Municipal road cross section intelligent optimization design method based on BIM

Abstract

The invention belongs to the technical field of municipal road design, and provides a BIM (Building Information Modeling)-based municipal road cross section intelligent optimization design method, which comprises the following steps of: dividing sub-broadening sections, obtaining a cross slope default interpolation generated by a BIM default interpolation algorithm in the sub-broadening sections, judging whether the cross slope default interpolation is effective or not, and identifying to-be-optimized sub-broadening sections; determining a cross slope interpolation reconstruction mode of the to-be-optimized sub-broadening section according to the proportion and distribution of invalid cross slope default interpolations in the to-be-optimized sub-broadening section, carrying out change trend analysis according to existing cross slope data in the to-be-optimized sub-broadening section, determining the type of the to-be-optimized sub-broadening section, and optimizing the to-be-optimized sub-broadening section according to the type of the to-be-optimized sub-broadening section. Selecting an adaptive model and reconstructing a cross slope interpolation in combination with a cross slope interpolation reconstruction mode of the to-be-optimized sub-broadening section to obtain a stake mark-cross slope data table; according to the stake mark-cross slope data table, the cross slope default interpolation of the to-be-optimized sub-broadening section is replaced by the BIM reverse assignment, and the primary compliance rate and the overall design efficiency of the cross slope design of the complex broadening section are improved.

Description

Technical Field

[0001] This invention belongs to the field of municipal road design technology, specifically a BIM-based intelligent optimization design method for municipal road cross-sections. Background Technology

[0002] In municipal road engineering design, cross-section design, especially the determination of road cross slope, directly affects driving safety, pavement drainage comfort, and engineering economy. With the in-depth application of Building Information Modeling (BIM) technology in the municipal transportation field, professional software such as Autodesk Civil 3D and Bentley OpenRoads have become mainstream design tools. These software programs typically use linear interpolation algorithms based on control points to automatically generate the cross slope of the entire road, which is highly efficient in standard section design. However, when dealing with "widened sections" such as channelized sections at intersections, bus bays, toll plazas, and interchange connection sections, the cross slope needs to undergo complex transitions due to changes in the number or width of lanes, and the software's default linear interpolation often exposes its limitations.

[0003] Linear interpolation algorithms can only guarantee a linear change in cross slope values ​​between control points, failing to perceive and comply with actual engineering constraints. This often leads to a series of design flaws: First, the generated cross slope values ​​at intermediate sections may exceed the allowable range (e.g., a negative slope, or "reverse slope," affecting drainage); second, the rate of change of cross slope between adjacent sections may increase dramatically, exceeding the allowable threshold per meter, causing bumpy driving and even safety hazards; third, if the density of control points is inappropriate, the interpolation results may completely deviate from the actual smooth curve of the terrain or functional requirements. Currently, solving these problems heavily relies on the experience of designers, requiring manual inspection of interpolation results section by section and repeated adjustments to control point positions and cross slope values, approximating a compliant solution through trial and error. This process is not only time-consuming, labor-intensive, and inefficient, but also prone to omissions due to human error, affecting design quality and compliance, and has become a bottleneck restricting the full-process automation and intelligence of BIM technology in road design.

[0004] Therefore, this invention provides a BIM-based intelligent optimization design method for the cross-section of municipal roads. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0006] The technical solution adopted by this invention to solve its technical problem is: a BIM-based intelligent optimization design method for the cross-section of municipal roads, comprising the following steps: Step S10: Divide the widening section into sub-widening sections according to the preset cross slope engineering constraints, obtain the default cross slope interpolation value generated by the BIM default interpolation algorithm in the sub-widening section, and compare it with the cross slope engineering constraints to determine whether the default cross slope interpolation value is valid. Step S20: Identify the sub-widening segment to be optimized based on whether the default cross slope interpolation is valid, and determine the cross slope interpolation reconstruction method of the sub-widening segment to be optimized based on the proportion and distribution of invalid default cross slope interpolation in the sub-widening segment to be optimized. The cross slope interpolation reconstruction method includes local reconstruction of the sub-widening segment and global reconstruction of the sub-widening segment. Step S30: Analyze the changing trend of the existing cross slope data in the sub-widening section to be optimized, determine the type of the sub-widening section to be optimized, select the appropriate model according to the type of the sub-widening section to be optimized, and reconstruct the cross slope interpolation in combination with the cross slope interpolation reconstruction method of the sub-widening section to be optimized, so as to obtain the station number-cross slope data table. Step S40: Based on the station number-cross slope data table, replace the default cross slope interpolation of the sub-widening section to be optimized with BIM reverse assignment.

