Intelligent monitoring and scheduling method and system for highway and municipal engineering construction process

Abstract

The invention relates to the technical field of construction vehicle control, and particularly discloses a highway and municipal engineering construction process intelligent monitoring and scheduling method and system.The method can accurately decide a scheduling strategy according to a comparison result of a material consumption index and a reference interval by monitoring material use parameters and judging whether to intelligently optimize vehicle scheduling; blind scheduling is avoided, the resource utilization efficiency is improved, the material shortage or overstock risk is reduced, when intelligent optimization vehicle scheduling is corrected, predicted transportation duration is matched in combination with a transportation path congestion index, a scheduling instruction is preposed or subjected to delay correction, it is ensured that vehicles start at the optimal time, transportation delay is reduced, and timely material supply is ensured; the construction progress is maintained to be stable, whether a scheduling early warning link is carried out or not is judged, the vehicle operation state and the operation efficiency factor are integrated, low-efficiency vehicles are accurately recognized and early warned, maintenance can be arranged in advance, vehicle faults are prevented from affecting construction, transportation continuity is guaranteed, and smooth engineering promotion is powerfully guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of construction vehicle control, and in particular to an intelligent monitoring and scheduling method and system for highway and municipal engineering construction processes. Background Art

[0002] With the rapid development of information technology, emerging technologies such as artificial intelligence and cloud computing have gradually penetrated into various fields, providing new technical approaches and solutions for intelligent monitoring and scheduling of vehicles during the construction process. By deploying various sensors, cameras and other intelligent sensing equipment at the construction site, multi-dimensional data such as construction environment, equipment status, and personnel location can be collected in real time, so as to accurately grasp the construction dynamics.

[0003] For example, the invention patent with publication number CN115909730A discloses an intelligent traffic control system for tunnel construction period based on digital twin, including a data acquisition unit for collecting information on vehicle control, an early warning analysis unit for integrating and processing various information obtained by the data acquisition unit, and a display scheduling unit for visually presenting the calculation results of the early warning analysis unit. The invention uses a multi-source data acquisition unit to collect UWB-based vehicle positioning data, construction progress data of each working face of the tunnel, signal light position data, and real-time camera monitoring data. According to vehicle traffic rules and traffic management plans, the vehicle running speed, regional distribution, and meeting behavior are analyzed to obtain recommended vehicle scheduling plans; scheduling instructions are issued through the large screen of the monitoring center, signal lights in the tunnel, and on-board information boards to achieve intelligent control of tunnel traffic.

[0004] For example, the invention patent with publication number CN117437768A provides an intelligent dispatching system and method for tunnel construction vehicles. The system includes a vehicle information module, an intelligent analysis module, a display module, a signal management module and a video monitoring module; the vehicle information module enters basic information of the vehicle and the driver and obtains the vehicle's location data; the intelligent analysis module analyzes the real-time traffic congestion status in different areas during tunnel construction based on the built-in algorithm; the display module is used to grasp the traffic status of different sections in the tunnel in real time; the signal management module adjusts the traffic signals in the tunnel according to the congestion level; the video monitoring module calls the surveillance camera in real time to conduct congestion analysis, formulate dispatch plans, and supervise and adjust the dispatch process.

[0005] However, in the process of implementing the embodiments of the present application, the present application found that the above-mentioned technology has at least the following technical problems: the current vehicle scheduling scheme has defects and does not fully consider the actual performance parameters of the vehicle. In the scheduling decision-making process, there is a lack of accurate analysis of the actual operating capabilities of the vehicle, resulting in a mismatch between the scheduling arrangements and the actual performance of the vehicle, and the inability to achieve optimal allocation and efficient utilization of transportation resources, which in turn affects the execution efficiency and safety of transportation tasks. Summary of the Invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for intelligent monitoring and scheduling of highway and municipal engineering construction processes, which can effectively solve the problems involved in the above-mentioned background technology.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: The first aspect of the present invention provides an intelligent monitoring and scheduling method for the construction process of highways and municipal engineering projects, including: step one, marking highways and municipal engineering projects as target projects, monitoring and analyzing the material usage parameters of the target project construction process, so as to determine whether to perform intelligent optimization of vehicle scheduling; step two, vehicles transport materials according to established transportation routes, collect and analyze the characteristic parameters of the transportation routes to which the vehicles belong, and intelligently correct the vehicle scheduling process; step three, obtaining and analyzing the operating status parameters of the vehicle, and at the same time correcting the operating status parameters of the vehicle through the material usage parameters of the target project construction process and the characteristic parameters of the transportation routes to which the vehicles belong, so as to determine whether to perform scheduling warnings for the vehicles.

