A municipal road cross section intelligent optimization design method based on BIM

Abstract

The application belongs to the technical field of municipal road design, and provides a municipal road cross section intelligent optimization design method based on BIM, which comprises the following steps: performing sub-expansion section division, obtaining cross slope default interpolation generated by a BIM default interpolation algorithm in the sub-expansion section, judging whether the cross slope default interpolation is valid, and identifying a to-be-optimized sub-expansion section; determining a cross slope interpolation reconstruction mode of the to-be-optimized sub-expansion section according to the proportion and distribution of invalid cross slope default interpolations in the to-be-optimized sub-expansion section; performing change trend analysis on the existing cross slope data in the to-be-optimized sub-expansion section, determining the type of the to-be-optimized sub-expansion section, selecting an adaptive model, and reconstructing the cross slope interpolation in combination with the cross slope interpolation reconstruction mode of the to-be-optimized sub-expansion section to obtain a stake number-cross slope data table; and replacing the cross slope default interpolation of the to-be-optimized sub-expansion section by BIM reverse assignment according to the stake number-cross slope data table, thereby improving the one-time compliance rate and overall design efficiency of the cross slope design of a complex expansion section.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of municipal road design, and in particular relates to an intelligent optimization design method for a municipal road cross section based on BIM. BACKGROUND

[0002] In the design of municipal road projects, cross section design, especially the determination of road cross slope, is directly related to driving safety, road surface drainage comfort and engineering economy. With the in-depth application of building information modeling (BIM) technology in the field of municipal transportation, professional software such as Autodesk Civil 3D and Bentley OpenRoads has become a mainstream design tool. These software usually use linear interpolation algorithm based on control points to automatically generate road cross slope along the whole line, which is efficient in standard section design. However, when facing “widening sections” such as intersection channelization sections, bus bays, toll station squares and interchange connection sections, the cross slope needs complex transition due to the change in the number or width of lanes, and the default linear interpolation of the software often exposes its limitations.

[0003] The linear interpolation algorithm can only ensure the linear change of the cross slope value between the control points, and cannot perceive and comply with the actual engineering constraints. This often leads to a series of design defects: first, the generated intermediate cross section slope value may exceed the range allowed by the specification (such as negative slope, which affects drainage); second, the cross slope change rate between adjacent sections may increase sharply, exceeding the allowed change threshold per meter, causing driving bumps and even safety hazards; third, when the control points are set at improper density, the interpolation result may completely deviate from the actual smooth curve of the terrain or functional requirements. Currently, solving these problems highly depends on the experience of designers, which requires manual inspection of the interpolation results section by section and repeated adjustment of the control point positions and cross slope values to approach the compliant solution through the “trial and error” method. This process not only consumes time and effort, but also is inefficient, and is prone to omissions due to human negligence, affecting design quality and compliance, which has become a bottleneck restricting the realization of full-process automation and intelligentization of BIM technology in road design.

[0004] Therefore, the application provides an intelligent optimization design method for a municipal road cross section based on BIM. SUMMARY

[0005] In order to make up for the deficiencies of the prior art and solve at least one technical problem proposed in the background art.

[0006] The technical scheme adopted by the application to solve the technical problems is: an intelligent optimization design method for a municipal road cross section based on BIM, comprising the following steps:

[0007] Step S10, the default interpolation of the BIM of the sub-widening section is obtained by dividing the widening section into sub-widening sections according to the preset cross slope engineering constraint requirements, and the default interpolation of the cross slope is compared with the cross slope engineering constraint requirements to determine whether the default interpolation of the cross slope is valid;

[0008] Step S20, according to whether the default interpolation of the cross slope is valid, the sub-widening section to be optimized is identified, and the cross slope interpolation reconstruction mode of the sub-widening section to be optimized is determined according to the proportion and distribution of the invalid default interpolation of the cross slope in the sub-widening section to be optimized, wherein the cross slope interpolation reconstruction mode includes local reconstruction of the sub-widening section and global reconstruction of the sub-widening section;

[0009] Step S30, the type of the sub-widening section to be optimized is determined according to the change trend analysis of the existing cross slope data in the sub-widening section to be optimized, the cross slope interpolation is reconstructed according to the type of the sub-widening section to be optimized and the cross slope interpolation reconstruction mode of the sub-widening section to be optimized, and a pile number-cross slope data table is obtained;

[0010] Step S40, the default interpolation of the cross slope of the sub-widening section to be optimized is replaced by BIM reverse assignment according to the pile number-cross slope data table.

[0011] As a further technical solution of the application, the division mode of the sub-widening section is:

[0012] The cross section design drawing is input into the BIM software and the widening section model is automatically constructed, and the parts of the widening section with the same preset cross slope engineering constraint requirements are marked as a sub-widening section in the widening section model;

[0013] The preset cross slope engineering constraint requirements include the cross slope value requirement and the cross slope change rate requirement 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.