[0007] As a further technical solution of the present invention: the division method of the sub-broadening segment is as follows: Input the cross-section design drawings into the BIM software and automatically build the widening section model. In the widening section model, the widening sections with the same preset cross slope engineering constraint requirements are divided and marked as a sub-widening section. The preset cross slope engineering constraints include cross slope value requirements and cross slope change rate requirements between adjacent sections. The cross slope value requirement is that the cross slope value is within the preset cross slope range, and the cross slope change rate requirement between adjacent sections is that the cross slope change rate does not exceed the preset change rate threshold.

[0008] As a further technical solution of the present invention: the process of determining whether the default cross slope interpolation is valid is as follows: If the default cross slope interpolation is not within the preset range of cross slope or the cross slope change rate corresponding to the default cross slope interpolation exceeds the preset change rate threshold, then the default cross slope interpolation is invalid. If the default cross slope interpolation is within the preset range of cross slope and the cross slope change rate corresponding to the default cross slope interpolation does not exceed the preset change rate threshold, then the default cross slope interpolation is valid.

[0009] As a further technical solution of the present invention: the process of identifying the sub-broadening segment to be optimized is as follows: If any invalid cross slope default interpolation exists within any sub-segment, then the sub-segment is marked as a sub-segment to be optimized.

[0010] As a further technical solution of the present invention: the process of determining the cross slope interpolation reconstruction method of the sub-widening segment to be optimized includes: The proportion of invalid cross slope default interpolations in the sub-widening segment to be optimized is calculated as the proportion of invalid cross slopes among all default cross slope interpolations. If the proportion of invalid cross slopes exceeds the preset threshold for invalid cross slopes, the cross slope interpolation reconstruction method will be global reconstruction. If the proportion of invalid cross slopes does not exceed the preset threshold for invalid cross slopes, then the distribution analysis is performed on the default interpolation of invalid cross slopes, and the cross slope interpolation reconstruction method is determined based on the distribution analysis results.

[0011] As a further technical solution of the present invention: the distribution analysis process is as follows: Obtain the default interpolation values ​​of all invalid cross slopes in the sub-widening section to be optimized, arrange them in the order of the corresponding station numbers, obtain the range of invalid station numbers based on the initial end station number and the end end station number, calculate the ratio of the length of the widening section corresponding to the range of invalid station numbers to the length of the sub-widening section to be optimized, and obtain the distribution value of invalid cross slope length. Summarize the station numbers corresponding to the default interpolation of invalid cross slopes, calculate the interval between each adjacent station number and perform mean value processing to obtain the average interval length of invalid cross slopes, calculate the ratio of the average interval length of invalid cross slopes to the length of the sub-widening section to be optimized, and obtain the discrete distribution value of invalid cross slopes. The invalid length distribution value of the cross slope is summed with the invalid discrete distribution value of the cross slope to obtain the invalid distribution value of the cross slope. The invalid distribution value of the cross slope is compared with the invalid distribution threshold of the cross slope. If the invalid distribution value of the cross slope exceeds the invalid distribution threshold of the cross slope, the cross slope interpolation reconstruction method is global reconstruction; if the invalid distribution value of the cross slope does not exceed the invalid distribution threshold of the cross slope, the cross slope interpolation reconstruction method is local reconstruction.

[0012] As a further technical solution of the present invention: the existing cross slope data in the sub-widening segment to be optimized includes the cross slope values ​​of the starting point and ending point of the sub-widening segment to be optimized, the cross slope values ​​of the set control points, and the effective default cross slope interpolation in the sub-widening segment to be optimized.

[0013] As a further technical solution of the present invention: the process of determining the type of the sub-segment to be optimized is as follows: The existing cross slope data in the sub-widening section to be optimized are arranged and summarized in order of the corresponding station number to obtain the effective cross slope sequence; Calculate the key features of the effective cross slope sequence, including the variance of the cross slope values ​​in the sequence, the mean cross slope rate of change, and the number of trend reversals; The effective cross slope sequence is fitted, and the type of sub-broadening segment to be optimized is determined by the goodness of fit and the key features of the effective cross slope sequence. Among them, the sub-broadening segment types to be optimized include stable sub-broadening segments, gradual sub-broadening segments, and fluctuating sub-broadening segments.

[0014] As a further technical solution of the present invention: the process of selecting the adaptation model and reconstructing the cross slope interpolation is as follows: If the cross slope interpolation reconstruction method is local reconstruction, then the nearest valid cross slope value is searched forward from the initial end station number of the invalid station number range, and the nearest valid cross slope value is searched backward from the end station number. The local reconstruction range is determined according to the station number corresponding to the valid cross slope value, and all valid cross slope data within the local reconstruction range are used as reconstruction input data. If the cross slope interpolation reconstruction method is global reconstruction, then all valid cross slope data in the sub-widening segment to be optimized will be used as reconstruction input data. The reconstructed input data is input into the adaptation model, and the preset cross slope engineering constraint requirements are used as constraints. The cross slope interpolation is reconstructed and organized into station number-cross slope data.

