Tunnel sideline automatic generation and topological relation processing method based on traverse point data

Abstract

The invention relates to the technical field of mine roadway sideline generation, in particular to a roadway sideline automatic generation and topological relation processing method based on traverse point data, and the method comprises the steps: S1, generating a sideline of a target roadway based on traverse point data; s2, in the side line extending process of the target roadway, if the target roadway intersects with other roadways, the step S3 is executed; if shielding exists between the roadway and other roadways, the step S4 is executed; s3, adjusting the side boundary of the target roadway in real time through a roadway intersection processing algorithm; s4, adjusting the side boundary of the target roadway in real time through a roadway shielding processing algorithm; and S5, repeating the steps S2 to S4 until the sideline of the target roadway is drawn. By processing roadway intersection and roadway shielding in the roadway sideline drawing process in real time, the mine roadway sideline generation quality and accuracy are improved.

Description

Technical Field

[0001] This invention relates to the field of mine roadway edge generation technology, specifically to a method for automatic generation of roadway edges and topology processing based on traverse point data. Background Technology

[0002] In the field of mining and production management, accurate mine roadway modeling is of paramount importance. It serves not only as a crucial basis for mine planning, design, and construction, but also provides intuitive and accurate data support for mine production scheduling, safety monitoring, and resource assessment.

[0003] In the actual process of drawing tunnel edge lines, especially when dealing with complex three-dimensional spatial relationships, there are many problems that need to be solved. Among them, the problem of missing three-dimensional topology, especially the loss of elevation topology information, is particularly prominent.

[0004] In a mine roadway system, roadways exhibit numerous intersections. Roadways of different directions and heights intersect, forming a complex three-dimensional network structure. Traditional methods for drawing roadway boundaries often handle intersections in a simplistic and crude manner, typically connecting them using a two-dimensional planar approach while ignoring vertical elevation differences. This results in roadway boundary lines that fail to accurately reflect the true spatial morphology and topological relationships at intersections. The loss of elevation and topological information not only affects the accuracy of the roadway model in three-dimensional space but also misleads subsequent model-based analyses of roadway ventilation, transportation, and other aspects, reducing the reliability of the analysis results.

[0005] Furthermore, occlusion is a common problem in mine roadways. Due to the complex and varied orientation of roadways, some roadways may be obscured by others. Current roadway boundary mapping techniques lack effective methods for handling occlusion. When roadway occlusion is encountered, the obscured portion is simply ignored, or inappropriate approximations are used. As a result, important topological information, such as the elevation of the obscured roadway and its relative position to the obscuring roadway, is lost.

[0006] In summary, existing methods for drawing mine roadway edges suffer from serious 3D topological deficiencies when dealing with roadway intersections and occlusions, especially the loss of elevation topological information, which greatly limits the accuracy and quality of mine roadway edge generation. Summary of the Invention

[0007] To address the shortcomings of the existing technologies, the technical problem to be solved by this invention is: how to provide a method for automatically generating roadway edges and processing topological relationships based on traverse point data, thereby improving the quality and accuracy of mine roadway edge generation by real-time processing of roadway intersections and roadway occlusions during the roadway edge drawing process.

[0008] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0009] A method for automatic generation of roadway edges and processing of topological relationships based on traverse point data includes:

[0010] S1: Generate the edge line of the target tunnel based on the traverse point data;

[0011] S2: During the extension of the target roadway's edge, determine whether the target roadway intersects with or is obstructed by other roadways: if it intersects with other roadways, proceed to step S3; if it is obstructed by other roadways, proceed to step S4.

[0012] S3: Adjust the edge line of the target tunnel in real time through the tunnel intersection processing algorithm;

[0013] S4: Adjust the edge line of the target lane in real time through the lane occlusion processing algorithm;

[0014] S5: Repeat steps S2 to S4 until the edge line of the target tunnel is drawn.

[0015] Preferably, in step S1, the edge line of the target tunnel is drawn through the following steps:

[0016] S101: Obtain the traverse point data of the target roadway, as well as the width of the left and right sidewalls;

[0017] S102: Generate the side lines and center lines of the target roadway using the traverse point data and the widths of the left and right side lines;

[0018] S103: Based on the side line and center line, the perpendicular foot is calculated using polar coordinates, and the coordinates of the two side line points are calculated using the outward expansion method;

[0019] S104: Determine if the radius of the centerline of the target roadway is 0: if yes, proceed to step S107; otherwise, proceed to step S105.

