Road construction progress accurate monitoring and scheduling method and system based on intelligent perception

Abstract

The invention belongs to the technical field of construction scheduling, and provides a road construction progress accurate monitoring and scheduling method and system based on intelligent perception, and the method comprises the steps: building a construction constraint table through analysis of a construction drawing and a three-dimensional information model, collecting the project amount through a three-dimensional point cloud registration algorithm, calculating the progress deviation rate, and obtaining a construction progress scheduling result; establishing a unique identifier for the overlapping structure subunit to construct a progress tracing chain and a tracing network, extracting a cross-chain branch subchain based on a resource intersection, a space proximity ratio and a time window overlapping ratio, and identifying a resource competition point and a urgency demand point through an equipment reuse rate and a collaborative urgency index; the resources are dynamically allocated by constructing a resource scheduling model, the system comprises a constraint construction module, a deviation acquisition module, a progress tracing module, a scheduling analysis module and a resource allocation module, a construction monitoring scheduling closed-loop scheme is constructed, and the construction progress management and control precision and the resource utilization efficiency are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of construction scheduling, and specifically relates to a method and system for precise monitoring and scheduling of road construction progress based on intelligent perception. Background Art

[0002] Road construction is a core link in urban infrastructure construction, and the scientific nature of its progress control and resource scheduling directly affects the project quality, construction period and cost. Traditional road construction management relies on manual inspections, two-dimensional drawing markings and empirical scheduling, with many deficiencies.

[0003] Existing technologies are difficult to identify overlapping structures (such as the spatial overlap between the subgrade cushion and the base course) and hidden structures (such as underground pipeline burial, pipeline crossing) in road construction, resulting in the inability to quantify the degree of spatial overlap of overlapping structures (such as volume ratio, projection area), the lack of key monitoring nodes, and prone to quality hazards such as poor interlayer bonding; parameters such as the burial depth and covering soil type of hidden structures rely on manual records, lacking automated traceability means, and it is difficult to quickly locate the root cause when problems such as leakage and misalignment occur.

[0004] Existing construction management technologies lack the ability to automatically analyze the deviation conduction path. A single progress deviation may cause a global impact through the process logic chain (such as the lag of base course construction leading to the delay of surface course paving), but traditional methods are difficult to quickly locate the associated sub-units, and the tracing cost is high; the resource scheduling of existing technologies (such as pavers, material transportation) relies on manual experience allocation, lacking quantitative analysis of resource competition points across regions and processes (such as equipment reuse rate, working face space conflict), which is prone to equipment idleness or material supply imbalance, resulting in construction period delays and cost waste.

[0005] Therefore, the present invention provides a method and system for precise monitoring and scheduling of road construction progress based on intelligent perception. Summary of the Invention

[0006] In order to make up for the deficiencies of the existing technology and solve at least one of the technical problems proposed in the background art.

[0007] The technical solution adopted by the present invention to solve its technical problems is: a method and system for precise monitoring and scheduling of road construction progress based on intelligent perception, the method includes: Collect the quantities of work of different hierarchical structures of road construction by using a three-dimensional point cloud registration algorithm, and perform construction deviation analysis to obtain the progress deviation rate; Obtain the progress deviation ratio of the overlapping structure sub-units, and construct a road construction progress traceability chain. Through deviation conduction analysis of the road construction overlapping structure, extract the progress traceability sub-chain, and then combine the spatial coordinates and process logic of the three-dimensional information model, and analyze the conduction relationship of the progress traceability sub-chain through an association rule algorithm to construct a progress traceability network; Extract the cross-chain branch sub-chain of the progress traceability network, perform resource scheduling analysis on the cross-chain branch sub-chain, identify the resource competition points of the cross-chain branch sub-chain, conduct collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chain; Obtain the construction scheduling resources for the urgent demand points, establish a resource allocation group, construct a resource scheduling model and input the resource allocation group to achieve resource allocation for the overlapping structure of road construction.

[0008] Furthermore, obtain the road construction drawings and the three-dimensional information model, perform explicit analysis on the construction drawings and the three-dimensional information model through intelligent perception algorithms, determine the overlapping and hidden structure units in the road construction process, extract the construction characteristic parameters of the overlapping and hidden structures, and construct a construction constraint table.

[0009] Furthermore, the method for performing the construction deviation analysis is as follows: Obtain the three-dimensional information models of all hierarchical structures of road construction, match and correspond the three-dimensional information models of the structures with the construction constraint table to obtain the corresponding road construction structures; Obtain the construction quantities of different levels and the corresponding time windows, obtain the time window of the current construction quantity from the construction constraint table, and calculate the deviation ratio to obtain the progress deviation ratio of the construction progress; Among them, the hierarchical structures include: surface structure, hidden structure, and overlapping structure.

[0010] Furthermore, the method for obtaining the construction quantities of the different levels is as follows: Collect the construction quantities of the surface structure of road construction through the three-dimensional point cloud registration algorithm; For the hidden structure of road construction, determine the construction quantity of the hidden structure of road construction in combination with the burial depth and position in the construction constraint table; For the construction quantity of the overlapping structure of road construction, obtain the road construction data and verify and analyze it in combination with the three-dimensional information model, and calculate the construction quantity of the overlapping structure.