[0015] As a further technical solution of the present invention: the process of replacing the default interpolation of the cross slope by BIM reverse assignment is as follows: Using the API interface or script function of the BIM software, read the corresponding reconstructed cross slope value in the station number-cross slope data table according to the station number of the sub-widening section model to be optimized in the BIM, and replace the default cross slope interpolation value generated by the default interpolation algorithm at the corresponding station number in the BIM model.

[0016] The beneficial effects of this invention are as follows: Based on preset engineering constraints (cross slope range and rate of change threshold), the BIM default linear interpolation results are automatically screened for compliance, quickly locating problem points such as reverse slopes and exceeding limits (e.g., 0.15% low slope at K2+340, -0.10% reverse slope at K2+360), replacing traditional manual verification. Secondly, by analyzing the proportion and spatial distribution characteristics of invalid points, the system intelligently determines whether to adopt a "local reconstruction" or "global reconstruction" strategy, avoiding a one-size-fits-all approach in the optimization process. Then, based on the changing trend (stable, gradual, fluctuating) of the effective cross slope data, the system adaptively matches the optimal mathematical model (linear, quadratic polynomial, cubic spline interpolation), generating a smooth-transition cross slope curve while ensuring compliance. Finally, through the BIM software's API interface, the optimized cross slope data is automatically reverse-assigned and the original model is updated, forming a complete intelligent optimization closed loop. This solution elevates BIM design from a trial-and-error process reliant on experience to a data-driven, rule-constrained automated process, significantly improving the first-time compliance rate and overall design efficiency of complex widening section cross slope designs. Attached Figure Description

[0017] The invention will now be further described with reference to the accompanying drawings.

[0018] Figure 1 This is a flowchart illustrating the steps of a BIM-based intelligent optimization design method for the cross-section of municipal roads according to an embodiment of the present invention. Figure 2 This is a logic judgment diagram of a BIM-based intelligent optimization design method for the cross-section of municipal roads according to an embodiment of the present invention. Detailed Implementation

[0019] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0020] Example 1: Please refer to Figures 1-2 As shown in the embodiment of the present invention, a BIM-based intelligent optimization design method for municipal road cross-sections includes the following steps: Step S10: Divide the widening section into sub-widening sections according to the preset cross slope engineering constraints, obtain the default cross slope interpolation value generated by the BIM default interpolation algorithm in the sub-widening section, and compare it with the cross slope engineering constraints to determine whether the default cross slope interpolation value is valid. In step S10, the method for dividing the widened segment into sub-widened segments is as follows: Input the cross-section design drawings into the BIM software to automatically build the widening section model. In the widening section model, the widening sections with the same preset cross slope engineering constraints are divided and marked as a sub-widening section. For example, in the widening section with the chainage range from K2+100 to K2+200, the cross slope value and cross slope change rate requirements of each chainage point are consistent. Among them, the preset cross slope engineering constraints include cross slope value requirements and cross slope change rate between adjacent sections. For example, the cross slope value is within the preset cross slope range (such as between 0.5% and 4%); the cross slope change rate per meter between adjacent sections does not exceed the preset change rate threshold (such as 0.5%). In step S10, it should be noted that the widening section refers to a road section where the number of lanes or the width of the road increases, such as a channelized section at an intersection, a bus stop section, or a toll plaza. In step S10, it should also be noted that the default interpolation algorithm of BIM refers to the mathematical method (usually linear interpolation) used by BIM road design software (such as Civil 3D, OpenRoads) to automatically calculate the cross slope of all intermediate sections based on the cross slope values ​​of the starting and ending points and the cross slope values ​​of the set control points. The default cross slope interpolation is the original cross slope value calculated by the default interpolation algorithm of BIM without manual correction. For example, there is a widening section of a channelized section at an intersection, with a chainage range of K2+300 to K2+450 (length 150 meters). The preset cross slope engineering constraint requirement is that the cross slope is between 0.5% and 4%, and the cross slope change rate does not exceed 0.3% / m. The engineer only sets 4 control points, as shown in Table 1 below. The default cross slope interpolation and cross slope change rate calculated by BIM based on the cross slope values ​​of the control points are shown in Table 2 below. Table 1: Cross slope values ​​for the control points set;

[0021] Table 2: Default interpolation values ​​and cross slope change rates calculated by the default interpolation algorithm in BIM;