[0014] As a further technical solution of the application, the process of determining whether the default interpolation of the cross slope is valid is:

[0015] If the default interpolation of the cross slope is not within the preset cross slope range or the cross slope change rate corresponding to the default interpolation of the cross slope exceeds the preset change rate threshold, the default interpolation of the cross slope is invalid;

[0016] If the default interpolation of the cross slope is within the preset cross slope range and the cross slope change rate corresponding to the default interpolation of the cross slope does not exceed the preset change rate threshold, the default interpolation of the cross slope is valid.

[0017] As a further technical solution of the application, the process of identifying the sub-widening section to be optimized is:

[0018] Based on any sub-expansion section, if there is any invalid transverse slope default interpolation in the sub-expansion section, the sub-expansion section is marked as a to-be-optimized sub-expansion section.

[0019] As a further technical solution of the application, the process of determining the transverse slope interpolation reconstruction mode of the to-be-optimized sub-expansion section comprises:

[0020] The number proportion of the invalid transverse slope default interpolation in all transverse slope default interpolations in the to-be-optimized sub-expansion section is counted to obtain a transverse slope invalidity proportion;

[0021] If the transverse slope invalidity proportion exceeds a preset transverse slope invalidity proportion threshold, the transverse slope interpolation reconstruction mode is global reconstruction.

[0022] If the transverse slope invalidity proportion does not exceed the preset transverse slope invalidity proportion threshold, the invalid transverse slope default interpolation is analyzed in distribution, and the transverse slope interpolation reconstruction mode is determined according to the distribution analysis result.

[0023] As a further technical solution of the application, the process of distribution analysis comprises:

[0024] All invalid transverse slope default interpolations in the to-be-optimized sub-expansion section are obtained, arranged in the order of corresponding stake numbers, and the invalid stake number range is obtained according to the initial end stake number and the end stake number. The ratio of the length of the expansion section corresponding to the invalid stake number range to the length of the to-be-optimized sub-expansion section is calculated to obtain a transverse slope invalidity length distribution value.

[0025] The stake numbers corresponding to the invalid transverse slope default interpolations are summarized, the intervals between adjacent stake numbers are calculated and mean value processing is performed to obtain a transverse slope invalidity average interval length, and the ratio of the transverse slope invalidity average interval length to the length of the to-be-optimized sub-expansion section is calculated to obtain a transverse slope invalidity discrete distribution value.

[0026] The transverse slope invalidity length distribution value and the transverse slope invalidity discrete distribution value are summed to obtain a transverse slope invalidity distribution value. The transverse slope invalidity distribution value is compared with a transverse slope invalidity distribution threshold. If the transverse slope invalidity distribution value exceeds the transverse slope invalidity distribution threshold, the transverse slope interpolation reconstruction mode is global reconstruction. If the transverse slope invalidity distribution value does not exceed the transverse slope invalidity distribution threshold, the transverse slope interpolation reconstruction mode is local reconstruction.

[0027] As a further technical solution of the application, the existing transverse slope data in the to-be-optimized sub-expansion section comprises the transverse slope values of the start point and the end point of the to-be-optimized sub-expansion section, the set control point transverse slope values, and the valid transverse slope default interpolations in the to-be-optimized sub-expansion section.

[0028] As a further technical solution of the application, the process of determining the type of the to-be-optimized sub-expansion section comprises:

[0029] The existing transverse slope data in the to-be-optimized sub-expansion section is arranged and summarized in the order of corresponding stake numbers to obtain a valid transverse slope sequence.

[0030] Key features of the effective cross-slope sequence are calculated, including variance of cross-slope values in the sequence, average of cross-slope change rate, and number of trend turning points;

[0031] The effective cross-slope sequence is fitted, and the type of the to-be-optimized sub-widening section is determined by the goodness of fit and in combination with the key features of the effective cross-slope sequence;

[0032] The type of the to-be-optimized sub-widening section includes a steady sub-widening section, a gradual change sub-widening section, and a fluctuation sub-widening section.

[0033] As a further technical solution of the present application, the process of selecting an adaptive model and reconstructing cross-slope interpolation is as follows:

[0034] If the cross-slope interpolation reconstruction mode is local reconstruction, the nearest effective cross-slope value is searched from the initial end stake number of the invalid stake number range, and the nearest effective cross-slope value is searched from the end stake number, and the local reconstruction range is determined according to the stake number corresponding to the effective cross-slope value, and all effective cross-slope data in the local reconstruction range are taken as reconstruction input data;

[0035] If the cross-slope interpolation reconstruction mode is global reconstruction, all effective cross-slope data in the to-be-optimized sub-widening section are taken as reconstruction input data;

[0036] The reconstruction input data is input into the adaptive model, a preset cross-slope engineering constraint requirement is taken as a constraint condition, the cross-slope interpolation is reconstructed, and the stake number-cross-slope data is arranged.