[0011] Furthermore, the method for constructing the progress traceability network is as follows: Obtain the sub-units of the overlapping structure corresponding to the negative progress deviation rate from the road construction progress traceability chain to obtain the progress lagging units; Based on the traceability chain of road construction, obtain the progress deviation rates of the adjacent sub-units of the progress lagging units downward, calculate the deviation ratio of the progress deviation rate of the progress lagging units to the progress deviation rates of the adjacent sub-units to obtain the deviation conduction rate; Extract the progress traceability sub-chains of multiple sub-units of the progress traceability chain based on the deviation conduction rate, and obtain the progress traceability sub-chains of all overlapping structures of road construction; Perform correlation analysis on the progress trace sub-chains of all structures, and connect the progress trace sub-chains through a branch structure where there is a correlation relationship to form a progress trace network.

[0012] Further, the method for obtaining the construction progress trace chain is as follows: Obtain the sub-units of each overlapping structure in road construction and establish a unique identification system; Determine the trace chain of road construction according to the construction sequence of each sub-unit of the overlapping structure; Obtain the progress deviation ratio of each sub-unit of the overlapping structure and perform coupling processing with the trace chain of road construction to construct the road construction progress trace chain.

[0013] Further, the method for identifying the resource competition points of the cross-chain branch sub-chains is as follows: By constructing the graph structure of the progress trace network, represent the directed edges of the sub-units of the overlapping structure as conduction relationships; Based on the sub-chain screening conditions, establish a sub-chain screening algorithm to extract the cross-chain branch sub-chains from the graph structure of the progress trace network; Obtain the equipment reuse rate and the time window coincidence ratio within the overlapping duration of the cross-chain branch sub-chain and its adjacent cross-chain branch sub-chains, establish a resource competition analysis model, and identify the resource competition points of the cross-chain branch sub-chains.

[0014] Further, the method for establishing the resource competition analysis model is as follows: The resource competition analysis model is established as follows: Obtain the time window overlapping duration, the time window coincidence ratio, and the equipment reuse rate of the cross-chain branch sub-chain and its adjacent sub-chains: Taking the time window coincidence ratio as the horizontal axis and the equipment reuse rate as the vertical axis, establish a two-dimensional resource competition analysis model.

[0015] Further, the method for determining the urgent demand points of the cross-chain branch sub-chains is as follows: Effectively screen the equipment reuse rate of the resource competition points within the overlapping duration to obtain the effective reuse rate; Obtain the resource competition points, perform normalization processing on the time window coincidence ratio and the effective reuse rate respectively, and perform a product processing on the reciprocal of the normalized time window coincidence ratio and the effective reuse rate to obtain the collaborative urgency index; Based on the collaborative urgency index, screen all the competing resource points to obtain the urgent demand points.

[0016] The intelligent perception-based precise monitoring and scheduling system for road construction progress includes the following modules: Constraint construction module: It is used to obtain road construction drawings and three-dimensional information models, conduct explicit analysis on the construction drawings and three-dimensional information models through intelligent perception algorithms, determine the overlapping and hidden structural units in the road construction process, extract the construction characteristic parameters of the overlapping and hidden structures, and construct a construction constraint table; Deviation acquisition module: It uses the three-dimensional point cloud registration algorithm to collect the quantities of work of different hierarchical structures of road construction, and conducts construction deviation analysis to obtain the progress deviation rate; Progress tracing module: It is used to obtain the progress deviation ratio of the overlapping structural subunits, construct a road construction progress tracing chain, conduct deviation conduction analysis on the overlapping structures of road construction, extract the progress tracing sub-chains, and then combine the spatial coordinates and process logic of the three-dimensional information model, and analyze the conduction relationship of the progress tracing sub-chains through the association rule algorithm to construct a progress tracing network; Scheduling analysis module: It is used to extract the cross-chain branch sub-chains of the progress tracing network, conduct resource scheduling analysis on the cross-chain branch sub-chains, identify the resource competition points of the cross-chain branch sub-chains, conduct collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chains; Resource allocation module: It obtains the construction scheduling resources of the urgent demand points, establishes a resource allocation group, constructs a resource scheduling model and inputs the resource allocation group to realize the resource allocation of the overlapping structures of road construction.

[0017] The beneficial effects of the present invention are as follows: 1. By using the three-dimensional information model and construction drawings, it can intelligently sense the overlapping (such as multi-layer paving structures) and hidden (such as underground pipelines) structural units in road construction, quantify the spatial overlapping degree (the proportion of overlapping volume) and hidden level (cover soil thickness, burial depth), construct a construction constraint table including spatial, temporal, and material parameters, and provide a structured data benchmark for quality control and engineering quantity measurement; calibrate the measured data through the three-dimensional point cloud registration algorithm, realize the collection of the quantities of work of the surface layer structure, hidden structure, and overlapping structure, and calculate the progress deviation rates of the surface layer, hidden layer, and overlapping layer based on the time window constraint of the construction constraint table, which can real-time feedback the difference between the construction progress and the plan and provide data support for dynamic adjustment.

[0018] 2. Construct a progress tracing chain through the unique identification system and process logic, use the deviation conduction rate as an index, and extract the progress tracing sub-chains by using graph theory algorithms, which is conducive to realizing the visualization of the path from a single deviation source to the global impact and shortening the problem location time; combine the spatial coordinates of the three-dimensional model and the process logic, construct a progress tracing network through the association rule algorithm, identify the deviation conduction mode, and support multi-level and cross-regional progress impact analysis; automatically extract cross-chain branch sub-chains based on multi-dimensional conditions such as resource intersection, spatial proximity ratio (operation surface coincidence degree), and time window coincidence ratio, identify resource competition points with high equipment reuse rate and significant time window overlap, and locate the scheduling bottleneck.