[0022] In step S10, the process of determining whether the default cross slope interpolation is valid is as follows: Compare the default cross slope interpolation with the preset cross slope engineering constraint requirements; If the default cross slope interpolation is not within the preset range of cross slope or the cross slope change rate corresponding to the default cross slope interpolation exceeds the preset change rate threshold, then the default cross slope interpolation is invalid. Conversely, if the default cross slope interpolation is within the preset range of cross slope and the cross slope change rate corresponding to the default cross slope interpolation does not exceed the preset change rate threshold, then the default cross slope interpolation is valid. Understandably, in this implementation plan, step S10 serves to refine the sub-regional division of the road widening section by using preset cross slope engineering constraints (such as cross slope value range and cross slope change rate limits). Its main purpose is to automatically identify and verify whether the original cross slope values ​​generated by the BIM software's default interpolation algorithm meet engineering specifications. By systematically comparing the algorithm-generated "default cross slope interpolation" with the constraints, problematic road sections can be quickly and accurately located, such as locations where the cross slope exceeds the allowable range or the change rate is too large. This step provides clear objectives and a basis for subsequent optimization work, essentially completing an automated "compliance screening" of the initial design results, thus replacing the inefficient traditional manual point-by-point verification method.

[0023] Step S20: Identify the sub-widening segment to be optimized based on whether the default cross slope interpolation is valid, and determine the cross slope interpolation reconstruction method of the sub-widening segment to be optimized based on the proportion and distribution of invalid default cross slope interpolation in the sub-widening segment to be optimized. The cross slope interpolation reconstruction method includes local reconstruction of the sub-widening segment and global reconstruction of the sub-widening segment. In step S20, the process of identifying the sub-widening segment to be optimized based on whether the default cross slope interpolation is valid is as follows: Based on any sub-expansion segment; If any invalid cross slope default interpolation exists in the cross slope default interpolation generated within the sub-widening segment, the sub-widening segment is marked as a sub-widening segment to be optimized, indicating that cross slope interpolation optimization is required. If there are no invalid cross slope default interpolations generated within the sub-widening segment, the sub-widening segment is marked as a normal sub-widening segment, indicating that no cross slope interpolation optimization is required, and no operation is performed. In step S20, the process of determining the cross slope interpolation reconstruction method for the sub-widening segment to be optimized is as follows: Based on any sub-segment to be optimized; The proportion of invalid cross slope default interpolations in the sub-widening segment to be optimized is calculated as the proportion of invalid cross slopes among all default cross slope interpolations. Compare the proportion of ineffective cross slope with the preset threshold for the proportion of ineffective cross slope; If the proportion of invalid cross slope exceeds the preset threshold, the cross slope interpolation reconstruction method of the sub-widening segment to be optimized will be global reconstruction. If the proportion of ineffective cross slope does not exceed the preset threshold for the proportion of ineffective cross slope, then perform a distribution analysis of ineffective cross slope. It should be noted that the cross slope invalidity threshold is used to make decisions between local and global reconstruction strategies. The method for setting it is as follows: First, the basic value can be set to 30% based on general engineering experience; second, it needs to be calibrated according to the road grade provisions in the "Code for Design of Urban Road Engineering" (CJJ37). For high-grade roads such as expressways and main roads, a stricter value (such as 20%~25%) should be used, while a more lenient value (such as 30%~35%) can be used for secondary roads and branch roads; finally, it can be fine-tuned according to the design stage objectives. The engineering logic of the cross slope invalidity threshold is that when the proportion of invalid points exceeds this critical value, it indicates that the BIM default interpolation has systematically deviated from the engineering constraints in this road section, and global reconstruction is more efficient and reliable than complex local repairs. In step S20, the distribution analysis process is as follows: Obtain all invalid cross slope default interpolation values ​​in the sub-widening segment to be optimized, and arrange them in order according to the station number corresponding to the invalid cross slope default interpolation value. After arrangement, obtain the station number range corresponding to the invalid cross slope default interpolation value based on the initial end station number and the end end station number, and mark it as invalid station number range. Obtain the length of the widening segment corresponding to the invalid station number range, and calculate the ratio with the length of the sub-widening segment to be optimized to obtain the cross slope invalid length distribution value. For example, assuming the sub-widening section to be optimized is from K2+300 to K2+450, with a length of 150 meters, and the invalid station range is from K2+355 to K2+430, with a length of 75 meters, then the invalid distribution value of the cross slope is 75 / 150=0.5. The station numbers corresponding to the default interpolation of the invalid cross slope are summarized, the interval between each adjacent station number is calculated, and the mean value is processed to obtain the average interval length of the invalid cross slope. The ratio of the average interval length of the invalid cross slope to the length of the sub-widening section to be optimized is calculated to obtain the discrete distribution value of the invalid cross slope. The ineffective length distribution value and the ineffective discrete distribution value of the cross slope are summed to obtain the ineffective distribution value of the cross slope; Compare the ineffective cross slope distribution values ​​with the ineffective cross slope distribution threshold; If the invalid cross slope distribution value exceeds the invalid cross slope distribution threshold, the cross slope interpolation reconstruction method for the sub-widening segment to be optimized is global reconstruction. If the cross slope invalid distribution value does not exceed the cross slope invalid distribution threshold, then the cross slope interpolation reconstruction method of the sub-widening segment to be optimized is local reconstruction. It should be noted that local reconstruction refers to recalculating the cross slope value only within the local station range where the invalid cross slope default interpolation is located, while global reconstruction refers to recalculating the cross slope value for the entire sub-widening section to be optimized. It should also be noted that the cross slope invalid distribution threshold is used to intelligently select reconstruction strategies based on the spatial distribution characteristics of invalid points. Its setting is based on the analysis of cross slope invalid distribution values, calculated from the length distribution value reflecting the degree of clustering and the discrete distribution value reflecting the degree of dispersion. The theoretical range of the cross slope invalid distribution threshold is (0,2), and the setting method is as follows: the decision boundary is determined through numerical experiments and engineering case analysis. When it is less than a certain value (e.g., 0.5), invalid points are highly clustered, and local reconstruction is suitable; when it is greater than another value (e.g., 1.0), invalid points are highly dispersed, and global reconstruction is suitable. The cross slope invalid distribution threshold is a critical value between these two, with a typical value of 0.6. The engineering basis is that when it is greater than 0.6, it indicates that the spatial distribution of invalid points has transitioned from local clustering to widespread dispersion. Global reconstruction can more effectively break the mutual constraints between invalid points and generate a smooth overall cross slope curve. Understandably, the ineffective cross slope distribution value is a key indicator that comprehensively characterizes the spatial distribution characteristics of cross slope design problems. Its physical significance lies in quantifying the clustering pattern and dispersion degree of ineffective cross slope default interpolation. Specifically, the ineffective cross slope length distribution value reflects the overall length distribution of ineffective cross slope default interpolation, while the ineffective cross slope discrete distribution value reflects the dispersion and independence of ineffective cross slope default interpolation. The smaller the ineffective cross slope distribution value, the more clustered the problem points are, and the stronger their mutual influence. When the ineffective cross slope distribution value is low, it indicates that the ineffective cross slope default interpolation is local and discrete, suitable for local reconstruction; when it is high, it means that the ineffective cross slope default interpolation has a wide range and strong dispersion, suitable for global reconstruction. Understandably, in this implementation scheme, step S20 serves the purpose of intelligently deciding on the optimization strategy for each problem sub-segment (i.e., the "sub-segment to be optimized") based on the screening results of step S10. It comprehensively judges whether the problem is local, fragmented, or large-scale and systemic by calculating the proportion and spatial distribution characteristics (such as cluster length and dispersion) of invalid cross slope points. Accordingly, the optimization method is classified as "local reconstruction" or "global reconstruction." The core significance of this step lies in achieving differentiation and precision in optimization strategies, avoiding a "one-size-fits-all" approach. It ensures that efficient and minimal local adjustments are used for small-scale, concentrated problems, while a comprehensive recalculation is initiated for large-scale, dispersed, and complex problems, thereby improving overall processing efficiency while ensuring optimization effectiveness.

