146] In this step, the pseudocode implementation for longitudinal profile elevation calculation and cut / fill analysis is as follows: FUNCTION Compute_Cut_Fill(S, H_ground, ProfileData): / / 1. Locate adjacent slope change points (VPIs) Index = Find_Index(ProfileData.Mileage, S) VPI_prev = ProfileData[Index - 1] / / 2. Calculate the tangent elevation of the straight slope section Dist_X = S - VPI_prev.Mileage H_tangent = VPI_prev.Elevation + Dist_X * VPI_prev.Slope / / 3. Vertical Curve Parabola Correction H_design = H_tangent R = VPI_prev.Radius IF R > 0 THEN / / Calculate the tangent length T Slope_Diff = Abs(ProfileData[Index].Slope - VPI_prev.Slope) T = R * Slope_Diff / 2.0 Dist_to_VPI = Abs(S - VPI_prev.Mileage) / / If within the range of the vertical curve, apply the corrected formula y = x^2 / 2R IF Dist_to_VPI <= T THEN Correction = (Dist_to_VPI^2) / (2 * R) / / Determine the symbol for a convex (Crest) or concave (Sag) curve IF VPI_prev.Slope < ProfileData[Index].Slope THEN Sign = 1 / / Concave shape, corrected upwards ELSE Sign = -1 / / Convex shape, correct downwards END IF H_design = H_design + Sign * Correction END IF END IF / / 4. Calculate cut and fill volumes Cut_Fill = H_design - H_ground RETURN (H_design, Cut_Fill) END FUNCTION

[0147] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0148] Based on the same inventive concept, this application also provides a road layout obstacle area staking device for implementing the above-described road layout obstacle area staking method. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more road layout obstacle area staking device embodiments provided below can be found in the above-described limitations of the road layout obstacle area staking method, and will not be repeated here.

[0149] In one exemplary embodiment, such as Figure 5 As shown, a staking device for obstacle zones in road layout is provided. The device's physical architecture includes a central processing unit (CPU), non-volatile memory, a high-precision GNSS positioning board, a human-machine interface module, and a power management unit, all connected via a system bus. The high-precision GNSS positioning board integrates a multi-frequency, multi-satellite receiver, connected to the CPU via a UART or SPI interface, and is configured to output raw observation data in NMEA format at a frequency of at least 5Hz, supporting real-time calculation of RTK differential data. The CPU is the core of the computation and control, configured to run an embedded operating system and execute geometric calculation instructions, supporting floating-point operations (FPU) to meet the millisecond-level solution requirements of nonlinear equations. The CPU implements the operation of the following functional modules by calling computer program instructions stored in the non-volatile memory:

[0150] a) A first determination module, used to determine the construction centerline model and longitudinal profile elevation information of the road based on the original design data, and to determine the integrated centerline model of the road based on the construction centerline model and the longitudinal profile design elevation information. This first determination module includes a multi-source data fusion storage engine configured to establish a hierarchical spatial database for storing and managing multi-source heterogeneous data. Specifically, it includes:

[0151] ① Bottom layer environmental data: used to store large-capacity digital topographic maps (GeoTIFF / SHP), and to achieve fast indexing of local area elevation data through direct memory access (DMA) technology;

[0152] ②Middle-layer design data layer: used to store the parsed road centerline topology model and longitudinal profile design parameter table;

[0153] ③ Top-level dynamic data layer: used for real-time caching of the time-series coordinate stream and sampled feature point data output by the GNSS receiver.

[0154] b) The second determination module is used to construct a distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle area based on the integrated centerline model and the feature points corresponding to each obstacle area collected in advance, and to determine the pile points to be added based on the distance objective function; wherein, the second determination module includes an adaptive feature sampling and recognition module, which is configured to perform pattern recognition and preprocessing on the discrete coordinate points collected on site.

[0155] ① Sampling mode adaptive logic: This module is configured to monitor the number of input feature points (N) in real time and automatically switch the solution strategy according to the value of N: when N=1, the perpendicular projection operator is activated; when N=2, the linear intersection operator is activated.

[0156] ② Data cleaning logic: Built-in GDOP (Geometric Precision Factor) threshold ≤ 2.0 judgment program, configured to automatically remove sampling data with non-fixed positioning status or exceeding precision limits.