[0020] S105: Determine the bending direction of the edge line: If the radius is a positive radius, the edge line bends clockwise; if the radius is a negative radius, the edge line bends counterclockwise.

[0021] S106: Calculate the arcs between the two guide points and obtain the arc edges on the left and right sides through the outward expansion algorithm;

[0022] S107: Connect the two side line points to obtain a straight side line.

[0023] Preferably, in step S102, if the second set of binding lines is enabled, the widths of the left and right binding lines of the second set of binding lines are obtained; the perpendicular feet are calculated using polar coordinates, the coordinates of the two side line points of the second set of binding lines are calculated using the outward expansion method, and the second set of binding lines and the first set of binding lines are connected.

[0024] Preferably, in step S3, the processing steps of the lane intersection processing algorithm include:

[0025] S301: Obtain the geometric data of other roadways that intersect with the target roadway;

[0026] S302: Parametric modeling based on tunnel geometry data, detecting potential intersections between the target tunnel and other tunnels, and generating a candidate list of intersections by comparing spatial coordinates;

[0027] S303: Perform geometric verification on each candidate point in the intersection candidate list using a line segment intersection detection algorithm: calculate whether the roadway boundary line actually intersects at the candidate point. If so, construct a roadway topology network diagram, record the connection relationship and intersection angle between each roadway and adjacent roadways, and add the candidate point to the intersection sequence; otherwise, delete the corresponding candidate point from the intersection candidate list.

[0028] S304: Assign priority labels to the lanes based on the lane topology network diagram and preset rules, and generate a sequence of intersections with priority labels;

[0029] S305: Select the corresponding edge adjustment strategy parameters for the intersection points in the intersection point sequence according to their priority order;

[0030] S306: For each intersection, calculate the coordinates of the adjusted edge control points based on the edge adjustment strategy parameters, and generate the adjusted edge.

[0031] S307: Check whether the adjusted edge line causes new conflicts with other roadways: If there is a conflict, return to step S305 to reselect the edge line adjustment strategy parameters; otherwise, output the adjusted edge line to achieve the edge line adjustment of the target roadway.

[0032] Preferably, in step S304, for multi-intersection scenarios, the processing order is sorted according to priority to ensure that the edge adjustment of high-priority lanes is not disturbed by low-priority lanes.

[0033] Preferably, in step S305, based on the intersection angle and the lane width, a suitable edge adjustment scheme is selected for the intersection from the predefined strategy library, and the corresponding edge adjustment strategy parameters are generated.

[0034] The sideline adjustment plan includes:

[0035] 1) Acute angle intersection: Use rounded transition or beveled angle treatment;

[0036] 2) Obtuse angle intersection: Keep the original edge line and only perform local smoothing near the intersection point;

[0037] 3) Multiple roadway intersections: The highest priority roadway is the center, and the edges of other roadways are gradually adjusted according to the angle ratio.

[0038] Preferably, in step S4, if the target lane obstructs other lanes, the processing steps of the lane obstruction handling algorithm include:

[0039] S401: Obtain real-time drawing data of the target tunnel, as well as static data and environmental data of the surrounding tunnels;

[0040] S402: Construct a geometric model of the target tunnel and surrounding tunnels, and mark all obstructions that may cause occlusion;

[0041] S403: Generate occlusion boundary equations based on occlusion type and calculate occlusion intensity; construct a parameterized occlusion model that includes occlusion boundary equations and occlusion intensity.

[0042] S404: Calculate the occlusion direction, occlusion object ID, occlusion intensity, and occlusion boundary of the target roadway to surrounding roadways based on the parametric occlusion model;

[0043] S405: Based on the occlusion direction, occlusion object ID, occlusion intensity and occlusion boundary of the target lane to the surrounding lanes, a preset occlusion processing strategy is matched, and the geometric model of the target lane is adjusted through the occlusion processing strategy to achieve the edge adjustment of the target lane.

[0044] Preferably, in step S403, the occlusion types include linear occlusion, curved surface occlusion, and combined occlusion; for linear occlusion, a plane equation is selected to generate the occlusion boundary equation; for curved surface occlusion, a quadratic surface equation is selected to generate the occlusion boundary equation; and for combined occlusion, a system of equations combining the plane equation and the quadratic surface equation is selected to generate the occlusion boundary equation.