[0019] 3. Construct a resource scheduling model through genetic algorithms, taking space-time constraints and total resources as inputs, minimizing construction period delays or resource idle costs, outputting optimal solutions such as equipment scheduling schedules and material transportation paths, and dynamically correcting the model in conjunction with Internet of Things data to achieve dynamic balance of construction scheduling resources. Brief Description of the Drawings

[0020] The present invention will be further described below with reference to the accompanying drawings.

[0021] Figure 1 is a flowchart of the method for accurately monitoring and scheduling road construction progress based on intelligent perception according to an embodiment of the present invention; Figure 2 is a flowchart of the construction method of the road construction progress traceability chain according to an embodiment of the present invention; Figure 3 is an architecture diagram of the system module for accurately monitoring and scheduling road construction progress based on intelligent perception according to an embodiment of the present invention. Detailed Embodiments

[0022] In order to make the technical means, creative features, achieved purposes and effects of the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0023] In road construction, concealed structures (such as underground pipelines) and overlapping structures (such as multi-layer paving layers) are difficult to identify their construction characteristic parameters (such as burial depth, overlapping volume ratio) due to their concealed space positions and complex process logics by traditional management means, which are prone to problems such as difficult traceability of quality hazards, large errors in engineering quantity measurement, and lag in progress control; through technologies such as the lightweight engine of the three-dimensional information model (BIM), graph neural network, and three-dimensional point cloud registration, two types of structures are automatically identified and a construction constraint table including space-time and material parameters is constructed, realizing full-process data-driven from design analysis to resource scheduling, solving the technical bottlenecks of traditional methods in structural feature quantification, deviation traceability, and dynamic collaborative scheduling, and providing an intelligent solution for the refined management of road construction.

[0024] Embodiment 1

[0025] Please refer to Figure 1 shown, the method for accurately monitoring and scheduling road construction progress based on intelligent perception according to an embodiment of the present invention includes the following steps: Step 1. Obtain road construction drawings and three-dimensional information models, perform explicit analysis on the construction drawings and three-dimensional information models through intelligent perception algorithms, determine overlapping and concealed structure units in the road construction process, extract construction characteristic parameters of the overlapping and concealed structures, and construct a construction constraint table; Among them, the method for performing explicit analysis on the construction drawings and three-dimensional information models through intelligent perception algorithms is: Preferably, load the road construction drawings and the three-dimensional information model (BIM) through the BIM lightweight engine, adopt the IFC standard parsing technology to extract the spatial coordinates, geometric dimensions, material properties and construction sequence constraints of each component in the model, and construct a three-dimensional semantic network including the structural layer stacking relationship; Use the spatial Boolean operation algorithm to intelligently perceive the spatial overlapping area of the multi-layer paving structure (such as the subgrade cushion and the base course), and combine with the process flow chart in the construction organization design to identify the design position and burial depth of the concealed structural units such as pipeline burial and underground pipeline intersection; For the overlapping structure, by calculating the ratio of the spatial overlapping volume and the projected area between components, quantify the overlapping degree and mark the key monitoring nodes; For the concealed structure, extract the concealed feature parameters such as the covering soil thickness and wrapping material based on the design description, establish a multi-dimensional feature database including "structure type - spatial position - concealment level", and finally realize the automatic identification and annotation of the overlapping and concealed structural units through the graph neural network (GNN), providing construction feature parameters and monitoring targets for the subsequent intelligent perception system deployment; Among them, the construction feature parameters include: spatial feature parameters, time feature parameters, and material feature parameters of the overlapping and concealed structures; It should be noted that the spatial feature parameters include: coordinates, dimensions, burial depth, and overlapping volume ratio of the overlapping and concealed structures; The time feature parameters include: start and end times of the process, time window constraints of the construction workload, interval between adjacent processes, and process logic constraints; The material feature parameters include: component material, covering soil type, and compaction degree standard; Construct a construction constraint table including the construction feature parameters of the overlapping and concealed structural units; It can be understood that the construction constraint table is used to associate the design parameters with the construction process control indicators, providing a structured data benchmark for the intelligent scheduling system for process logic verification, resource allocation optimization and progress deviation analysis, which is conducive to realizing the quality control of the concealed and overlapping structures and the measurement of the engineering quantity during the construction process.