[0037] As a further technical solution of the present application, the process of replacing the cross-slope default interpolation by BIM reverse assignment is as follows:

[0038] According to the stake number of the to-be-optimized sub-widening section model in the BIM, the corresponding reconstruction cross-slope value in the stake number-cross-slope data table is read through the API interface or script function of the BIM software, and the cross-slope default interpolation generated by the default interpolation algorithm at the corresponding stake number in the BIM model is replaced.

[0039] The present application has the following advantages:

[0040] The preset engineering constraint (cross slope value range and change rate threshold) is used for automatically screening the BIM default linear interpolation result, and the problem points (such as K2+340 0.15% low slope and K2+360-0.10% reverse slope) such as reverse slope and over-limit value are quickly located, which replaces the traditional manual checking. Secondly, by analyzing the proportion and spatial distribution characteristics of invalid points, the "local reconstruction" or "global reconstruction" strategy is intelligently judged to avoid one-size-fits-all in the optimization process. Then, according to the change trend (smooth, gradual change, fluctuation) of the effective cross slope data, the best mathematical model (linear, quadratic polynomial, cubic spline interpolation) is adaptively matched to generate a smooth transition cross slope curve under the premise of ensuring compliance. Finally, the optimized cross slope data is automatically assigned and updated to the original model through the API interface of the BIM software, forming a complete intelligent optimization closed loop. The BIM design is improved from relying on experience and repeated trial and error to a data-driven and rule-constrained automatic process, which significantly improves the one-time compliance rate and overall design efficiency of the complex widening section cross slope design. BRIEF DESCRIPTION OF DRAWINGS

[0041] The application will be further described below with reference to the drawings.

[0042] Fig. 1 is a step flow chart of a municipal road cross section intelligent optimization design method based on BIM according to an embodiment of the application;

[0043] Fig. 2 is a logic judgment diagram of a municipal road cross section intelligent optimization design method based on BIM according to an embodiment of the application. DETAILED DESCRIPTION

[0044] In order to make the technical means, creative features, purposes and effects realized by the application easy to understand, the application will be further described below with reference to the specific embodiments.

[0045] Embodiment 1: Please refer to Figs. 1-2 The municipal road cross section intelligent optimization design method based on BIM according to an embodiment of the application includes the following steps:

[0046] Step S10: The cross slope default interpolation generated by the BIM default interpolation algorithm in the sub-widening section is obtained by dividing the widening section into sub-widening sections according to the preset cross slope engineering constraint requirement, and compared with the cross slope engineering constraint requirement to determine whether the cross slope default interpolation is valid;

[0047] In step S10, the sub-widening section division of the widening section is as follows:

[0048] The cross-section design drawing is input into the BIM software, and a widening section model is automatically constructed. In the widening section model, the part of the widening section with the same preset transverse slope engineering constraint requirement is divided and marked as a sub-widening section. For example, in the part of the widening section with pile number ranging from K2+100 to K2+200, the transverse slope value and the transverse slope change rate of each pile number point are consistent;

[0049] The preset transverse slope engineering constraint requirement includes the transverse slope value requirement and the transverse slope change rate between adjacent sections. For example, the transverse slope value is within the preset transverse slope range (such as between 0.5% and 4%); and the transverse slope change rate between adjacent sections does not change by more than a preset change rate threshold (such as 0.5%) per meter;

[0050] In step S10, it should be noted that the widening section represents a road section in which the number of lanes or the width of the road is increased, such as a road intersection channelization section, a bus station section, a toll station square, etc.

[0051] In step S10, it should also be noted that the BIM default interpolation algorithm represents a mathematical method (usually linear interpolation) for automatically calculating the transverse slope of all sections in the middle according to the transverse slope values of the starting point and the ending point and the transverse slope values of the set control points in the BIM road design software (such as Civil 3D, OpenRoads). The transverse slope default interpolation is the original transverse slope value calculated by the BIM default interpolation algorithm without manual correction. For example, there is a widening section of a road intersection channelization section with a pile number range of K2+300 to K2+450 (length of 150 meters). The preset transverse slope engineering constraint requirement is that the transverse slope is between 0.5% and 4%, and the transverse slope change rate does not exceed 0.3% / m. The engineer only sets four control points, as shown in Table 1 below. The transverse slope default interpolation and the transverse slope change rate calculated by the BIM are shown in Table 2 below:

[0052] Table 1: Set control point transverse slope value;

[0053]

[0054] Table 2: Transverse slope default interpolation and transverse slope change rate calculated by the BIM default interpolation algorithm;

[0055]

[0056] In step S10, the process of determining whether the transverse slope default interpolation is valid is as follows:

[0057] The transverse slope default interpolation is compared with the preset transverse slope engineering constraint requirement;

[0058] If the transverse slope default interpolation is not within the preset transverse slope range or the transverse slope change rate corresponding to the transverse slope default interpolation exceeds the preset change rate threshold, it indicates that the transverse slope default interpolation is invalid.