[0157] c) The pile addition processing module is used to determine the engineering standard station number of each pile to be added based on the integrated centerline model and the location information of each pile to be added, and to perform pile addition processing on each pile to be added based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal profile design elevation information; wherein, the pile addition processing module includes a core geometric solution engine, which is the computing center of the device and is configured to perform the solution of the core mathematical model:

[0158] ① Spatial registration unit: configured to convert the WGS-84 coordinates acquired by GNSS into engineering independent coordinate system coordinates in real time, and spatially overlay them with the CAD analytical model;

[0159] ② Hybrid solution unit: configured to simultaneously solve obstacle boundary equations (linear or nonlinear fitting equations) and road centerline analytical equations (high-order curve equations including Fresnel integrals), and use Brent's Method to search for numerical solutions within the preset mileage domain, outputting unique theoretical staking point coordinates and corresponding mathematical mileage.

[0160] d) Immersive Lofting Guidance Module: This module is configured to provide multi-dimensional physical feedback through a human-computer interaction module.

[0161] ①Visual guidance unit: Configured to dynamically render the deviation between the current position vector and the theoretical pile point vector on the display screen, and generate directional guidance arrows and remaining distance values;

[0162] ② Tactile feedback control unit: configured to send a pulse signal to drive the linear motor to generate vibration feedback when the calculated plane deviation is less than a preset threshold (e.g., 0.2m), thereby enabling blind operation prompts.

[0163] e) Data Closed-Loop and Result Management Module: This module is configured to perform correlation calculations and persistent encapsulation of data.

[0164] ① Cut and Fill Analysis Unit: Configured to design the elevation based on the longitudinal profile of the solved mileage index, and perform differential calculation with the measured ground elevation to generate cut and fill instructions;

[0165] ② Encrypted storage unit: configured to encapsulate "sampling features - calculation process - layout results" into tamper-proof binary data packets, and support uploading to the cloud server via wireless communication interface to realize full-process closed-loop traceability of construction data.

[0166] Considering the diversity of actual engineering scenarios, the device of the present invention can also be implemented in the form of a general-purpose smart terminal + external / built-in high-precision positioning module.

[0167] 1) General-purpose computing platform: The central processing module and human-computer interaction module can be implemented using existing high-performance smartphones, industrial tablets, or PDA handhelds. The computer program (APP) is installed in the operating system (such as Android / iOS / HarmonyOS) of this general-purpose terminal, and uses the terminal's built-in CPU and GPU to perform the aforementioned multi-source data fusion, geometric calculation, and graphics rendering tasks.

[0168] 2) Positioning module adaptation method:

[0169] Method 1 (External): For general-purpose mobile phones / tablets that do not have RTK calculation capabilities, the device connects to an external high-precision GNSS receiver via a wireless communication interface (Bluetooth / WiFi) or a physical interface (Type-C / OTG). The general-purpose terminal receives the NMEA differential positioning data stream output by the external receiver as the system's position input.

[0170] Method 2 (Built-in): For industrial-grade tablets or surveying handheld devices with high-precision positioning capabilities, directly call their built-in GNSS board interface to obtain fixed solution coordinates.

[0171] The various modules in the obstacle zone staking device described above for road layout can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0172] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The database stores the original road design data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a method for adding stakes in obstacle areas during road layout.

[0173] Those skilled in the art will understand that Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0174] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0175] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0176] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0177] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0178] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0179] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0180] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.< / profile> < / alignment>

Claims

1. A method for adding stakes in obstacle areas during road layout, characterized in that, The method includes: The construction centerline model and longitudinal profile elevation information of the road are determined based on the original design data of the road, and the integrated centerline model of the road is determined based on the construction centerline model and the longitudinal profile design elevation information. Based on the integrated centerline model and the feature points corresponding to each obstacle zone pre-collected, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the reference objects corresponding to each obstacle zone, and the points to be added are determined based on the distance objective function. Based on the integrated centerline model and the location information of each pile to be added, the engineering standard station number of each pile to be added is determined, and based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal section design elevation information, pile addition processing is performed on each pile to be added.

2. The method according to claim 1, characterized in that, Based on the integrated centerline model and the pre-collected feature points corresponding to each obstacle zone, a distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle zone. The points to be added are then determined based on the distance objective function, including: For each obstacle region, when the number of feature points corresponding to the obstacle region is at least 3, the least squares method is used to determine the analytical function corresponding to the obstacle region, and the fitted line equation corresponding to the obstacle region is determined based on the analytical function corresponding to the obstacle region. Based on the fitted straight line equation and the integrated centerline model, a first distance objective function is determined between the mileage parameter points on the integrated centerline model and the corresponding reference object of the obstacle zone. Based on the first distance objective function, the Brent algorithm is used to determine the number of first intersection points between the fitted straight line and the centerline of the road within the interval of each line element in the road; When a first intersection point is determined to exist, that first intersection point is designated as the point to be added; when multiple first intersection points are determined to exist, the point to be added is determined based on the Euclidean distance between each first intersection point and the center point of the feature point of the obstacle; when no first intersection point is determined to exist, an early warning mechanism is triggered.