[0026] Step 2: Use the three-dimensional point cloud registration algorithm to collect the engineering quantities of different hierarchical structures of the road construction, and perform construction deviation analysis to obtain the progress deviation rate; Obtain the three-dimensional information models of all hierarchical structures of the road construction, and match the three-dimensional information models of the structures with the construction constraint table to obtain the matched road construction structures; Among them, the hierarchical structures include: surface structure, concealed structure, and overlapping structure; Based on the matched road construction structures, collect the construction engineering quantities of the road construction surface structure through the three-dimensional point cloud registration algorithm; Among them, the method for obtaining the construction quantities of the concealed structure and the overlapping structure is as follows: S1. For the concealed structure of road construction, determine the construction quantity of the concealed structure of road construction by combining the burial depth and position in the construction constraint table; Exemplarily, for the concealed project of pipeline burial, connect the designed burial depth (H d ), pipe diameter (D) in the construction constraint table with the buried position coordinates of multiple RFID tags collected in real time, calculate the actual length (L r ) of the laid pipeline through the connection distance, and obtain the density difference before and after the construction compaction of the concealed structure , and obtain the construction quantity V of pipeline burial through the formula: ; hid Among them, is the designed density of the road construction design drawing, and π is the pi; S2. For the construction quantity of the overlapping structure of road construction, obtain the road construction data and verify and analyze it in combination with the three-dimensional information model to calculate the construction quantity of the overlapping structure; Among them, the method of model verification and analysis is as follows: S201: Calibrate the three-dimensional information model of the overlapping structure with the measured coordinates of the overlapping structure to determine the construction boundary of the overlapping structure; Preferably, use the three-dimensional point cloud registration algorithm to unify the space-time reference of the overlapping structure coordinate data of the surface point cloud of the structural layer obtained by the laser scanner with the BIM model: Among them, the method of unifying the space-time reference is as follows: Select or automatically identify the same-name feature points (such as the internal and external corners of the structural layer, joint endpoints) in the model and the measured data to establish an initial matching pair; Then, optimize the transformation parameters (translation, rotation, scaling) based on the least squares method, convert the measured coordinates of the initial matching pair from the local coordinate system to the global coordinate system of the BIM model. After calibration, extract the construction boundary of the overlapping structure through the contour lines of the point cloud and the model; S202. Combine the construction boundary of the overlapping structure to perform a spatial intersection analysis on the three-dimensional information model to detect the geometric overlapping range of the adjacent structural layers of the overlapping structure; Preferably, use the spatial analysis module of the BIM software, use the calibrated construction boundary of the overlapping structure as the reference geometric entity, and perform a Boolean intersection operation with the three-dimensional model of the adjacent structural layer to obtain the geometric overlapping range; S203. Based on the geometric overlapping range, calculate the volume of the overlapping layer to obtain the construction quantity of the overlapping structure; Among them, the method for obtaining the construction progress deviation rate is as follows: Obtain the time windows of different hierarchical structures from the construction constraint table; ​Based on the construction quantities of the surface structure layer, hidden structure, and overlapping structure, as well as the corresponding time windows, obtain the time windows for the construction quantities of the corresponding hierarchical structures from the construction constraint table, and calculate the deviation ratio to obtain the progress deviation ratio of the construction progress. The technical solution of this embodiment is as follows: Obtain the road construction drawings and the 3D information model, perform explicit analysis on the construction drawings and the 3D information model through intelligent perception algorithms to determine the overlapping and hidden structure units in the road construction process, extract the construction characteristic parameters of the overlapping and hidden structures, and construct a construction constraint table; Use the 3D point cloud registration algorithm to collect the construction quantities of different hierarchical structures of the road construction, and perform construction deviation analysis to obtain the progress deviation rate; Based on the time window constraints of the construction constraint table, calculate the progress deviation rates of the surface layer, hidden layer, and overlapping layer, which can real-time feedback the difference between the construction progress and the plan, and provide data support for dynamic adjustment.