[0045] Obstruction intensity is the degree of interference of an obstruction on the function of a target roadway, expressed by the formula:

[0046]

[0047] In the formula: ω1 and ω2 are weighting coefficients.

[0048] Preferably, in step S405, the occlusion handling strategy includes:

[0049] 1) Scale the cross-section: Adjust the width / height proportionally;

[0050] 2) Offset edge line: Shift the center line along the occlusion direction;

[0051] 3) Detour planning: Call the path planning algorithm to generate a new centerline.

[0052] Preferably, in step S4, if the target roadway is obstructed by other roadways, the processing steps of the roadway obstruction handling algorithm include:

[0053] S411: Obtain real-time drawing data of the target tunnel, as well as static data and environmental data of the surrounding tunnels;

[0054] S412: Construct a geometric model of the target tunnel and surrounding tunnels, and mark all obstructions that may cause occlusion;

[0055] S413: Generate occlusion boundary equations based on occlusion type and calculate occlusion intensity; construct a parameterized occlusion model that includes occlusion boundary equations and occlusion intensity.

[0056] S414: Calculate the occlusion direction, occlusion object ID, occlusion intensity, and occlusion boundary of the target roadway based on the parametric occlusion model;

[0057] S415: Based on the occlusion direction, occlusion object ID, occlusion intensity and occlusion boundary of the target lane from the surrounding lanes, a preset occlusion processing strategy is matched, and the geometric model of the target lane is adjusted through the occlusion processing strategy to achieve the edge adjustment of the target lane.

[0058] Compared with existing technologies, the method for automatic generation of roadway edges and processing of topological relationships based on traverse point data in this invention has the following advantages:

[0059] In mine roadway intersection scenarios, existing methods are prone to errors or deviations in topology due to their inability to accurately handle the complex geometric relationships at the intersection. To address this issue, this invention employs a roadway intersection processing algorithm to adjust the edges of the target roadway in real time, precisely capturing the location and connection method of the intersection point. This ensures the accurate representation of the intersection relationship of roadways in three-dimensional space, avoiding problems such as discontinuous or incorrectly connected topologies. Simultaneously, the roadway intersection processing algorithm can dynamically optimize the shape and direction of the edges at the intersection based on the actual conditions of the intersecting roadways, resulting in a more rational topology. This not only reduces unnecessary edge redundancy but also makes the transition of the roadway intersection section smoother and more natural, thereby improving the overall quality and accuracy of mine roadway edge generation.

[0060] When roadways are obstructed, existing methods struggle to accurately determine the obstruction relationship, easily leading to topological confusion. To address this issue, the roadway obstruction processing algorithm of this invention adjusts the target roadway edge in real time, accurately distinguishing between obstructed and unobstructed sections. This accurately reflects the actual obstruction situation of the roadway in three-dimensional space, ensuring the authenticity and accuracy of the topological structure and avoiding topological errors caused by improper obstruction handling. Simultaneously, the algorithm automatically adjusts the target roadway edge according to the obstruction situation, optimizing the edge layout of obstructed areas. This ensures that the obstruction relationship is reasonably reflected in the topological structure, preventing abnormal extension or overlap of edges at obstructed locations while ensuring the integrity and coherence of the overall roadway topology. This improves the quality of mine roadway edge generation, providing more precise support for roadway design, planning, and management. Attached Figure Description

[0061] To make the objectives, technical solutions, and advantages of the invention clearer, the invention will now be described in further detail with reference to the accompanying drawings, wherein:

[0062] Figure 1 This is a logic block diagram of a method for automatically generating roadway edges and processing topological relationships based on traverse point data.

[0063] Figure 2 A flowchart for generating the lane edge lines.

[0064] Figure 3 A flowchart for handling intersections and obstructions in alleyways. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but only to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0066] It should be noted that similar reference numerals and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the figures, or the orientation or positional relationship commonly used when the product is in use. They are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third," etc., are only used to distinguish descriptions and should not be construed as indicating or implying relative importance. In addition, the terms "horizontal," "vertical," etc., do not mean that the component is required to be absolutely horizontal or suspended, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted. In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0067] The following detailed explanation illustrates the specific implementation methods:

[0068] Example:

[0069] This embodiment discloses a method for automatically generating roadway edge lines and processing topological relationships based on traverse point data.