[0059] Conversely, if the transverse slope default interpolation is within the preset range of the transverse slope and the transverse slope change rate corresponding to the transverse slope default interpolation does not exceed the preset change rate threshold, it indicates that the transverse slope default interpolation is valid.

[0060] It can be understood that in the present embodiment, the function of step S10 is to perform fine sub-regional division on the road widening section by the preset transverse slope engineering constraint requirements (such as the transverse slope value range and the transverse slope change rate limit). The main purpose is to automatically identify and verify whether the original transverse slope value generated by the BIM software default interpolation algorithm meets the engineering specification. By systematically comparing the "transverse slope default interpolation" generated by the algorithm with the constraint conditions, the problematic road section, such as the position where the transverse slope exceeds the allowed range or the change rate is too large, can be quickly and accurately located. This step provides a clear target and basis for subsequent optimization work, which is equivalent to completing the automatic "compliance screening" of the initial design results, thereby replacing the inefficient mode of traditional manual point-by-point checking.

[0061] Step S20, according to whether the transverse slope default interpolation is valid, identifying the sub-widening section to be optimized, and determining the transverse slope interpolation reconstruction method of the sub-widening section to be optimized according to the proportion and distribution of invalid transverse slope default interpolations in the sub-widening section to be optimized, wherein the transverse slope interpolation reconstruction method includes sub-widening section local reconstruction and sub-widening section global reconstruction;

[0062] In step S20, the process of identifying the sub-widening section to be optimized according to whether the transverse slope default interpolation is valid is:

[0063] Based on any sub-widening section;

[0064] If there is any invalid transverse slope default interpolation in the generated transverse slope default interpolations within the sub-widening section, the sub-widening section is marked as a sub-widening section to be optimized, indicating that transverse slope interpolation optimization is needed;

[0065] If there is no invalid transverse slope default interpolation in the generated transverse slope default interpolations within the sub-widening section, the sub-widening section is marked as a normal sub-widening section, indicating that transverse slope interpolation optimization is not needed, and no operation is performed;

[0066] In step S20, the process of determining the transverse slope interpolation reconstruction method of the sub-widening section to be optimized is:

[0067] Based on any sub-widening section to be optimized;

[0068] Statistical proportion of the number of invalid transverse slope default interpolations in all transverse slope default interpolations in the sub-widening section to be optimized, to obtain a transverse slope invalidity proportion;

[0069] Compare the transverse slope invalidity proportion with a preset transverse slope invalidity proportion threshold;

[0070] If the transverse slope invalidity ratio exceeds the preset transverse slope invalidity ratio threshold, the transverse slope interpolation reconstruction mode of the sub-widening section to be optimized is global reconstruction;

[0071] If the transverse slope invalidity ratio does not exceed the preset transverse slope invalidity ratio threshold, distribution analysis of transverse slope invalidity is performed;

[0072] It should be noted that the transverse slope invalidity ratio threshold is used to make a decision between local reconstruction and global reconstruction strategies, and its setting method is as follows: first, the base value can be set to 30% according to general engineering experience; second, it needs to be calibrated according to the provisions of road grade in the "Code for Design of Urban Road Engineering" (CJJ37), and stricter values (such as 20%~25%) are used for high-grade roads such as expressways and main roads, and looser values (such as 30%~35%) are used for secondary roads and branch roads; finally, it can be fine-tuned according to the target of the design stage. The engineering logic of the transverse slope invalidity ratio threshold is that when the invalidity ratio exceeds this threshold, it indicates that the default interpolation of BIM has systematically deviated from the engineering constraints in this section, and using global reconstruction is more efficient and reliable than complex local repair;

[0073] In step S20, the distribution analysis process is:

[0074] All invalid transverse slope default interpolations in the sub-widening section to be optimized are obtained, and are sequentially arranged according to the pile numbers corresponding to the invalid transverse slope default interpolations. After the arrangement, the pile number range corresponding to the invalid transverse slope default interpolations is obtained according to the initial end pile number and the end pile number, and is marked as the invalid pile number range. The length of the widening section corresponding to the invalid pile number range is obtained, and is proportionally calculated with the length of the sub-widening section to be optimized to obtain the transverse slope invalidity length distribution value;

[0075] For example, assuming that the sub-widening section to be optimized is K2+300 to K2+450, the length is 150 meters, the invalid pile number range is K2+355 to K2+430, and the length is 75 meters, then the transverse slope invalidity distribution value is 75 / 150=0.5;

[0076] The pile numbers corresponding to the invalid transverse slope default interpolations are summarized, the intervals between adjacent pile numbers are calculated, and mean value processing is performed to obtain the transverse slope invalidity average interval length. The transverse slope invalidity average interval length is proportionally calculated with the length of the sub-widening section to be optimized to obtain the transverse slope invalidity discrete distribution value;