[0027] Embodiment 2 As Figure 1 shown, the method for precise monitoring and scheduling of road construction progress based on intelligent perception further includes the following steps: Step 3: Obtain the progress deviation ratio of the overlapping structure sub-units, and construct a road construction progress traceability chain. Through deviation conduction analysis of the overlapping structure of the road construction, extract the progress traceability sub-chain, and then combine the spatial coordinates and process logic of the 3D information model to analyze the conduction relationship of the progress traceability sub-chain through the association rule algorithm, and construct a progress traceability network. As Figure 2 shown, the construction method of the road construction progress traceability chain is as follows: A1: Obtain the sub-units of each overlapping structure of the road construction, and establish a unique identification system; It should be explained that each overlapping structure of the road construction contains multiple sub-units; Assign a global construction identifier to each sub-unit of the overlapping structure to establish a unique identification system; A2: Determine the traceability chain of the road construction according to the construction sequence of each sub-unit of the overlapping structure; A3: Obtain the progress deviation ratio of each sub-unit of the overlapping structure, and perform coupling processing with the traceability chain of the road construction to construct a road construction progress traceability chain; Exemplarily, the base course is divided into sub-units "JC-01" (section K0+000 - K0+500) and "JC-02" (section K0+500 - K1+000) according to the construction paragraphs, and the surface course is divided into "MC-01" (corresponding to the base course JC-01 section) and "MC-02" (corresponding to the base course JC-02 section). A globally unique identifier such as "JC-01-20250520", "MC-01-20250521", etc. is assigned to each sub-unit to establish an identification system; the traceability chain order is determined according to the construction sequence "JC-01 → JC-02 → MC-01 → MC-02"; if the progress deviation ratio of JC-01 is -15% (lag), JC-02 is -10%, MC-01 is -8%, and MC-02 is -5%, the deviation ratio of each sub-unit is coupled with its order in the traceability chain to form a progress traceability chain including "JC-01 (-15%) → JC-02 (-10%) → MC-01 (-8%) → MC-02 (-5%)", and the progress traceability chain reflects the conduction path of the deviation along the construction sequence. Among them, the method for analyzing the deviation conduction of the overlapping structure of road construction and extracting the progress traceability sub-chain is as follows: Obtain the sub-units of the overlapping structure corresponding to the negative progress deviation rate from the road construction progress traceability chain to get the progress lagging units. Based on the traceability chain of road construction, obtain the progress deviation rate of the adjacent sub-units of the progress lagging unit downward, and calculate the deviation ratio of the progress deviation rate of the progress lagging unit to the progress deviation rate of the adjacent sub-units to obtain the deviation conduction rate. Extract the progress traceability sub-chains of multiple sub-units of the progress traceability chain based on the deviation conduction rate, and obtain the progress traceability sub-chains of all overlapping structures of road construction. It can be understood that extracting the progress traceability sub-chain based on the deviation conduction rate takes the progress lagging unit as the core and traverses the process logic network through the graph theory algorithm: first, screen out the sub-units with direct influence according to the value of the deviation conduction rate (such as β = 1 indicating strong conduction), use the unique identifier of the sub-unit to associate its construction timestamp, spatial coordinates and deviation data, construct a directed acyclic graph according to the process sequence, and extract a single influence path as the progress traceability sub-chain through depth-first search. For the progress traceability sub-chains of all overlapping structures, it is necessary to first identify the overlapping structure type (such as base course - surface course overlap) through the three-dimensional information model and the construction constraint table, then use the structure ID as an index to batch-screen the sub-units belonging to this type, and aggregate them according to the time window constraint and conduction relationship to generate a hierarchical progress traceability sub-chain set to realize the visualization of the traceability path from a single deviation to the global influence. Among them, the method for analyzing the conduction relationship of the progress traceability sub-chain through the association rule algorithm is as follows: Perform correlation analysis on the progress trace sub-chains of the entire structure, and connect the progress trace sub-chains with a branch structure where there is a correlation relationship to form a progress trace network; Those skilled in the art can understand that a sub-chain spatial index is constructed based on the spatial coordinates of the 3D information model (such as mileage stake number, structural layer elevation), and the physically associated sub-chain nodes are identified through geometric overlap detection (such as intersection, inclusion relationship); At the same time, utilize the process logic of road construction to extract the time conduction correlation between sub-chains (such as multiple sub-chains sharing the same immediate previous process). Abstract the sub-chains into directed edges (with deviation conduction rate attributes) and sub-units into nodes (with ID, type, space-time coordinate attributes) through the Neo4j algorithm, and adopt the association rule algorithm of Apriori to analyze the conduction mode across progress trace sub-chains (such as the association rule of base course lag → synchronous delay of multiple surface courses); Use a tree-like hybrid graph as the branch structure to dynamically connect the progress trace sub-chains with direct and indirect associations, form a multi-level progress trace network including "deviation source - conduction path - influence range", and dynamically display the chain reaction and its impact on road construction through a visualization engine; It should be explained that the functions of establishing the progress trace network are as follows: Function 1. Locate the deviation source: Through the directed connection of the progress trace sub-chains (such as the sub-unit ID associated with the time stamp and deviation data), lock the progress-lagging unit and its downstream sub-units directly or indirectly affected, and shorten the problem location time; Function 2. Visualize the conduction path: Dynamically display "deviation source - conduction path - influence range" with a tree-like hybrid graph, intuitively present the chain effect caused by spatial overlap (such as overlapping adjacent working faces) and time logic (such as delay of the immediate previous process), and assist managers in predicting the risk diffusion trend; Function 3. Support cross-chain collaborative analysis: Mine the conduction mode across sub-chains (such as the association between multiple base course lags and surface course synchronous delay) through the association rule algorithm, provide "deviation conduction priority" data for the resource scheduling model, realize the management upgrade from passive response to active prevention, and improve the intelligence and refinement level of construction progress control.