[0070] like Figure 1 As shown, the method for automatic generation of roadway edges and processing of topological relationships based on traverse point data includes:

[0071] S1: Generate the edge line of the target tunnel based on the traverse point data;

[0072] S2: During the extension of the target roadway's edge, determine whether the target roadway intersects with or is obstructed by other roadways: if it intersects with other roadways, proceed to step S3; if it is obstructed by other roadways, proceed to step S4.

[0073] S3: Adjust the edge line of the target tunnel in real time through the tunnel intersection processing algorithm;

[0074] S4: Adjust the edge line of the target lane in real time through the lane occlusion processing algorithm;

[0075] S5: Repeat steps S2 to S4 until the edge line of the target tunnel is drawn.

[0076] In mine roadway intersection scenarios, existing methods are prone to errors or deviations in topology due to their inability to accurately handle the complex geometric relationships at the intersection. To address this issue, this invention employs a roadway intersection processing algorithm to adjust the edges of the target roadway in real time, precisely capturing the location and connection method of the intersection point. This ensures the accurate representation of the intersection relationship of roadways in three-dimensional space, avoiding problems such as discontinuous or incorrectly connected topologies. Simultaneously, the roadway intersection processing algorithm can dynamically optimize the shape and direction of the edges at the intersection based on the actual conditions of the intersecting roadways, resulting in a more rational topology. This not only reduces unnecessary edge redundancy but also makes the transition of the roadway intersection section smoother and more natural, thereby improving the overall quality and accuracy of mine roadway edge generation.

[0077] When roadways are obstructed, existing methods struggle to accurately determine the obstruction relationship, easily leading to topological confusion. To address this issue, the roadway obstruction processing algorithm of this invention adjusts the target roadway edge in real time, accurately distinguishing between obstructed and unobstructed sections. This accurately reflects the actual obstruction situation of the roadway in three-dimensional space, ensuring the authenticity and accuracy of the topological structure and avoiding topological errors caused by improper obstruction handling. Simultaneously, the algorithm automatically adjusts the target roadway edge according to the obstruction situation, optimizing the edge layout of obstructed areas. This ensures that the obstruction relationship is reasonably reflected in the topological structure, preventing abnormal extension or overlap of edges at obstructed locations while ensuring the integrity and coherence of the overall roadway topology. This improves the quality of mine roadway edge generation, providing more precise support for roadway design, planning, and management.

[0078] To better illustrate the technical solution of the present invention, this embodiment is described in the following parts.

[0079] I. Edge line generation

[0080] This invention, based on measured data from mine roadways, innovatively develops an intelligent roadway edge line generation engine. It automatically generates the left and right sidewall lines of the roadway using a dynamic outward expansion algorithm, based on the measured coordinates of the traverse points and the corresponding designed widths of the left and right sidewalls. By introducing a curvature adaptive compensation mechanism, it ensures that the edge line accuracy in complex areas such as turning sections and slope changes meets the requirements of the "GB / T50598-2020 Code for Design of Coal Mine Shafts," with errors controlled within ±0.05m.

[0081] like Figure 2 As shown, the edge line of the target tunnel is drawn by following these steps:

[0082] S101: Obtain the traverse point data of the target roadway, as well as the width of the left and right sidewalls;

[0083] S102: Generate the side lines and center lines of the target roadway using the traverse point data and the widths of the left and right side lines;

[0084] In step S102, if the second set of binding lines is enabled, the widths of the left and right binding lines of the second set of binding lines are obtained; the perpendicular feet are calculated using polar coordinates, the coordinates of the two side line points of the second set of binding lines are calculated using the outward expansion method, and the second set of binding lines and the first set of binding lines are connected.

[0085] S103: Based on the side line and center line, the perpendicular foot is calculated using polar coordinates, and the coordinates of the two side line points are calculated using the outward expansion method;

[0086] S104: Determine if the radius of the centerline of the target roadway is 0: if yes, proceed to step S107; otherwise, proceed to step S105.

[0087] S105: Determine the bending direction of the edge line: If the radius is a positive radius, the edge line bends clockwise; if the radius is a negative radius, the edge line bends counterclockwise.

[0088] S106: Calculate the arcs between the two guide points and obtain the arc edges on the left and right sides through the outward expansion algorithm;

[0089] S107: Connect the two side line points to obtain a straight side line.

[0090] The core technologies of this invention include:

[0091] Dynamic expansion algorithm: Based on the coordinates of the traverse points and the design cross-sectional parameters (left side width W_L, right side width W_R), the boundary calculation method based on polar coordinate transformation is used to automatically generate the roadway edge line that meets the engineering accuracy.