[0077] The transverse slope invalidity length distribution value and the transverse slope invalidity discrete distribution value are summed to obtain the transverse slope invalidity distribution value;

[0078] The transverse slope invalidity distribution value is compared with the transverse slope invalidity distribution threshold;

[0079] If the transverse slope invalid distribution value exceeds the transverse slope invalid distribution threshold value, the transverse slope interpolation reconstruction mode of the sub-widening section to be optimized is global reconstruction;

[0080] If the transverse slope invalid distribution value does not exceed the transverse slope invalid distribution threshold value, the transverse slope interpolation reconstruction mode of the sub-widening section to be optimized is local reconstruction;

[0081] It should be noted that local reconstruction refers to only recalculating the transverse slope value in the local stake number range where the invalid transverse slope default interpolation is located, and global reconstruction refers to comprehensively recalculating the transverse slope value of the entire sub-widening section to be optimized;

[0082] It should also be noted that the transverse slope invalid distribution threshold value is used to intelligently select the reconstruction strategy based on the spatial distribution characteristics of the invalid points. Its setting is based on the analysis of the transverse slope invalid distribution value, and is calculated from the length distribution value reflecting the degree of aggregation and the discrete distribution value reflecting the degree of dispersion. The theoretical range of the transverse slope invalid distribution threshold value is (0, 2), and the setting method is as follows: through numerical experiments and engineering case analysis to determine the decision boundary, when less than a certain value (such as 0.5), the invalid points are highly aggregated, and local reconstruction is suitable; when greater than another value (such as 1.0), the invalid points are highly dispersed, and global reconstruction is suitable. The transverse slope invalid distribution threshold value is a critical value between the two, and the typical value is 0.6. Its engineering basis is: when greater than 0.6, it indicates that the spatial distribution of invalid points has transitioned from local aggregation to widespread dispersion, and global reconstruction can more effectively break the mutual constraints between invalid points and generate a smooth transverse slope curve as a whole;

[0083] It can be understood that the transverse slope invalid distribution value is a key indicator that comprehensively represents the spatial distribution characteristics of the transverse slope design problem. Its physical meaning lies in quantifying the aggregation pattern and dispersion degree of the invalid transverse slope default interpolation. Specifically, the transverse slope invalid length distribution value reflects the overall length distribution of the invalid transverse slope default interpolation, and the transverse slope invalid discrete distribution value reflects the dispersion and independence of the invalid transverse slope default interpolation. The smaller the transverse slope invalid distribution value, the higher the aggregation of the problem points, and the stronger the mutual influence. When the transverse slope invalid distribution value is low, it indicates that the invalid transverse slope default interpolation is local and discrete, and local reconstruction is suitable. When the transverse slope invalid distribution value is high, it means that the invalid transverse slope default interpolation has a wide range and strong dispersion, and global reconstruction is suitable;

[0084] It can be understood that in the present embodiment, the role of step S20 is to intelligently determine the optimization strategy for each problem sub-widening section (i.e., the "to-be-optimized sub-widening section") based on the screening result of step S10. It comprehensively judges whether the problem is local and scattered or large-scale and systematic by calculating the proportion and spatial distribution characteristics (such as the aggregation length and dispersion degree) of the invalid transverse slope points. According to this, the optimization mode is classified as "local reconstruction" or "global reconstruction". The core significance of this step is to realize the differentiation and precision of the optimization strategy, avoiding the "one-size-fits-all" processing method. It ensures that for small-scale and concentrated problems, local adjustment is adopted, and for large-scale and dispersed complex problems, comprehensive recalculation is started, thereby ensuring the optimization effect while improving the overall processing efficiency.

[0085] Embodiment 2: Please refer to Figs. 1-2 As shown in the figure, based on the basis of embodiment 1, the BIM-based municipal road cross section intelligent optimization design method described in the embodiment of the application further comprises the following steps:

[0086] Step S30, according to the existing transverse slope data in the to-be-optimized sub-widening section, the change trend is analyzed, the type of the to-be-optimized sub-widening section is determined, the adaptive model is selected according to the type of the to-be-optimized sub-widening section, and the transverse slope interpolation is reconstructed by combining the transverse slope interpolation of the to-be-optimized sub-widening section, to obtain a pile number-transverse slope data table;

[0087] In step S30, the existing transverse slope data in the to-be-optimized sub-widening section includes the transverse slope values of the start point and the end point, the transverse slope values of the set control points, and the effective transverse slope default interpolation in the to-be-optimized sub-widening section;

[0088] In step S30, the process of determining the type of the to-be-optimized sub-widening section is:

[0089] The existing transverse slope data in the to-be-optimized sub-widening section is arranged and summarized in the corresponding pile number order to obtain the effective transverse slope sequence of the to-be-optimized sub-widening section;

[0090] The key features of the effective transverse slope sequence are calculated, including the variance of the transverse slope values in the sequence, the average transverse slope change rate, and the number of trend turning points (the number of positive and negative alternations of the transverse slope values in the effective transverse slope sequence), etc.