[0008] As a further method, vehicle scheduling is intelligently optimized, and the specific optimization process is as follows: if the material consumption index of the target project is greater than the maximum value of the material consumption reference interval, the number of vehicles in the supplementary scheduling status and the total supplementary scheduling material quality are obtained and matched from the scheduling database based on the material consumption index growth rate of the target project, and a first scheduling instruction is generated according to the number of vehicles in the supplementary scheduling status and the total supplementary scheduling material quality; if the material consumption index of the target project is less than the minimum value of the material consumption reference interval, a delay prompt is given for the expected departure time point, and a second scheduling instruction is generated according to the delay prompt.

[0009] As a further method, the vehicle scheduling process is intelligently corrected. The specific correction process is: analyzing the characteristic parameters of the transport path to which the vehicle belongs, obtaining the congestion index of the transport path, and matching the estimated transport time of the transport path from the scheduling database according to the congestion index of the transport path; correcting the first scheduling instruction and the second scheduling instruction according to the estimated transport time of the transport path, the specific correction process is: obtaining the basic transport time, and performing difference processing on it with the estimated transport time of the transport path, and marking the processing result as the transport time deviation value; obtaining the estimated departure time point of the vehicle in the supplementary scheduling state, and performing pre-correction processing on the estimated departure time point of the vehicle in the supplementary scheduling state according to the transport time deviation value, thereby correcting the first scheduling instruction; obtaining the estimated departure time point of the vehicle in the waiting state, and performing correction processing on the estimated departure time point of the vehicle in the waiting state according to the transport time deviation value, thereby correcting the second scheduling instruction.

[0010] As a further method, the number of vehicles in the supplementary scheduling state and the total supplementary scheduling material quality are allocated in a specific process: the operating efficiency index of each vehicle in the to-be-scheduled state is obtained, and they are sorted in descending order according to the operating efficiency index; based on the number of vehicles in the supplementary scheduling state, the vehicles in the to-be-scheduled state with the operating efficiency index ranked first are marked in turn as vehicles in the supplementary scheduling state until the number of marked vehicles is equal to the number of vehicles in the supplementary scheduling state; at the same time, the operating efficiency factor of each vehicle in the supplementary scheduling state is obtained, and the difference between the factor and the operating efficiency threshold is processed; the processing result is compared with the operating efficiency threshold, and finally the operating efficiency margin of each vehicle in the supplementary scheduling state is obtained, the basic scheduling material quality is obtained, and the actual scheduling material quality of each vehicle in the supplementary scheduling state is obtained according to the operating efficiency margin of each vehicle in the supplementary scheduling state, and then the total supplementary scheduling material quality is allocated, starting from the supplementary scheduling state vehicle with the operating efficiency index ranked first, until the allocation of the total supplementary scheduling material quality is completed.

[0011] The second aspect of the present invention provides an intelligent monitoring and scheduling system for the construction process of highways and municipal engineering projects, including: an optimization scheduling module, which is used to mark highways and municipal engineering projects as target projects, monitor and analyze the material usage parameters of the target project construction process, and thus determine whether to perform intelligent optimization of vehicle scheduling; an intelligent correction module, which is used to transport materials according to the established transportation route, collect and analyze the characteristic parameters of the transportation route to which the vehicle belongs, and perform intelligent correction on the vehicle scheduling process; a scheduling warning module, which is used to obtain and analyze the operating status parameters of the vehicle, and at the same time correct the operating status parameters of the vehicle through the material usage parameters of the target project construction process and the characteristic parameters of the transportation route to which the vehicle belongs, so as to determine whether to perform scheduling warning for the vehicle.