[0092] Error control system: Introduces a real-time quality detection mechanism. When the distance between adjacent traverse points exceeds the set threshold (default 5m), virtual control points are automatically inserted to ensure that the mapping accuracy meets the ±50mm error requirement specified in GB / T 50598-2020.

[0093] Dual-parameter sidewall parameter system: The introduction of the dual-parameter sidewall parameter system can intelligently handle scenarios of sudden changes in roadway width (such as a 3m→6m widening section) and supports dual-parameter sidewall configuration to ensure smooth edge transition and accurate topological relationship, strictly complying with the requirements of the "GB 50215-2019 Coal Industry Mine Design Code" for roadway widening sections.

[0094] Intelligent curvature control module: Supports dynamic radius setting, automatically optimizes the geometric continuity of turning segments, perfectly adapts to the smooth transition requirements of special roadways such as water tanks and parking lots, introduces a directional curvature control mechanism, and achieves precise control of the roadway bending direction through positive and negative radius parameters. Positive radius (+R) - indicates clockwise bending (right turn); negative radius (-R) - indicates counterclockwise bending (left turn).

[0095] II. Handling of intersections of lanes

[0096] like Figure 3 As shown, the processing steps of the lane intersection processing algorithm include:

[0097] S301: Obtain the geometric data of other roadways that intersect with the target roadway; the roadway geometric data includes the coordinates of the starting point and ending point, width, direction and topological relationship of each roadway;

[0098] S302: Parametric modeling based on tunnel geometry data, detecting potential intersections between the target tunnel and other tunnels, and generating a candidate list of intersections by comparing spatial coordinates;

[0099] In this embodiment, the candidate list of intersections includes the intersection lane ID and the estimated intersection location.

[0100] S303: Perform geometric verification on each candidate point in the intersection candidate list using a line segment intersection detection algorithm: calculate whether the roadway boundary line actually intersects at the candidate point. If so, construct a roadway topology network diagram, record the connection relationship and intersection angle between each roadway and adjacent roadways, and add the candidate point to the intersection sequence; otherwise, delete the corresponding candidate point from the intersection candidate list.

[0101] In this embodiment, the confirmed list of intersections includes precise coordinates, intersection lane IDs, and intersection angles.

[0102] S304: Assign priority labels to the lanes based on the lane topology network diagram and preset rules, and generate a sequence of intersections with priority labels;

[0103] In this embodiment, the preset rules include the functional attributes of the lane (such as main lane / branch lane), traffic flow, design specifications, etc.

[0104] For scenarios with multiple intersections (such as the intersection of three or more lanes), the processing order is sorted according to priority to ensure that the boundary adjustment of high-priority lanes is not affected by low-priority lanes.

[0105] S305: Select the corresponding edge adjustment strategy parameters for the intersection points in the intersection point sequence according to their priority order;

[0106] Based on the intersection angle and the lane width, select an appropriate edge adjustment scheme for the intersection from the predefined strategy library and generate the corresponding edge adjustment strategy parameters.

[0107] The sideline adjustment plan includes:

[0108] 1) Acute angle intersection: Use rounded transitions or beveled angles to ensure that the vehicle's turning radius meets safety standards;

[0109] 2) Obtuse angle intersection: Keep the original edge line and only perform local smoothing near the intersection point;

[0110] 3) Multiple roadway intersections: The highest priority roadway is the center, and the edges of other roadways are gradually adjusted according to the angle ratio.

[0111] S306: For each intersection point, calculate the coordinates of the adjusted edge control points based on the edge adjustment strategy parameters, and generate the adjusted edge; it is necessary to ensure that the adjusted edge is continuous and meets the minimum width constraint.

[0112] S307: Check whether the adjusted edge line causes new conflicts with other roadways: If there is a conflict, return to step S305 to reselect the edge line adjustment strategy parameters; otherwise, output the adjusted edge line to achieve the edge line adjustment of the target roadway.

[0113] III. Roadway Obstruction Treatment

[0114] like Figure 3 As shown, if the target lane obstructs other lanes, the processing steps of the lane obstruction handling algorithm include:

[0115] S401: Obtain real-time drawing data of the target tunnel, as well as static data and environmental data of the surrounding tunnels;

[0116] In this embodiment, the real-time drawing data of the target tunnel includes centerline coordinates, cross-sectional shape, size, and drawing direction; the static data of the surrounding tunnels includes geometric model, support structure parameters, and pipeline location; and the environmental parameters include geological conditions, construction stage, and safety standard thresholds.