[0024] Example 2: Please refer to Figures 1-2 As shown in the figure, based on Embodiment 1, the BIM-based intelligent optimization design method for municipal road cross-sections of this invention further includes the following steps: Step S30: Analyze the changing trend of the existing cross slope data in the sub-widening section to be optimized, determine the type of the sub-widening section to be optimized, select the appropriate model according to the type of the sub-widening section to be optimized, and reconstruct the cross slope interpolation in combination with the cross slope interpolation reconstruction method of the sub-widening section to be optimized, so as to obtain the station number-cross slope data table. In step S30, the existing cross slope data in the sub-widening segment to be optimized includes the cross slope values ​​of the start and end points, the cross slope values ​​of the set control points, and the valid default cross slope interpolation in the sub-widening segment to be optimized. In step S30, the process of determining the type of the sub-segment to be optimized is as follows: The existing cross slope data in the sub-widening section to be optimized are arranged and summarized according to the corresponding station number order to obtain the effective cross slope sequence of the sub-widening section to be optimized. Key features for calculating the effective cross slope sequence include the variance of cross slope values ​​in the sequence, the mean of the rate of change of cross slope, and the number of trend reversals (the number of positive and negative alternations of cross slope values ​​in the effective cross slope sequence). Linear fitting, quadratic polynomial fitting, and cubic polynomial fitting were used to fit the effective cross slope sequence, and the goodness of fit R² was calculated for each. If the linear fitting R² ≥ 0.90, the variance ≤ 0.5%², and the mean rate of change ≤ 0.02% / m, it was determined to be a stationary sub-broadening segment; if the quadratic polynomial fitting R² ≥ 0.85 and the mean rate of change is between 0.02% and 0.05% / m, it was determined to be a gradually changing sub-broadening segment; if the cubic polynomial fitting R² ≥ 0.80, the variance > 1.0%², and there are two or more trend reversals, it was determined to be a fluctuating sub-broadening segment. For example, taking the K2+300 to K2+450 sub-slope widening section as an example, its effective cross slope data includes control points K2+300 (2.0%), K2+350 (1.0%), K2+400 (3.5%), K2+450 (2.5%) and effective interpolation points K2+310 (1.45%), K2+320 (0.95%), K2+330 (0.52%), K2+410 (2.80%), etc. The calculated variance is 1.23%², the mean rate of change is 0.042% / m, and the R² after cubic polynomial fitting is 0.89. There are three trend reversals, so the sub-slope widening section to be optimized is finally determined to be a fluctuating sub-slope widening section. In this implementation plan, the determination of the type of sub-segment to be optimized is illustrated by example, as shown in Table 3 below; Table 3: Determination of Sub-segment Widening Types to be Optimized;