[0012] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention provides an intelligent monitoring and scheduling method and system for the construction process of highways and municipal engineering projects. By monitoring material usage parameters and determining whether to intelligently optimize vehicle scheduling, the present invention can accurately decide on scheduling strategies based on the comparison results of the material consumption index and the reference interval, avoid blind scheduling, improve resource utilization efficiency, and reduce the risk of material shortages or backlogs. When correcting the intelligently optimized vehicle scheduling, the present invention combines the transportation path congestion index to match the expected transportation time, and corrects the scheduling instructions in advance or delay to ensure that vehicles depart at the optimal time, reduce transportation delays, ensure timely supply of materials, maintain stable construction progress, determine whether to perform scheduling warning links, comprehensively integrate vehicle operating status and operating efficiency factors, accurately identify low-efficiency vehicles and issue warnings, arrange maintenance in advance, avoid vehicle failures affecting construction, ensure transportation continuity, and effectively ensure the smooth progress of the project.

[0013] (2) The present invention sorts the high-efficiency vehicles according to the operation efficiency index and prioritizes them as supplementary dispatch vehicles, which can give full play to the transportation capacity of high-efficiency vehicles, improve the overall transportation efficiency, reduce transportation costs and time losses, and allocate the actual dispatch material quality based on the operation efficiency margin, so that high-efficiency vehicles can take on more transportation tasks, optimize resource allocation, avoid resource waste and uneven distribution, and such a scientific and reasonable allocation mechanism ensures the accurate delivery of the total supplementary dispatch material quality, effectively guarantees the timely supply of construction materials, and maintains a stable construction progress.

[0014] (3) The present invention can accurately reflect the real-time transportation performance of vehicles by judging the vehicle operation status and updating the efficiency factor after the operation is completed, providing a reliable basis for subsequent scheduling decisions. By comparing the efficiency factor of the vehicle to be scheduled with the threshold, it can scientifically determine whether to issue an early warning, identify low-efficiency vehicles in advance, and effectively prevent transportation risks. The low-efficiency vehicles to be scheduled are marked as waiting for maintenance and issued early warnings, and maintenance can be arranged in time to avoid the impact of faults on construction. The idle and operating status classification is clearly defined, making vehicle management clear and organized, which helps to achieve reasonable allocation of vehicle resources, ensure efficient and stable transportation of construction materials, and promote the smooth progress of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The present invention is further described with reference to the accompanying drawings. However, the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative effort.

[0016] Figure 1 Schematic diagram of the method steps of the present invention.

[0017] Figure 2 This is a schematic diagram of system module connections of the present invention.

[0018] Figure 3 Detailed flow chart of the present invention.

[0019] Figure 4 It is a detailed schematic diagram of material distribution of the present invention. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0021] Reference Figure 1As shown, the first aspect of the present invention provides an intelligent monitoring and scheduling method for the construction process of highways and municipal engineering projects, including: step 1, marking highways and municipal engineering projects as target projects, monitoring and analyzing material usage parameters during the construction process of the target projects, and thus determining whether to perform intelligent optimization of vehicle scheduling.

[0022] Specifically, to determine whether to perform intelligent optimization of vehicle scheduling, the specific determination process is: analyze the material usage parameters of the target project construction process, obtain the material consumption index of the target project, and compare it with the material consumption reference range; if the material consumption index of the target project belongs to the material consumption reference range, then intelligent optimization of vehicle scheduling will not be performed; if the material consumption index of the target project does not belong to the material consumption reference range, then intelligent optimization of vehicle scheduling will be performed; the above-mentioned material consumption reference range is an ideal material consumption range established by technical personnel through fitting historical project data and construction specification requirements, and is stored in the scheduling database as a benchmark reference. When the material consumption index is within the reference range, it is determined that the current material usage efficiency meets the expected standards of the technical personnel, and the existing vehicle scheduling plan is maintained; if the material consumption index exceeds the range, the intelligent vehicle scheduling optimization mechanism is activated.