3. The method according to claim 2, characterized in that, The method further includes: For each obstacle zone, when the number of feature points corresponding to the obstacle zone is 2, the virtual boundary line equation corresponding to the obstacle zone is determined based on the feature points of the obstacle zone. Based on the virtual boundary line equation and the integrated centerline model, a second distance objective function is determined between the mileage parameter points on the integrated centerline model and the corresponding reference object of the obstacle zone. Based on the second distance objective function, it is determined whether each line element in the road meets the preset conditions. Based on the second distance objective function, the Brent algorithm is used to determine the number of second intersection points between the virtual boundary line and the centerline of the road within the interval of each line element that meets the preset conditions. The preset conditions are that the product of the second distance objective function value corresponding to the starting point of the line element and the second distance objective function value corresponding to the ending point of the line element has a sign change. When a second intersection point is determined to exist, that second intersection point is used as the point to be added as a stake; when multiple second intersection points are determined to exist, the point to be added as a stake is determined based on the Euclidean distance between each second intersection point and the center point of the virtual boundary line.

4. The method according to claim 2, characterized in that, The method further includes: For each obstacle region, when the number of feature points corresponding to the obstacle region is 1, candidate line elements are determined based on the bounding boxes corresponding to the feature points of the obstacle region and each line element. Based on each candidate line element and the integrated centerline model, a third distance objective function is constructed between the mileage parameter points on the integrated centerline model and the corresponding reference object of the obstacle zone. Based on the third distance objective function, the Brent algorithm is used to determine the target local mileage corresponding to each candidate line element within the interval of each candidate line element, and to determine the pile points to be added based on the target local mileage of each candidate line element.

5. The method according to claim 1, characterized in that, The original design data of the road includes road plan drawings, longitudinal profile design data, and digital topographic maps; the determination of the construction centerline model and longitudinal profile elevation information of the road based on the original design data includes: The road plan drawing is analyzed and reconstructed using geometric line extraction, line topology repair, and curvature continuity arbitration algorithms to obtain the centerline geometric model. The centerline geometric model and the digital topographic map are projected and transformed, and the coordinates of the projected centerline geometric model and the digital topographic map are unified to obtain the construction centerline model. The longitudinal profile design data is filled in for missing information, and the longitudinal profile design data after missing information filling is then standardized for accuracy to obtain longitudinal profile elevation information.

6. The method according to claim 1, characterized in that, The determination of the engineering standard station number of each pile to be added based on the integrated centerline model and the location information of each pile to be added includes: For each pile to be added, the global coordinates and geometric cumulative mileage of the pile to be added are determined based on the integrated centerline model and the location information of the pile to be added. The geometric cumulative mileage of the point to be added is matched with a pre-built chain break index table. When the matching result determines that the point to be added belongs to a long chain interval or a short chain interval, the geometric cumulative mileage is corrected based on the chain break difference corresponding to the long chain interval or short chain interval to obtain the engineering station mileage of the point to be added. The engineering mileage is formatted to obtain the standard engineering mileage of the point to be added.

7. The method according to claim 1, characterized in that, The method further includes: Based on the construction centerline model, the plane analytical equations of each line element in the road are established using a geometric analytical method; Based on the plane analytical equations of each line element, the plane analytical equation of the entire road is determined. Based on the longitudinal profile design elevation information and the plane analytical equation of the entire road, the integrated centerline model corresponding to the road is determined. Specifically, when the line element is a straight line segment, the linear vector equation of the line element is constructed using linear vector equations; when the line element is a circular curve segment, the plane analytical equation of the line element is constructed using standard circle equations; and when the line element is a transition curve segment, the plane analytical equation of the line element is constructed based on the spiral curve formula.

8. A device for adding stakes in obstacle areas during road layout, characterized in that, The device includes: The first determining module is used to determine the construction centerline model and longitudinal profile elevation information of the road based on the original design data of the road, and to determine the integrated centerline model of the road based on the construction centerline model and the longitudinal profile design elevation information. The second determining module is used to construct a distance objective function between the mileage parameter points on the integrated centerline model and the corresponding reference objects of each obstacle area based on the integrated centerline model and the pre-collected feature points of each obstacle area, and to determine the pile points to be added based on the distance objective function. The pile addition processing module is used to determine the engineering standard station number of each pile to be added based on the integrated centerline model and the location information of each pile to be added, and to perform pile addition processing on each pile to be added based on the engineering standard station number of each pile to be added and the design elevation of each pile to be added determined by the longitudinal section design elevation information.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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