[0025] In step S30, the process of selecting the appropriate model to reconstruct the cross slope interpolation is as follows: The stationary type sub-segment is matched with a linear interpolation model, the gradually changing type sub-segment is matched with a quadratic polynomial interpolation model, and the fluctuating type sub-segment is matched with a cubic spline interpolation model. It should be noted that the model's adaptation is based on: The engineering scenarios for smooth sub-widening sections include bus stop sections, toll plazas, and other areas requiring smooth road surfaces. The core requirement is a stable cross slope with no unnecessary fluctuations. The essence of a linear interpolation model is to determine a straight line from two points, with the cross slope value at the intermediate section uniformly distributed according to a fixed rate of change. This rate of change is constant and can be precisely controlled. For smooth sub-widening sections, since the original effective cross slope sequence already exhibits low fluctuations and low rates of change, linear interpolation does not need to introduce complex curves. It can directly generate interpolation results with uniform rates of change that do not exceed preset thresholds based on the compliant cross slope values ​​at the start, end, and control points, avoiding additional fluctuations caused by overly complex models. The engineering scenarios for gradual sub-widening sections are the transition areas of intersection channelization sections. The core requirement is a smooth, gradual unidirectional change in cross slope. Linear interpolation can fit the trend of a constant rate of change. However, the cross slope change rate of gradual sub-widening sections may exhibit slight non-linearity. In this case, linear interpolation may lead to insufficient goodness of fit and potentially invalid interpolation. The quadratic polynomial interpolation model can accurately fit the gradual trend of the original effective cross slope sequence and avoid the problem of excessive change rate caused by abrupt changes. The engineering scenario of the undulating sub-widening section is the interchange connection section. Its core problem is that the default linear interpolation of BIM causes a large number of invalid interpolations such as reverse slope and excessive change rate. Neither linear interpolation nor quadratic polynomial interpolation can handle the complex scenario of multiple trend changes. The cubic spline interpolation model can accurately fit the complex undulating law of multiple trend changes and strictly control the change rate of adjacent sections to not exceed the preset threshold. For example, for the undulating sub-widening section K2+300-K2+450 in Table 2, cubic spline interpolation can generate a curve "smoothly transitioning from 1.0% to 3.5%" between K2+350-K2+400 based on 4 compliant control points, avoiding the generation of reverse slope, and correcting the change rate at K2+400 from 0.36% / m to the compliant range, solving the invalid problem of the default interpolation of BIM, and adapting to the multi-lane conversion requirements under complex terrain. If it is a local reconstruction of a sub-widening section, based on the range of invalid station numbers, search backward from the initial station number to find the nearest valid cross slope value. The valid cross slope value may be a valid default cross slope interpolation or a set control point cross slope value. Search backward from the end station number to find the nearest valid cross slope value. Determine the local reconstruction range based on the station number corresponding to the found valid cross slope value, and use all valid cross slope data within the local reconstruction range as reconstruction input data. For example, suppose the sub-widening segment to be optimized is from K2+300 to K2+450, and the invalid station range is from K2+355 to K2+430; Looking forward: the cross slope of 0.15% at K2+340 is an invalid cross slope value. Continuing forward, the cross slope of 0.52% at K2+330 is a valid cross slope value. Looking backwards: the cross slope of 1.75% at K2+430 is the effective cross slope value; Local reconstruction scope: station points between K2+330 and K2+430; Reconstruct the input data: K2+330 (0.52%), K2+350 (1.0%), K2+400 (3.5%), K2+430 (1.75%), and all valid cross slope values ​​between K2+355 and K2+430; If it is a global reconstruction of a sub-widening segment, then all valid cross slope data in the sub-widening segment to be optimized will be used as reconstruction input data. The reconstructed input data is input into the model adapted to the sub-widening section to be optimized, and the preset cross slope engineering constraints are used as constraints. The cross slope interpolation is reconstructed and organized into a station-cross slope data table, as shown in Table 4 below: Table 4: Data table obtained after reconstructing cross slope interpolation;