[0023] Specifically, the material consumption index of the target project, the specific analysis process is: the material usage parameters of the target project construction process include the material footprint reduction rate, the construction area growth rate and the material usage rate; it should be explained that the material in this embodiment refers to concrete, and the material footprint reduction rate represents the proportion of the concrete stacking area reduced compared to the initial stacking area. The material footprint reduction rate can be obtained by using the formula (initial footprint - new footprint) ÷ initial footprint × 100%. The initial footprint and the new footprint can be obtained by analyzing the camera photos. For example, cameras are installed around the concrete stacking area to ensure that the stacking area can be fully covered, and clear images of the concrete stacking area are taken regularly (such as at a specific time every day). With the help of image processing software (such as Matrix Lab software, etc.), the collected images are pre-processed, including noise removal (using Gaussian filtering and other methods) to obtain the image quality. and enhance contrast (such as histogram equalization) to improve image quality. Then, an edge detection algorithm (such as the Sobel algorithm) is used to accurately identify the boundary of the concrete stacking area. According to the conversion relationship between image pixels and actual distance (technicians need to calibrate on site in advance), the boundary identified in the image is converted into actual length, and the area occupied by the concrete stacking area is calculated. The above-mentioned growth rate of the area of ​​the constructed area represents the increase in the area of ​​the constructed area per unit time, which can be obtained through camera photography analysis. For example, high-definition wide-angle cameras are deployed at reasonable locations on the construction site to ensure full coverage and overlapping fields of view. The installation height and angle are adjusted in combination with the on-site terrain, obstacles, etc. to obtain clear and complete images. A scheduled task is set to enable the camera to automatically capture images at fixed intervals (such as every hour / day) and transmit them to the server for storage in real time. The image is first pre-processed to remove noise, enhance contrast, and correct distortion to improve quality. Then, a scale-invariant feature transformation is used to extract feature points of the concrete-constructed area and calculate the area, and the growth rate is calculated based on the time interval. The above-mentioned material utilization rate represents the ratio of the measured volume of the concrete pile to the initial volume of the concrete pile, specifically (initial volume of the concrete pile - measured volume of the concrete pile) / measured volume of the concrete pile. Both the initial volume of the concrete pile and the measured volume of the concrete pile can be captured by a camera, and a high-precision point cloud model is generated based on a hybrid algorithm of motion recovery structure and multi-view stereo vision. The concrete solid mesh model is generated through Poisson surface reconstruction to calculate the volume.

[0024] The influence of the deviation between the material footprint reduction rate and the reference material footprint reduction rate on the material consumption index, the deviation between the constructed area growth rate and the reference constructed area growth rate on the material consumption index, and the deviation between the material utilization rate and the reference material utilization rate on the material consumption index are quantified by measurement values. These influences are coupled to obtain the material consumption index of the target project. The material consumption index of the target project represents the material consumption of the target project, and its specific expression is: ; Where, is the material consumption index of the target project, is the reduction rate of material floor space, is the reference material floor space reduction rate preset in the scheduling database, is the growth rate of the constructed area, is the reference construction area growth rate preset in the scheduling database, is the material utilization rate, The reference material usage rate preset in the scheduling database, It is the material floor space reduction rate measurement value preset in the scheduling database. is the growth rate measurement value of the constructed area preset in the scheduling database. It is a material utilization rate measure preset in the scheduling database.

[0025] The above-mentioned reference growth rate of the constructed area represents the reference value of the growth rate of the constructed area; the above-mentioned reference reduction rate of the material floor area represents the reference value of the reduction rate of the material floor area; the above-mentioned reference material utilization rate represents the reference value of the material utilization rate.