[0091] The effective transverse slope sequence is fitted by linear fitting, quadratic polynomial fitting and cubic polynomial fitting respectively, and the fitting goodness R2 is calculated. If the linear fitting R2 is greater than or equal to 0.90, the variance is less than or equal to 0.5%2, and the average change rate is less than or equal to 0.02% / m, it is determined as a stable type sub-widening section; if the quadratic polynomial fitting R2 is greater than or equal to 0.85 and the average change rate is between 0.02%-0.05% / m, it is determined as a gradual type sub-widening section; if the cubic polynomial fitting R2 is greater than or equal to 0.80, the variance is greater than 1.0%2, and there are two or more trend turning points, it is determined as a fluctuating type sub-widening section.

[0092] For example, taking the K2+300 to K2+450 sub-widening section as an example, the effective transverse 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%) and the like, the variance is calculated as 1.23%2, the average change rate is 0.042% / m, the cubic polynomial fitting R2=0.89, and there are three trend turning points, so the final judgment of the type of the sub-widening section to be optimized is a fluctuating type sub-widening section.

[0093] In the present embodiment, the type judgment of the sub-widening section to be optimized is exemplarily illustrated as shown in Table Three below.

[0094] Table Three: Type judgment of sub-widening section to be optimized

[0095]

[0096] In step S30, the process of selecting the adaptive model to reconstruct the transverse slope interpolation is as follows:

[0097] The stable type sub-widening section matches the linear interpolation model, the gradual type sub-widening section matches the quadratic polynomial interpolation model, and the fluctuating type sub-widening section matches the cubic spline interpolation model.

[0098] It should be noted that the basis for adapting the model is:

[0099] The engineering scene of the stable type sub-widening section is the bus station section and the toll station square, etc. which need flat road surface. The core demand is stable transverse slope and no extra fluctuation. The essence of the linear interpolation model is to determine a straight line through two points, and the transverse slope value of the middle section is uniformly distributed according to the fixed change rate. The change rate is constant and can be accurately controlled. For the stable type sub-widening section, since the original effective transverse slope sequence has shown the characteristics of low fluctuation and low change rate, the linear interpolation does not need to introduce complex curves. It can directly generate the interpolation results with uniform change rate and not exceeding the preset threshold based on the compliant transverse slope values of the start point, end point and control point, avoiding additional fluctuations caused by excessive complexity of the model. The engineering scene of the gradual type sub-widening section is the transition area of the intersection channelization section. The core demand is one-way smooth transition of the transverse slope. The linear interpolation can fit the trend of constant change rate. However, the change rate of the transverse slope of the gradual type sub-widening section may be slightly nonlinear. At this time, the linear interpolation may lead to insufficient fitting degree and may appear invalid interpolation. The quadratic polynomial interpolation model can not only accurately fit the gradual trend of the original effective transverse slope sequence, but also avoid the problem of exceeding the change rate caused by sudden change. The engineering scene of the fluctuation type sub-widening section is the interchanges connection section. The core problem is a large number of invalid interpolations such as reverse slope and excessive change rate caused by the default linear interpolation of BIM. The linear interpolation and the quadratic polynomial interpolation cannot handle the complex scene of multiple trend turning. The cubic spline interpolation model can not only accurately fit the complex fluctuation law of multiple trend turning, but also strictly control the change rate of adjacent sections not to exceed the preset threshold. For example, for the fluctuation type sub-widening section of K2+300-K2+450 in Table 2, the cubic spline interpolation can generate a curve of “smoothly transition from 1.0% to 3.5%” between K2+350-K2+400 based on 4 compliant control points, avoiding 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 demand under complex terrain.

[0100] If local reconstruction is performed for the sub-widening section, the nearest effective transverse slope value is found by searching from the initial end stake number forward according to the invalid stake number range, wherein the effective transverse slope value may be an effective transverse slope default interpolation or a set control point transverse slope value. The nearest effective transverse slope value is found by searching from the end stake number backward. The local reconstruction range is determined according to the stake number corresponding to the found effective transverse slope value, and all effective transverse slope data in the local reconstruction range are taken as the reconstruction input data.

[0101] For example, it is assumed that the sub-widening section to be optimized is K2+300 to K2+450, and the invalid stake number range is K2+355 to K2+430.

[0102] Forward search: the transverse slope of K2+340 is 0.15%, which is an invalid transverse slope value. Continue to search forward, and the transverse slope of K2+330 is 0.52%, which is an effective transverse slope value.