[0026] Understandably, in this implementation plan, step S30 serves the purpose of intelligently reconstructing cross slope curves for different problem sub-segments. First, it analyzes the changing trends of effective cross slope data, classifying road sections into engineering types such as stable, gradually changing, or fluctuating. Then, it matches the most suitable mathematical model, such as linear, polynomial, or spline interpolation models, for each type. Finally, based on the local or global reconstruction scope determined in step S20, and using compliant effective data points as a benchmark, it recalculates the cross slope values ​​for all station numbers under preset engineering constraints. This step is the core of the technical solution; its significance lies in replacing the simple linear interpolation defaulted to BIM with a mathematical model that better conforms to actual engineering practices, thereby generating cross slope design lines that both meet strict specification requirements (no exceeding limits, no reverse slope) and smoothly reflect the actual terrain and functional needs of the road.

[0027] Step S40: Based on the station number-cross slope data table, replace the default cross slope interpolation of the sub-widening section to be optimized with BIM reverse assignment. In step S40, the process of replacing the default cross slope interpolation of the sub-segment to be optimized is as follows: Using the API interface or script function of the BIM software, read the corresponding reconstructed cross slope value in the station number-cross slope data table according to the station number of the sub-widening section model to be optimized in the BIM, and replace the original cross slope default interpolation value (i.e. invalid or cross slope value that needs to be optimized) generated by the software default interpolation algorithm at the station number of the sub-widening section model to be optimized in the BIM. Understandably, in this implementation scheme, step S40 serves to seamlessly integrate and feed back the optimized cross slope design data into the BIM model, completing the design loop. By calling the BIM software's API or script interface, the compliant "station number-reconstructed cross slope value" table generated in step S30 is precisely reverse-assigned and replaces the corresponding invalid or suboptimal default cross slope interpolations in the original model. This step ensures that the results of all intelligent analysis and optimization calculations are directly and accurately updated to the core BIM design files, realizing an automated link from "analysis and optimization" to "model update." Ultimately, this automatically brings the road cross slope design in the BIM model to a compliant, reasonable, and smooth optimized state, greatly improving design quality and efficiency.

[0028] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A BIM-based intelligent optimization design method for the cross-section of municipal roads, characterized in that: Includes the following steps: Step S10: Divide the widening section into sub-widening sections according to the preset cross slope engineering constraints, obtain the default cross slope interpolation value generated by the BIM default interpolation algorithm in the sub-widening section, and compare it with the cross slope engineering constraints to determine whether the default cross slope interpolation value is valid. Step S20: Identify the sub-widening segment to be optimized based on whether the default cross slope interpolation is valid, and determine the cross slope interpolation reconstruction method of the sub-widening segment to be optimized based on the proportion and distribution of invalid default cross slope interpolation in the sub-widening segment to be optimized. The cross slope interpolation reconstruction method includes local reconstruction of the sub-widening segment and global reconstruction of the sub-widening segment. Step S30: Analyze the changing trend of the existing cross slope data in the sub-widening section to be optimized, determine the type of the sub-widening section to be optimized, select the appropriate model according to the type of the sub-widening section to be optimized, and reconstruct the cross slope interpolation in combination with the cross slope interpolation reconstruction method of the sub-widening section to be optimized, so as to obtain the station number-cross slope data table. Step S40: Based on the station number-cross slope data table, replace the default cross slope interpolation of the sub-widening section to be optimized with BIM reverse assignment.

2. The intelligent optimization design method for municipal road cross-sections based on BIM according to claim 1, characterized in that: The sub-broadening segment is divided as follows: Input the cross-section design drawings into the BIM software and automatically build the widening section model. In the widening section model, the widening sections with the same preset cross slope engineering constraint requirements are divided and marked as a sub-widening section. The preset cross slope engineering constraints include cross slope value requirements and cross slope change rate requirements between adjacent sections. The cross slope value requirement is that the cross slope value is within the preset cross slope range, and the cross slope change rate requirement between adjacent sections is that the cross slope change rate does not exceed the preset change rate threshold.

3. The intelligent optimization design method for municipal road cross-sections based on BIM according to claim 1, characterized in that: The process for determining whether the default cross slope interpolation is valid is as follows: If the default cross slope interpolation is not within the preset range of cross slope or the cross slope change rate corresponding to the default cross slope interpolation exceeds the preset change rate threshold, then the default cross slope interpolation is invalid. If the default cross slope interpolation is within the preset range of cross slope and the cross slope change rate corresponding to the default cross slope interpolation does not exceed the preset change rate threshold, then the default cross slope interpolation is valid.