[0026] What needs to be explained is that in the process of highway and municipal engineering construction, the reduction rate of material floor space, the growth rate of constructed area and the material utilization rate are closely intertwined, and together they shape the dynamic changes of the material consumption index. When the speed of material utilization accelerates, the area of ​​the constructed area will expand rapidly due to the efficient conversion of materials into engineering entities, and its area growth rate will increase significantly, reflecting the tight construction rhythm. At the same time, materials are consumed rapidly, and the storage area is rapidly reduced. The reduction rate of material floor space is greatly improved, and the material utilization rate rises simultaneously due to reduced waste and high input-output ratio. The three work together to push the material consumption index up rapidly. At this time, the dispatching system needs to respond quickly and replenish materials and vehicles in time. To ensure uninterrupted construction, on the contrary, when the material usage speed slows down, the construction progress is hindered, the growth of the constructed area stagnates or even slows down, the material floor area reduction rate decreases accordingly, materials accumulate in the storage area, the utilization rate decreases, and the material consumption index grows weakly or even falls. This may be due to factors such as construction plan adjustments, equipment failures or poor material supply connections. At this time, the scheduling system needs to re-evaluate the demand, reasonably reduce vehicle scheduling, and avoid idle resources and waste. It can be seen that the three parameters are linked to the material usage speed. By affecting the material consumption index, it provides an accurate decision-making basis for the intelligent monitoring and scheduling system, helping the project to achieve a dynamic balance between efficient material utilization and reasonable supply, and ensure the orderly progress of construction.

[0027] The above-mentioned material footprint reduction rate measurement value is used to quantify the influence of the unit value of the material footprint reduction rate on the material consumption index; the above-mentioned constructed area area growth rate measurement value is used to quantify the influence of the unit value of the constructed area growth rate on the material consumption index; the above-mentioned material utilization rate measurement value is used to quantify the influence of the unit value of the material utilization rate on the material consumption index. The scheduling database stores the correspondence between the material footprint reduction rate, the constructed area growth rate and the material utilization rate and their corresponding measurement values. For example, the material footprint reduction rate, the constructed area growth rate and the material utilization rate are input into the scheduling database, and the scheduling database can retrieve the material footprint reduction rate measurement value, the constructed area growth rate measurement value and the material utilization rate measurement value, and the value range is between 0 and 1.

[0028] Furthermore, vehicle scheduling is intelligently optimized, and the specific optimization process is as follows: if the material consumption index of the target project is greater than the maximum value of the material consumption reference interval, then the material consumption index growth rate of the target project is obtained and matched from the scheduling database, and the number of vehicles in the supplementary scheduling state and the total supplementary scheduling material quality are obtained, and the first scheduling instruction is generated according to the number of vehicles in the supplementary scheduling state and the total supplementary scheduling material quality; the material consumption index growth rate of the above-mentioned target project refers to the deviation ratio between the material consumption index of the target project and the maximum value of the material consumption reference interval, specifically, the material consumption index of the target project is subtracted from the maximum value of the material consumption reference interval, and the result is divided by the maximum value of the material consumption reference interval, and finally the material consumption index growth rate of the target project is obtained. rate; the above-mentioned number of vehicles in the supplementary scheduling status and the total supplementary scheduling material quality, the specific matching process is: the scheduling database stores the material consumption index growth rate-supplementary scheduling status vehicle number mapping table and the material consumption index growth rate-total supplementary scheduling material quality mapping table, and directly queries the material consumption index growth rate of the target project in the scheduling database to obtain the number of vehicles in the supplementary scheduling status and the total supplementary scheduling material quality corresponding to the material consumption index growth rate of the target project; the above-mentioned first scheduling instruction, which is an optimized scheduling instruction set for the number of vehicles in the supplementary scheduling status and the total supplementary scheduling material quality, aims to ensure the precise matching of material supply and construction demand by dynamically allocating transportation resources, and sends it to relevant technical personnel.