[0117] S402: Construct the geometric model of the target tunnel and surrounding tunnels, mark all obstructions that may cause occlusion, and associate the geometric properties of the obstructions;

[0118] In this embodiment, the obstruction may be anchor bolt support, cable tray, support structure, pipeline, temporary stockpile, etc.

[0119] S403: Generate occlusion boundary equations based on occlusion type, calculate occlusion intensity and introduce dynamic factors; construct a parameterized occlusion model that includes occlusion boundary equations, occlusion intensity and dynamic factors;

[0120] Specifically, the types of obstructions include linear obstructions (such as tunnel cross-sections), curved surface obstructions (such as arch support), and combined obstructions (such as pipelines + supports). For linear obstructions, the planar equation is used to generate the obstruction boundary equation; for curved surface obstructions, the quadratic surface equation is used to generate the obstruction boundary equation; and for combined obstructions, the equations formed by combining the planar equation and the quadratic surface equation are used to generate the obstruction boundary equation.

[0121] Obstruction intensity is the degree of interference of an obstruction on the function of a target roadway, expressed by the formula:

[0122]

[0123] In the formula: ω1 and ω2 are weighting coefficients;

[0124] Dynamic factors include the design time factor and schedule factor.

[0125] S404: Calculate the occlusion direction, occlusion object ID, occlusion intensity, and occlusion boundary of the target roadway to surrounding roadways based on the parametric occlusion model;

[0126] S405: Based on the occlusion direction, occlusion object ID, occlusion intensity and occlusion boundary of the target lane to the surrounding lanes, a preset occlusion processing strategy is matched, and the geometric model of the target lane is adjusted through the occlusion processing strategy to achieve the edge adjustment of the target lane.

[0127] Occlusion handling strategies include:

[0128] 1) Scaling the cross-section: Adjust the width / height proportionally (e.g., reduce the width from 3 meters to 2.5 meters);

[0129] 2) Offset edge line: Shift the center line along the shading direction (e.g., shift it upwards by 0.3 meters and then regenerate the cross-section);

[0130] 3) Detour planning: Use a path planning algorithm (such as A* algorithm) to generate a new centerline.

[0131] like Figure 3 As shown, if the target lane is obstructed by other lanes, the processing steps of the lane occlusion handling algorithm include:

[0132] S411: Obtain real-time drawing data of the target tunnel, as well as static data and environmental data of the surrounding tunnels;

[0133] In this embodiment, the real-time drawing data of the target tunnel includes centerline coordinates, cross-sectional shape, size, and drawing direction; the static data of the surrounding tunnels includes geometric model, support structure parameters, and pipeline location; and the environmental parameters include geological conditions, construction stage, and safety standard thresholds.

[0134] S412: Construct a geometric model of the target tunnel and surrounding tunnels, mark all obstructions that may cause occlusion, and associate the geometric properties of the obstructions.

[0135] In this embodiment, the obstruction may be anchor bolt support, cable tray, support structure, pipeline, temporary stockpile, etc.

[0136] S413: Generate occlusion boundary equations based on occlusion type, calculate occlusion intensity and introduce dynamic factors; construct a parameterized occlusion model that includes occlusion boundary equations, occlusion intensity and dynamic factors;

[0137] S414: Calculate the occlusion direction, occlusion object ID, occlusion intensity, and occlusion boundary of the target roadway based on the parametric occlusion model;

[0138] S415: Based on the occlusion direction, occlusion object ID, occlusion intensity and occlusion boundary of the target lane from the surrounding lanes, a preset occlusion processing strategy is matched, and the geometric model of the target lane is adjusted through the occlusion processing strategy to achieve the edge adjustment of the target lane.

[0139] Based on tunnel elevation data, this invention establishes a multi-level projection relationship model to automatically identify and handle the projection overlap problem of different intermediate tunnel sections and the edge connection relationship at the connection point of connected tunnels.

[0140] Its core technologies include:

[0141] Multi-level projection relationship processing module: Traditional roadway projection processing methods only support simple occlusion between adjacent levels, making it difficult to handle the actual situation of mutual occlusion between multi-level roadways in complex mining environments. This invention proposes a recursive multi-level occlusion topology modeling technique, which establishes a global occlusion relationship network to achieve accurate occlusion processing for roadways of any number of levels.