4. The intelligent optimization design method for cross-sections of municipal roads based on BIM according to claim 1, characterized in that: The process of identifying the sub-segment to be optimized is as follows: If any invalid cross slope default interpolation exists within any sub-segment, then the sub-segment is marked as a sub-segment to be optimized.

5. The intelligent optimization design method for municipal road cross-sections based on BIM according to claim 1, characterized in that: The process of determining the cross slope interpolation reconstruction method for the sub-widening segment to be optimized includes: The proportion of invalid cross slope default interpolations in the sub-widening segment to be optimized is calculated as the proportion of invalid cross slopes among all default cross slope interpolations. If the proportion of invalid cross slopes exceeds the preset threshold for invalid cross slopes, the cross slope interpolation reconstruction method will be global reconstruction. If the proportion of invalid cross slopes does not exceed the preset threshold for invalid cross slopes, then the distribution analysis is performed on the default interpolation of invalid cross slopes, and the cross slope interpolation reconstruction method is determined based on the distribution analysis results.

6. The intelligent optimization design method for municipal road cross-sections based on BIM according to claim 5, characterized in that: The process of the distribution analysis is as follows: Obtain the default interpolation values ​​of all invalid cross slopes in the sub-widening section to be optimized, arrange them in the order of the corresponding station numbers, obtain the range of invalid station numbers based on the initial end station number and the end end station number, calculate the ratio of the length of the widening section corresponding to the range of invalid station numbers to the length of the sub-widening section to be optimized, and obtain the distribution value of invalid cross slope length. Summarize the station numbers corresponding to the default interpolation of invalid cross slopes, calculate the interval between each adjacent station number and perform mean value processing to obtain the average interval length of invalid cross slopes, calculate the ratio of the average interval length of invalid cross slopes to the length of the sub-widening section to be optimized, and obtain the discrete distribution value of invalid cross slopes. The invalid length distribution value of the cross slope is summed with the invalid discrete distribution value of the cross slope to obtain the invalid distribution value of the cross slope. The invalid distribution value of the cross slope is compared with the invalid distribution threshold of the cross slope. If the invalid distribution value of the cross slope exceeds the invalid distribution threshold of the cross slope, the cross slope interpolation reconstruction method is global reconstruction; if the invalid distribution value of the cross slope does not exceed the invalid distribution threshold of the cross slope, the cross slope interpolation reconstruction method is local reconstruction.

7. The intelligent optimization design method for cross-sections of municipal roads based on BIM according to claim 1, characterized in that: The existing cross slope data in the sub-segment to be optimized includes the cross slope values ​​at the start and end points of the sub-segment to be optimized, the cross slope values ​​of the set control points, and the valid default cross slope interpolation in the sub-segment to be optimized.

8. The intelligent optimization design method for municipal road cross-sections based on BIM according to claim 7, characterized in that: The process of determining the type of sub-segment to be optimized is as follows: The existing cross slope data in the sub-widening section to be optimized are arranged and summarized in order of the corresponding station number to obtain the effective cross slope sequence; Calculate the key features of the effective cross slope sequence, including the variance of the cross slope values ​​in the sequence, the mean cross slope rate of change, and the number of trend reversals; The effective cross slope sequence is fitted, and the type of sub-broadening segment to be optimized is determined by the goodness of fit and the key features of the effective cross slope sequence. Among them, the sub-broadening segment types to be optimized include stable sub-broadening segments, gradual sub-broadening segments, and fluctuating sub-broadening segments.

9. The intelligent optimization design method for municipal road cross-sections based on BIM according to claim 8, characterized in that: The process of selecting the appropriate model and reconstructing the cross slope interpolation is as follows: If the cross slope interpolation reconstruction method is local reconstruction, then the nearest valid cross slope value is searched forward from the initial end station number of the invalid station number range, and the nearest valid cross slope value is searched backward from the end station number. The local reconstruction range is determined according to the station number corresponding to the valid cross slope value, and all valid cross slope data within the local reconstruction range are used as reconstruction input data. If the cross slope interpolation reconstruction method is global reconstruction, then all valid cross slope data in the sub-widening segment to be optimized will be used as reconstruction input data. The reconstructed input data is input into the adaptation model, and the preset cross slope engineering constraint requirements are used as constraints. The cross slope interpolation is reconstructed and organized into station number-cross slope data.

10. The intelligent optimization design method for cross-sections of municipal roads based on BIM according to claim 1, characterized in that: The process of replacing the default cross slope interpolation with BIM reverse assignment is as follows: Using the API interface or script function of the BIM software, read the corresponding reconstructed cross slope value in the station number-cross slope data table according to the station number of the sub-widening section model to be optimized in the BIM, and replace the default cross slope interpolation value generated by the default interpolation algorithm at the corresponding station number in the BIM model.

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