[0029] If the material consumption index of the target project is less than the minimum value of the material consumption reference interval, the expected departure time will be delayed and a second scheduling instruction will be generated based on the delay prompt. The above-mentioned second scheduling instruction is an optimized scheduling instruction set based on the delay prompt, which aims to avoid oversupply of materials and idle transportation resources by dynamically adjusting the expected departure time of the vehicle and the allocation of transportation resources. The above-mentioned expected departure time is determined by technical personnel through the construction management and control platform, integrating progress simulation data, real-time monitoring values ​​of the material consumption index and traffic situation perception information, and using time series prediction algorithms (such as long short-term memory networks) to generate basic time window recommendations. The final departure time must be electronically approved by the technical person in charge through the digital authentication system, and the timed wake-up program of the on-board terminal and the interlocking control of the preparation process in the on-site receiving area will be triggered simultaneously to ensure that the spatiotemporal coordination accuracy meets the minute-level control requirements.

[0030] Furthermore, the specific allocation process for the number of vehicles in the supplementary scheduling state and the total quality of supplementary scheduling materials is as follows: obtain the operating efficiency index of each vehicle in the to-be-scheduled state, and sort them in descending order according to the operating efficiency index; based on the number of vehicles in the supplementary scheduling state, mark the vehicles in the to-be-scheduled state starting from the vehicle with the first operating efficiency index in turn, and mark them as vehicles in the supplementary scheduling state until the number of marked vehicles is equal to the number of vehicles in the supplementary scheduling state; at the same time, obtain the operating efficiency factor of each vehicle in the supplementary scheduling state, perform difference processing with the operating efficiency threshold, perform ratio processing with the processing result and the operating efficiency threshold, and finally obtain the operating efficiency margin of each vehicle in the supplementary scheduling state, obtain the basic scheduling material quality, and according to the operating efficiency margin of each vehicle in the supplementary scheduling state, obtain the actual scheduling material quality of each vehicle in the supplementary scheduling state, and then distribute the total quality of supplementary scheduling materials, starting from the vehicle in the supplementary scheduling state with the first operating efficiency index, until the total quality of supplementary scheduling materials is equal to the total quality of supplementary scheduling materials. Allocation is completed, which specifically refers to the actual dispatch material mass allocated to the supplementary dispatch status vehicle from the total supplementary dispatch material mass. If the supplementary dispatch status vehicle cannot fully allocate the total supplementary dispatch material mass, an early warning will prompt the technical staff to dispatch additional vehicles; the above-mentioned operating efficiency margin is used to quantify the extent to which the operating efficiency factor is greater than the operating efficiency threshold; the above-mentioned basic dispatch material mass refers to the rated value of the material mass that the vehicle can transport, which is extracted from the vehicle production specification; the actual dispatch material mass of each supplementary dispatch status vehicle is specifically obtained as follows: the scheduling database stores the operating efficiency margin-quality correction coefficient mapping table, and directly queries the operating efficiency margin of each supplementary dispatch status vehicle from the scheduling database to obtain the quality correction coefficient corresponding to the operating efficiency margin, and multiplies it with the basic dispatch material mass. The processing result is the actual dispatch material mass of each supplementary dispatch status vehicle. The above-mentioned quality correction coefficient represents the proportional value of the reduction correction of the basic dispatch material mass.

[0031] It needs to be explained that the dispatching vehicles are of uniform specifications, so the quality of basic dispatching materials is consistent.

[0032] In a specific embodiment, the present invention sorts by operating efficiency index and prioritizes marking high-efficiency vehicles as supplementary dispatch vehicles, which can give full play to the transportation capacity of high-efficiency vehicles, improve overall transportation efficiency, reduce transportation costs and time losses, and allocate actual dispatch material quality based on operating efficiency margin, so that high-efficiency vehicles can take on more transportation tasks, optimize resource allocation, avoid resource waste and uneven distribution, and such a scientific and reasonable allocation mechanism ensures the accurate delivery of the total supplementary dispatch material quality, effectively guarantees the timely supply of construction materials, and maintains a stable construction progress.