[0142] Intelligent edge connection module: Provides professional-grade edge processing solutions, including: independent processing mechanism - each edge calculates processing parameters separately to avoid mutual interference; angle adaptive algorithm - includes three basic processing modes: extension, chamfering, and break.

[0143] Error control system: Construct a multi-layered accuracy assurance system, including: occlusion error judgment - occlusion is only considered to exist when the elevation is above 3m by default; intersection judgment error - connection relationship error judgment - connection relationship is considered to exist when the distance is within 0.1m by default.

[0144] Complex Intersection Processing Module: A solution specifically designed for multiple lane connection points, employing a two-stage processing architecture of topology network construction and intelligent edge optimization, specifically designed to solve the edge processing challenges in complex multi-lane intersection scenarios. By establishing a precise spatial topology relationship model, it achieves intelligent and independent processing of each lane edge.

[0145] Real-time processing module: Adopting a dynamic incremental processing architecture, it breaks through the limitations of the traditional batch processing mode, and builds and maintains the topology network in real time during the tunnel drawing process, realizing the technological leap from "post-processing" to "real-time processing".

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit the technical solutions. Those skilled in the art should understand that any modifications or equivalent substitutions to the technical solutions of the present invention without departing from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A method for automatically generating roadway edge lines and processing topological relationships based on traverse point data, characterized in that, include: S1: Generate the edge line of the target tunnel based on the traverse point data; S2: During the extension of the target roadway's edge, determine whether the target roadway intersects with or is obstructed by other roadways: if it intersects with other roadways, proceed to step S3; if it is obstructed by other roadways, proceed to step S4. S3: Adjust the edge line of the target tunnel in real time through the tunnel intersection processing algorithm; S4: Adjust the edge line of the target lane in real time through the lane occlusion processing algorithm; S5: Repeat steps S2 to S4 until the edge line of the target tunnel is drawn.

2. The method for automatic generation of roadway edges and processing of topological relationships based on traverse point data as described in claim 1, characterized in that: In step S1, the edge line of the target tunnel is drawn through the following steps: S101: Obtain the traverse point data of the target roadway, as well as the width of the left and right sidewalls; S102: Generate the side lines and center lines of the target roadway using the traverse point data and the widths of the left and right side lines; S103: Based on the side line and center line, the perpendicular foot is calculated using polar coordinates, and the coordinates of the two side line points are calculated using the outward expansion method; S104: Determine if the radius of the centerline of the target roadway is 0: If yes, proceed to step S107; Otherwise, proceed to step S105; S105: Determine the bending direction of the edge line: If the radius is a positive radius, the edge line bends clockwise; if the radius is a negative radius, the edge line bends counterclockwise. S106: Calculate the arcs between the two guide points and obtain the arc edges on the left and right sides through the outward expansion algorithm; S107: Connect the two side line points to obtain a straight side line.

3. The method for automatic generation of roadway edges and processing of topological relationships based on traverse point data as described in claim 2, characterized in that: In step S102, if the second set of binding lines is enabled, the widths of the left and right binding lines of the second set of binding lines are obtained; the perpendicular feet are calculated using polar coordinates, the coordinates of the two side line points of the second set of binding lines are calculated using the outward expansion method, and the second set of binding lines and the first set of binding lines are connected.

4. The method for automatic generation of roadway edges and processing of topological relationships based on traverse point data as described in claim 1, characterized in that: In step S3, the processing steps of the lane intersection processing algorithm include: S301: Obtain the geometric data of other roadways that intersect with the target roadway; S302: Parametric modeling based on tunnel geometry data, detecting potential intersections between the target tunnel and other tunnels, and generating a candidate list of intersections by comparing spatial coordinates; S303: Perform geometric verification on each candidate point in the intersection candidate list using a line segment intersection detection algorithm: calculate whether the roadway boundary line actually intersects at the candidate point. If so, construct a roadway topology network diagram, record the connection relationship and intersection angle between each roadway and adjacent roadways, and add the candidate point to the intersection sequence; otherwise, delete the corresponding candidate point from the intersection candidate list. S304: Assign priority labels to the lanes based on the lane topology network diagram and preset rules, and generate a sequence of intersections with priority labels; S305: Select the corresponding edge adjustment strategy parameters for the intersection points in the intersection point sequence according to their priority order; S306: For each intersection, calculate the coordinates of the adjusted edge control points based on the edge adjustment strategy parameters, and generate the adjusted edge. S307: Check whether the adjusted edge line causes new conflicts with other roadways: If there is a conflict, return to step S305 to reselect the edge line adjustment strategy parameters; otherwise, output the adjusted edge line to achieve the edge line adjustment of the target roadway.