[0028] Step 4. Extract the cross-chain branch sub-chains of the progress trace network, conduct resource scheduling analysis on the cross-chain branch sub-chains, identify the resource competition points of the cross-chain branch sub-chains, conduct collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chains; Among them, the method for extracting the cross-chain branch sub-chains of the progress trace network is: By constructing the graph structure of the progress trace network, represent the conduction relationship with the directed edges of the sub-units of the overlapping structure; Among them, the conduction relationships include: the conduction order of different subunits in the time dimension, the conduction relationship of subunit spatial overlap, the deviation conduction rate between different subunits, and the process logic constraints between construction constraint tables; Based on the sub-chain screening conditions, a sub-chain screening algorithm is established to extract cross-chain branch sub-chains from the graph structure of the progress traceability network; Among them, the sub-chain screening conditions include: B1. There is a resource intersection. Different progress traceability sub-chains have a resource intersection, that is, different road construction equipment and materials are applied for use by multiple progress traceability sub-chains; Exemplarily, road pavers are jointly used by multiple progress traceability sub-chains; B2. By calculating the coincidence degree of the working surfaces of adjacent progress traceability sub-chains with a branch structure, the spatial proximity ratio is obtained; Preferably, through the formula: The spatial proximity ratio S is obtained ratio ; Among them, V a , V b respectively represent the volumes of two adjacent progress traceability sub-chains a and b, represents the overlapping volume of the working surfaces of adjacent progress traceability sub-chains; B3. Calculate the overlapping degree of the time window constraints of adjacent progress traceability sub-chains to obtain the time window coincidence ratio; Preferably, obtain the time windows of adjacent progress traceability sub-chains and calculate the overlapping proportion of the time windows to obtain the time window coincidence ratio; Exemplarily, the time window of progress traceability sub-chain a is [T a_start , T a_end , and the time window of progress traceability sub-chain b is [T b_start , T b_end ; Through the formula: The overlapping duration T over is obtained; Through the formula: The time window coincidence ratio T ratio is obtained; Those skilled in the art can understand that the sub-chain screening algorithm realizes the extraction of cross-chain branch sub-chains through graph traversal, multi-dimensional condition filtering, and clustering analysis: by traversing the graph structure of the progress traceability network, for each sub-chain node, the adjacent nodes with resource intersections (B1) are matched through a hash table; The spatial proximity ratio (B2) is calculated by using the BIM spatial analysis interface to calculate the ratio of the overlapping volume to the total volume of the adjacent node working surfaces, and at the same time, the time window field is parsed to calculate the ratio of the overlapping duration to obtain the time window coincidence ratio (B3); by setting different thresholds (such as resource intersection ≥ 1 category, spatial proximity ratio > 10%, time window coincidence ratio > 20%), node pairs that meet the conditions are filtered, and finally, the label propagation algorithm (LPA) is used to cluster the filtered nodes to generate a cross-chain branch subgraph containing resource, space, and time associations, realizing the automatic extraction of cross-chain branch sub-chains; It should be noted that the role of identifying cross-chain branch sub-chains is to locate complex conflict scenarios in road construction caused by resource, space, and time associations. By screening sub-chain combinations with resource intersections (such as sharing pavers), overlapping spatial working surfaces (such as overlapping adjacent construction sections), and overlapping time windows, the spatio-temporal conflict intensity of resource competition points (such as equipment reuse rate, time window coincidence ratio) is quantified, providing target objects for subsequent resource scheduling analysis, enabling the system to specifically identify urgent demand points that need to be coordinated first, and then optimizing the spatio-temporal allocation of equipment, materials, and manpower through the resource allocation model to avoid resource conflicts and idleness across processes and regions, improving the utilization efficiency of construction resources and reducing the risk of project duration delays; Among them, the method of conducting resource scheduling analysis on cross-chain branch sub-chains and identifying resource competition points of cross-chain branch sub-chains is as follows: Obtain the overlapping duration T of the cross-chain branch sub-chain and the adjacent cross-chain branch sub-chain over the equipment reuse rate within it, as well as the time window coincidence ratio, and establish a resource competition analysis model to identify the resource competition points of the cross-chain branch sub-chain; It should be noted that the equipment reuse rate is determined by calculating the ratio of the total time that road construction equipment is occupied by each cross-chain branch sub-chain within the overlapping duration to the overlapping duration, reflecting the degree of repeated use of the equipment during the overlapping time; Among them, the method of establishing the resource competition analysis model is as follows: Obtain the time window overlapping duration T of the cross-chain branch sub-chain and its adjacent sub-chain over , the time window coincidence ratio and the equipment reuse rate: Establish a two-dimensional resource competition analysis model with the time window coincidence ratio as the horizontal axis and the equipment reuse rate as the vertical axis, set the threshold intervals for the time window and the equipment reuse rate (such as time window coincidence ratio > 50% and equipment reuse rate > 60%), and the sub-chain combinations falling within the high threshold interval are determined as resource competition points, indicating that there are significant conflicts in time and equipment resources and need to be coordinated and scheduled first; Among them, the method of conducting collaborative urgency analysis on resource competition points and determining the urgent demand points of cross-chain branch sub-chains is as follows: Effectively screen and process the equipment reuse rate of the resource competition point within the overlapping duration to obtain the effective reuse rate; It is understandable that when effectively screening and processing the device reuse rate at the resource competition point within the overlapping duration, it is necessary to, based on the device status data (such as positioning trajectories, start and stop timestamps) collected in real time by the Internet of Things, eliminate the non-working periods of the devices (such as fault shutdowns, maintenance breaks) and invalid occupancy durations, and only retain the time when the devices are in the operating state and are actually called by the cross-chain branch sub-chains. The "effective reuse rate = (total effective operating time of the device within the overlapping duration / overlapping duration)" is used for calculation to obtain the true device reuse efficiency index after eliminating the virtual occupancy duration, providing a reliable basis for identifying the intensity of resource competition; Normalize the time window coincidence ratio and the effective reuse rate at the resource competition point respectively, and multiply the reciprocal of the normalized time window coincidence ratio and the effective reuse rate to obtain the collaborative urgency index; Based on the collaborative urgency index, screen all the competing resource points to obtain the urgent demand points; It is understandable that the collaborative urgency index is compared with the preset collaborative urgency range value, and the competing resource points that meet the preset collaborative urgency range value are screened as the urgent demand points; It should be noted that the physical meaning of the collaborative urgency index lies in quantifying the comprehensive conflict intensity of the cross-chain branch sub-chains in the time and resource dimensions. The higher the value of the collaborative urgency index, the higher the urgency of resource competition and the scheduling priority; Time window coincidence ratio: Reflects the overlapping degree of the construction time between sub-chains. The larger the value, the more significant the time conflict (such as multiple construction segments synchronously occupying the time window of the same device); The reciprocal of the effective reuse rate: Is inversely proportional to the actual utilization efficiency of the device resources. The larger the value of the reciprocal of the effective reuse rate, the higher the proportion of idle or inefficient occupancy of the device within the overlapping duration (such as the device frequently starting and stopping or waiting due to scheduling conflicts); The collaborative urgency index integrates spatio-temporal data through standardizing the dimension, provides an intuitive priority ranking basis for the resource scheduling model, is conducive to locating the key bottleneck points of "severe time conflict and high device idling rate", and optimizing resource allocation.