[0103] Backward search: K2+430, the effective cross slope value is 1.75%;

[0104] Local reconstruction range: stake points between K2+330 and K2+430;

[0105] Reconstruction input data: K2+330 (0.52%), K2+350 (1.0%), K2+400 (3.5%), K2+430 (1.75%), and all effective cross slope values between K2+355 and K2+430;

[0106] If global reconstruction is performed for the sub-widening section, all effective cross slope data in the to-be-optimized sub-widening section are taken as reconstruction input data;

[0107] The reconstruction input data are input into the model adapted to the to-be-optimized sub-widening section, and the preset cross slope engineering constraint requirement is taken as a constraint condition, the cross slope interpolation is reconstructed, and a stake number-cross slope data table is arranged, which is shown in Table Four in the following table as an example:

[0108] Table Four: Data table obtained after reconstruction of cross slope interpolation;

[0109]

[0110] It can be understood that in the present embodiment, the role of step S30 is to perform intelligent cross slope curve reconstruction for different problem sub-widening sections. First, it analyzes the change trend of effective cross slope data, and classifies the road sections into engineering types such as smooth type, gradual change type or fluctuation type. Then, the most suitable mathematical model is matched for different types, such as linear, polynomial or spline interpolation model. Finally, according to the local or global reconstruction range determined in step S20, the cross slope values of all stake numbers are recalculated under the preset engineering constraint with the effective data points as the basis. This step is the core of the technical solution, and its significance is to replace the BIM default simple linear interpolation with a mathematical model that is more in line with the actual laws of engineering, thereby generating a cross slope design line that not only meets the strict specification requirements (not exceeding the limit, not reversing the slope), but also smoothly reflects the real terrain and functional requirements of the road.

[0111] Step S40, according to the stake number-cross slope data table, the cross slope default interpolation of the to-be-optimized sub-widening section is replaced by BIM reverse assignment;

[0112] In step S40, the process of replacing the cross slope default interpolation of the to-be-optimized sub-widening section is as follows:

[0113] By the API interface or script function of the BIM software, the corresponding reconstructed transverse slope value in the pile number-transverse slope data table is read according to the pile number of the sub-widening section model to be optimized in the BIM, and the original transverse slope default interpolation (i.e. invalid or optimized transverse slope value) of the sub-widening section model to be optimized in the BIM at the pile number is replaced;

[0114] It can be understood that in the present embodiment, the role of step S40 is to seamlessly integrate and feed back the optimized transverse slope design data into the BIM model, and complete the design closed loop. By calling the API or script interface of the BIM software, the "pile number-reconstructed transverse slope value" table generated in step S30 is accurately assigned in reverse and replaces the corresponding invalid or poor transverse slope default interpolation in the original model. This step ensures that the results of all intelligent analysis and optimization calculation can be directly and accurately updated to the core BIM design file, realizing the automatic link from "analysis and optimization" to "model update". Finally, the road transverse slope design in the BIM model is automatically optimized to be compliant, reasonable and smooth, greatly improving the design quality and efficiency.

[0115] The basic principles, main features and advantages of the present application are shown and described above. It should be understood by those skilled in the art that the present application is not limited by the above examples, and the above examples and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A municipal road cross-section intelligent optimization design method based on BIM, characterized in that: The method comprises the following steps: Step S10, sub-widening section division is performed on the widening section by presetting the cross slope engineering constraint requirements, cross slope default interpolation generated by the BIM default interpolation algorithm in the sub-widening section is obtained, and the cross slope default interpolation is compared with the cross slope engineering constraint requirements to determine whether the cross slope default interpolation is valid; Step S20, according to whether the cross slope default interpolation is valid, the sub-widening section to be optimized is identified, and according to the proportion and distribution of the invalid cross slope default interpolation in the sub-widening section to be optimized, the cross slope interpolation reconstruction mode of the sub-widening section to be optimized is determined, wherein the cross slope interpolation reconstruction mode comprises local reconstruction of the sub-widening section and global reconstruction of the sub-widening section; Step S30, the change trend of the existing cross slope data in the sub-widening section to be optimized is analyzed to determine the type of the sub-widening section to be optimized, an adaptive model is selected according to the type of the sub-widening section to be optimized, and the cross slope interpolation is reconstructed in combination with the cross slope interpolation reconstruction mode of the sub-widening section to be optimized to obtain a pile number-cross slope data table; Step S40, according to the pile number-cross slope data table, the cross slope default interpolation of the sub-widening section to be optimized is replaced by BIM reverse assignment.

2. The BIM-based municipal road cross-section intelligent optimization design method according to claim 1, characterized in that: The division mode of the sub-widening section is as follows: The cross section design drawing is input into the BIM software and the widening section model is automatically constructed, and in the widening section model, the partial widening sections with the same preset cross slope engineering constraint requirements are marked as a sub-widening section; The preset cross slope engineering constraint requirements comprise a cross slope value requirement and a cross slope change rate requirement between adjacent sections, the cross slope value requirement is that the cross slope value is within a preset cross slope range, and the cross slope change rate requirement between adjacent sections is that the cross slope change rate does not exceed a preset change rate threshold.