5. The method for automatic generation of roadway edges and processing of topological relationships based on traverse point data as described in claim 4, characterized in that: In step S304, for multi-intersection scenarios, the processing order is sorted according to priority to ensure that the edge adjustment of high-priority lanes is not affected by low-priority lanes.

6. The method for automatic generation of roadway edges and processing of topological relationships based on traverse point data as described in claim 4, characterized in that: In step S305, based on the intersection angle and the roadway width, a suitable edge adjustment scheme is selected for the intersection from the predefined strategy library, and the corresponding edge adjustment strategy parameters are generated. The sideline adjustment plan includes: 1) Acute angle intersection: Use rounded transition or beveled angle treatment; 2) Obtuse angle intersection: Keep the original edge line and only perform local smoothing near the intersection point; 3) Multiple roadway intersections: The highest priority roadway is the center, and the edges of other roadways are gradually adjusted according to the angle ratio.

7. The method for automatic generation of roadway edge lines and processing of topological relationships based on traverse point data as described in claim 1, characterized in that: In step S4, if the target lane obstructs other lanes, the processing steps of the lane obstruction handling algorithm include: S401: Obtain real-time drawing data of the target tunnel, as well as static data and environmental data of the surrounding tunnels; S402: Construct a geometric model of the target tunnel and surrounding tunnels, and mark all obstructions that may cause occlusion; S403: Generate occlusion boundary equations based on occlusion type and calculate occlusion intensity; construct a parameterized occlusion model that includes occlusion boundary equations and occlusion intensity. S404: Calculate the occlusion direction, occlusion object ID, occlusion intensity, and occlusion boundary of the target roadway to surrounding roadways based on the parametric occlusion model; S405: Based on the occlusion direction, occlusion object ID, occlusion intensity and occlusion boundary of the target lane to the surrounding lanes, a preset occlusion processing strategy is matched, and the geometric model of the target lane is adjusted through the occlusion processing strategy to achieve the edge adjustment of the target lane.

8. The method for automatic generation of roadway edge lines and processing of topological relationships based on traverse point data as described in claim 7, characterized in that: In step S403, the types of occlusion include linear occlusion, curved surface occlusion, and combined occlusion; Linear occlusion uses plane equations to generate occlusion boundary equations; curved surface occlusion uses quadratic surface equations to generate occlusion boundary equations; combined occlusion uses a system of equations combining plane equations and quadratic surface equations to generate occlusion boundary equations. Obstruction intensity is the degree of interference of an obstruction on the function of a target roadway, expressed by the formula: In the formula: ω1 and ω2 are weighting coefficients.

9. The method for automatic generation of roadway edges and processing of topological relationships based on traverse point data as described in claim 7, characterized in that: In step S405, the occlusion handling strategy includes: 1) Scale the cross-section: Adjust the width / height proportionally; 2) Offset edge line: Shift the center line along the occlusion direction; 3) Detour planning: Call the path planning algorithm to generate a new centerline.

10. The method for automatic generation of roadway edge lines and processing of topological relationships based on traverse point data as described in claim 1, characterized in that: In step S4, if the target roadway is obstructed by other roadways, the roadway obstruction handling algorithm includes the following steps: S411: Obtain real-time drawing data of the target tunnel, as well as static data and environmental data of the surrounding tunnels; S412: Construct a geometric model of the target tunnel and surrounding tunnels, and mark all obstructions that may cause occlusion; S413: Generate occlusion boundary equations based on occlusion type and calculate occlusion intensity; construct a parameterized occlusion model that includes occlusion boundary equations and occlusion intensity. S414: Calculate the occlusion direction, occlusion object ID, occlusion intensity, and occlusion boundary of the target roadway based on the parametric occlusion model; S415: Based on the occlusion direction, occlusion object ID, occlusion intensity and occlusion boundary of the target lane from the surrounding lanes, a preset occlusion processing strategy is matched, and the geometric model of the target lane is adjusted through the occlusion processing strategy to achieve the edge adjustment of the target lane.

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