[0029] Step 5: Obtain the construction scheduling resources for the urgent demand points, establish a resource allocation group, construct a resource scheduling model and input the resource allocation group to achieve resource allocation for the overlapping structure of road construction; Among them, the method of obtaining the construction scheduling resources for the urgent demand points and establishing a resource allocation group is as follows: The construction scheduling resources include: device resources, material resources, construction personnel; Construct a resource allocation group including construction scheduling resources and the overlapping duration; Among them, the method of constructing a resource scheduling model and inputting the resource allocation group to achieve resource allocation for the overlapping structure of road construction is as follows: Preferably, when constructing a resource scheduling model and inputting a resource allocation group, the core constraint conditions such as spatio-temporal constraints, total resource volume, and process logic should be taken into account. The genetic algorithm is adopted, and data such as the equipment list (such as paver number, available time period), material requirements (such as gravel volume, supply time), and labor teams (such as skill types, work shifts) of the resource allocation group are used as inputs. The optimal solution that minimizes the construction period delay or resource idle cost is obtained through model solving, and a scheduling plan including an equipment scheduling time table, a material transportation route, and a team operation partition is output. At the same time, the three-dimensional information model and Internet of Things real-time data (such as equipment positioning trajectories, material inventory) are linked to dynamically correct the model parameters, realizing the dynamic allocation of resources for the overlapping structure of road construction; The technical solution of this embodiment is as follows: Obtain the progress deviation ratio of the overlapping structure sub-units, and construct a road construction progress traceability chain. Through deviation conduction analysis of the overlapping structure of road construction, extract the progress traceability sub-chain, and then combine the spatial coordinates and process logic of the three-dimensional information model. Analyze the conduction relationship of the progress traceability sub-chain through the association rule algorithm to construct a progress traceability network; Extract the cross-chain branch sub-chain of the progress traceability network, conduct resource scheduling analysis on the cross-chain branch sub-chain, identify the resource competition points of the cross-chain branch sub-chain, conduct collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chain; Obtain the construction scheduling resources of the urgent demand points, establish a resource allocation group, construct a resource scheduling model and input the resource allocation group to realize the resource allocation of the overlapping structure of road construction.

[0030] Embodiment 3 As Figure 3 shown, the accurate monitoring and scheduling system for road construction progress based on intelligent perception includes the following modules: Constraint construction module: Used to obtain road construction drawings and three-dimensional information models, conduct explicit analysis on the construction drawings and three-dimensional information models through intelligent perception algorithms, determine the overlapping and hidden structure units in the road construction process, extract the construction characteristic parameters of the overlapping and hidden structures, and construct a construction constraint table; Deviation acquisition module: Use the three-dimensional point cloud registration algorithm to collect the engineering quantities of different hierarchical structures of road construction, and conduct construction deviation analysis to obtain the progress deviation rate; Progress traceability module: Used to obtain the progress deviation ratio of the overlapping structure sub-units, and construct a road construction progress traceability chain. Through deviation conduction analysis of the overlapping structure of road construction, extract the progress traceability sub-chain, and then combine the spatial coordinates and process logic of the three-dimensional information model. Analyze the conduction relationship of the progress traceability sub-chain through the association rule algorithm to construct a progress traceability network; Scheduling analysis module: Used to extract the cross-chain branch sub-chain of the progress traceability network, conduct resource scheduling analysis on the cross-chain branch sub-chain, identify the resource competition points of the cross-chain branch sub-chain, conduct collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chain; Resource allocation module: Obtain the construction scheduling resources of urgent demand points, establish a resource allocation group, construct a resource scheduling model and input the resource allocation group to achieve resource allocation for the overlapping structure of road construction.

[0031] The above shows and describes 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 by the above embodiments. What is described in the above embodiments and the specification only illustrates the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended technical solutions and their equivalents.

Claims

1. A method for precise monitoring and scheduling of road construction progress based on intelligent perception, characterized in that: It includes the following steps: Using a 3D point cloud registration algorithm to collect the quantities of work for different hierarchical structures of road construction, and conducting construction deviation analysis to obtain the progress deviation rate; Obtaining the progress deviation ratio of overlapping structural subunits, and constructing a road construction progress traceability chain. Through deviation conduction analysis of the overlapping structures in road construction, extracting the progress traceability sub-chain, and then combining the spatial coordinates and process logic of the 3D information model, analyzing the conduction relationship of the progress traceability sub-chain through an association rule algorithm to construct a progress traceability network; Extracting the cross-chain branch sub-chain of the progress traceability network, conducting resource scheduling analysis on the cross-chain branch sub-chain, identifying the resource competition points of the cross-chain branch sub-chain, conducting collaborative urgency analysis on the resource competition points, and determining the urgent demand points of the cross-chain branch sub-chain; Obtaining the construction scheduling resources for the urgent demand points, establishing a resource allocation group, constructing a resource scheduling model and inputting the resource allocation group to achieve resource allocation for the overlapping structures in road construction.

2. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 1, characterized in that: Obtaining the road construction drawings and the 3D information model, conducting explicit analysis on the construction drawings and the 3D information model through an intelligent perception algorithm, determining the overlapping and hidden structural units in the road construction process, extracting the construction characteristic parameters of the overlapping and hidden structures, and constructing a construction constraint table.

3. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 1, wherein: The way to conduct the said construction deviation analysis is: Obtaining the 3D information models of all hierarchical structures of road construction, and matching and corresponding the 3D information models of the structures with the construction constraint table to obtain the corresponding road construction structures; Obtaining the construction quantities of work at different levels and the corresponding time windows, obtaining the time window of the current construction quantity of work from the construction constraint table, and conducting deviation ratio calculation to obtain the progress deviation ratio of the construction progress; Among them, the hierarchical structures include: surface structure, hidden structure, overlapping structure.

4. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 3, wherein: The way to obtain the construction quantities of work at the said different levels is: Collecting the construction quantities of work of the surface structure of road construction through a 3D point cloud registration algorithm; For the hidden structure of road construction, determining the construction quantities of work of the hidden structure of road construction in combination with the burial depth and position in the construction constraint table; For the construction quantities of work of the overlapping structure of road construction, obtaining road construction data and verifying and analyzing in combination with the 3D information model, and calculating the construction quantities of work of the overlapping structure.

5. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 1, characterized in that: The way to construct the said progress traceability network is: Obtaining the subunits of the overlapping structure corresponding to a negative progress deviation rate from the road construction progress traceability chain to obtain the progress lagging units; Based on the traceability chain of road construction, obtaining the progress deviation rate of the adjacent subunits of the progress lagging units downward, calculating the deviation ratio of the progress deviation rate of the progress lagging units to the progress deviation rate of the adjacent subunits to obtain the deviation conduction rate; Extracting the progress traceability sub-chains of multiple subunits of the progress traceability chain based on the deviation conduction rate, and obtaining the progress traceability sub-chains of all overlapping structures in road construction; Conducting correlation analysis on the progress traceability sub-chains of all structures, and connecting the progress traceability sub-chains through branch structures where there are correlation relationships to form a progress traceability network.

6. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 5, characterized in that: The way to obtain the said construction progress traceability chain is: Obtaining the subunits of each overlapping structure in road construction and establishing a unique identification system; Determine the traceability chain of road construction according to the construction sequence of each subunit of the overlapping structure; Obtain the progress deviation ratio of each subunit of the overlapping structure, and perform coupling processing with the traceability chain of road construction to construct the road construction progress traceability chain.

7. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 1, wherein: The way to identify the resource competition points of the cross-chain branch sub-chain is: By constructing the graph structure of the progress traceability network, represent the directed edges of the subunits of the overlapping structure as conduction relationships; Establish a sub-chain screening algorithm based on the sub-chain screening conditions to extract the cross-chain branch sub-chain from the graph structure of the progress traceability network; Obtain the equipment reuse rate and the time window coincidence ratio within the overlapping duration of the cross-chain branch sub-chain and the adjacent cross-chain branch sub-chain, establish a resource competition analysis model, and identify the resource competition points of the cross-chain branch sub-chain.

8. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 7, wherein: The way to establish the resource competition analysis model is: The resource competition analysis model is established by: obtaining the time window overlapping duration, the time window coincidence ratio, and the equipment reuse rate of the cross-chain branch sub-chain and its adjacent sub-chain; Establish a two-dimensional resource competition analysis model with the time window coincidence ratio as the horizontal axis and the equipment reuse rate as the vertical axis.

9. The method for precise monitoring and scheduling of road construction progress based on intelligent perception according to claim 1, wherein: The way to determine the urgent demand points of the cross-chain branch sub-chain is: Effectively screen the equipment reuse rate of the resource competition points within the overlapping duration to obtain the effective reuse rate; Obtain the resource competition points, perform normalization processing on the time window coincidence ratio and the effective reuse rate respectively, and perform product processing on the reciprocal of the normalized time window coincidence ratio and the effective reuse rate to obtain the collaborative urgency index; Based on the collaborative urgency index, screen all the competing resource points to obtain the urgent demand points.

10. A precise monitoring and scheduling system for road construction progress based on intelligent perception, which is used to implement the precise monitoring and scheduling method for road construction progress described in any one of claims 1-9, and is characterized in that: It includes the following modules: Constraint construction module: used to obtain the road construction drawings and the three-dimensional information model, perform explicit analysis on the construction drawings and the three-dimensional information model through intelligent perception algorithms, determine the overlapping and concealed structural units in the road construction process, extract the construction characteristic parameters of the overlapping and concealed structures, and construct a construction constraint table; Deviation acquisition module: use the three-dimensional point cloud registration algorithm to collect the engineering quantities of different hierarchical structures of road construction, and perform construction deviation analysis to obtain the progress deviation rate; Progress traceability module: used to obtain the progress deviation ratio of the overlapping structure subunits, construct the road construction progress traceability chain, perform deviation conduction analysis on the road construction overlapping structure, extract the progress traceability sub-chain, and then combine the spatial coordinates and process logic of the three-dimensional information model to analyze the conduction relationship of the progress traceability sub-chain through the association rule algorithm to construct the progress traceability network; Scheduling analysis module: used to extract the cross-chain branch sub-chain of the progress traceability network, perform resource scheduling analysis on the cross-chain branch sub-chain, identify the resource competition points of the cross-chain branch sub-chain, perform collaborative urgency analysis on the resource competition points, and determine the urgent demand points of the cross-chain branch sub-chain; Resource allocation module: obtain the construction scheduling resources of the urgent demand points, establish a resource allocation group, construct a resource scheduling model and input the resource allocation group to realize the resource allocation of the road construction overlapping structure.

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