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

4. The BIM-based municipal road cross-section intelligent optimization design method according to claim 1, characterized in that: The process of identifying the sub-widening section to be optimized is as follows: Based on any sub-widening section, if there is any invalid cross slope default interpolation in the sub-widening section, the sub-widening section is marked as the sub-widening section to be optimized.

5. The BIM-based municipal road cross-section intelligent optimization design method according to claim 1, characterized in that: The process of determining the cross slope interpolation reconstruction mode of the sub-widening section to be optimized comprises: The number proportion of the invalid cross slope default interpolation in all cross slope default interpolations in the sub-widening section to be optimized is counted to obtain a cross slope invalidity proportion; If the cross slope invalidity proportion exceeds a preset cross slope invalidity proportion threshold, the cross slope interpolation reconstruction mode is global reconstruction; If the cross slope invalidity proportion does not exceed the preset cross slope invalidity proportion threshold, the invalid cross slope default interpolation is analyzed in distribution, and the cross slope interpolation reconstruction mode is determined according to the distribution analysis result.

6. The BIM-based municipal road cross-section intelligent optimization design method according to claim 5, characterized in that: The process of distribution analysis is as follows: All invalid cross slope default interpolations in the sub-widening section to be optimized are obtained, arranged in order according to the corresponding pile numbers, the invalid pile number range is obtained according to the initial end pile number and the end end pile number, the ratio of the length of the widening section corresponding to the invalid pile number range to the length of the sub-widening section to be optimized is calculated to obtain a cross slope invalid length distribution value; The invalid transverse slope default interpolation corresponding pile numbers are summarized, the intervals between adjacent pile numbers are calculated and mean value processing is performed to obtain an invalid transverse slope average interval length, and a ratio of the invalid transverse slope average interval length to the length of the to-be-optimized sub-widening section is calculated to obtain a transverse slope invalid discrete distribution value; The transverse slope invalid length distribution value and the transverse slope invalid discrete distribution value are summed to obtain a transverse slope invalid distribution value; the transverse slope invalid distribution value is compared with a transverse slope invalid distribution threshold value, if the transverse slope invalid distribution value exceeds the transverse slope invalid distribution threshold value, the transverse slope interpolation reconstruction mode is global reconstruction, and if the transverse slope invalid distribution value does not exceed the transverse slope invalid distribution threshold value, the transverse slope interpolation reconstruction mode is local reconstruction.

7. The BIM-based municipal road cross-section intelligent optimization design method according to claim 1, characterized in that: The existing transverse slope data in the to-be-optimized sub-widening section include transverse slope values at the start point and the end point of the to-be-optimized sub-widening section, control point transverse slope values set and valid transverse slope default interpolations in the to-be-optimized sub-widening section.

8. The BIM-based municipal road cross-section intelligent optimization design method according to claim 7, characterized in that: The process of determining the type of the to-be-optimized sub-widening section is as follows: The existing transverse slope data in the to-be-optimized sub-widening section are arranged in sequence according to corresponding pile numbers to obtain a valid transverse slope sequence; Key features of the valid transverse slope sequence are calculated, and the key features include a variance of the transverse slope values in the sequence, a mean value of a transverse slope change rate and a trend turning number; The valid transverse slope sequence is fitted, and the type of the to-be-optimized sub-widening section is determined by a fitting degree and in combination with the key features of the valid transverse slope sequence; The type of the to-be-optimized sub-widening section includes a steady type sub-widening section, a gradual change type sub-widening section and a fluctuation type sub-widening section.

9. The BIM-based municipal road cross-section intelligent optimization design method according to claim 8, characterized in that: The process of selecting an adaptive model and reconstructing transverse slope interpolation is as follows: If the transverse slope interpolation reconstruction mode is local reconstruction, the nearest valid transverse slope value is searched from an initial end pile number of the invalid pile number range, the nearest valid transverse slope value is searched from an end pile number, and a local reconstruction range is determined according to pile numbers corresponding to the valid transverse slope values, and all valid transverse slope data in the local reconstruction range are taken as reconstruction input data; If the transverse slope interpolation reconstruction mode is global reconstruction, all valid transverse slope data in the to-be-optimized sub-widening section are taken as reconstruction input data; The reconstruction input data are input into the adaptive model, a preset transverse slope engineering constraint requirement is taken as a constraint condition, transverse slope interpolation is reconstructed, and pile number-transverse slope data are arranged.

10. The BIM-based municipal road cross-section intelligent optimization design method according to claim 1, characterized in that: The process of replacing the transverse slope default interpolation by BIM reverse assignment is as follows: According to an API interface or a script function of a BIM software, a corresponding reconstruction transverse slope value in the pile number-transverse slope data table is read according to a pile number of a to-be-optimized sub-widening section model in the BIM, and a transverse slope default interpolation generated by a default interpolation algorithm at a corresponding pile number in the BIM model is replaced.

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