[0033] Step 2: The vehicle transports materials according to the established transportation route, collects and analyzes the characteristic parameters of the vehicle's transportation route, and makes intelligent corrections to the vehicle scheduling process.

[0034] Specifically, the vehicle scheduling process is intelligently corrected. The specific correction process is: analyze the characteristic parameters of the transportation path to which the vehicle belongs, obtain the congestion index of the transportation path, and match the estimated transportation time of the transportation path from the scheduling database based on the congestion index of the transportation path; the above-mentioned estimated transportation time of the transportation path is specifically matched as follows: store a mapping table of congestion index-estimated transportation time of the transportation path in the scheduling database, and directly query the congestion index of the transportation path from the scheduling database to obtain the estimated transportation time of the transportation path corresponding to the congestion index.

[0035] It should be explained that, based on the congestion index of the transport route, the estimated transport time of the transport route matched from the scheduling database is greater than or equal to the basic transport time.

[0036] According to the estimated transportation time of the transportation route, the first scheduling instruction and the second scheduling instruction are corrected. The specific correction process is: obtain the basic transportation time, and perform subtraction processing on it with the estimated transportation time of the transportation route, and mark the processing result as the transportation time deviation value; the above-mentioned basic transportation time represents the theoretical transportation time completed under standard reference conditions (such as ideal weather, normal road conditions, default loading volume and other preset benchmark parameters), which is extracted from the scheduling database; the above-mentioned transportation time deviation value refers to the deviation time between the basic transportation time and the estimated transportation time of the transportation route, specifically, the transportation time deviation value is obtained by subtracting the basic transportation time from the estimated transportation time of the transportation route.

[0037] The estimated departure time of the vehicle in the supplementary scheduling status is obtained, and the estimated departure time of the vehicle in the supplementary scheduling status is advanced according to the transport time deviation value, thereby correcting the first scheduling instruction; the above-mentioned advance correction processing refers to advancing the estimated departure time of the vehicle in the supplementary scheduling status by the time corresponding to the transport time deviation value, thereby obtaining the actual departure time of the vehicle in the supplementary scheduling status, and the actual departure time of the vehicle in the supplementary scheduling status is included in the corrected first scheduling instruction.

[0038] Obtain the estimated departure time of the vehicle in the waiting state, and correct the estimated departure time of the vehicle in the waiting state according to the transport time deviation value, thereby correcting the second scheduling instruction; the above-mentioned delay correction processing refers to querying the estimated departure time correction duration from the scheduling database according to the transport time deviation value, and adding it to the estimated departure time of the vehicle in the waiting state, thereby correcting the estimated departure time of the vehicle in the waiting state, wherein the estimated departure time correction duration refers to the time duration for advancing or delaying the estimated departure time.

[0039] The estimated departure time points of vehicles in the supplementary scheduling status and the estimated departure time points of vehicles in the waiting-to-depart status are all integrated by technical personnel through the construction management and control platform with progress simulation data, real-time monitoring values ​​of material consumption index and traffic situation perception information, and the basic time window recommendations are generated using time series prediction algorithms (such as long short-term memory networks). The final departure time point must be electronically approved by the technical person in charge through the digital authentication system.

[0040] Furthermore, the congestion index of the transport path is specifically analyzed as follows: the characteristic parameters of the transport path to which the vehicle belongs include the vehicle density of the transport path, the historical maximum vehicle transport time of the transport path, and the average curvature radius of the transport path; the above-mentioned vehicle density refers to the number of vehicles distributed per unit area, which can be monitored by traffic monitoring cameras; the above-mentioned historical maximum vehicle transport time indicates the longest time required for a vehicle to complete the transport task of this path in historical transport figures, which is extracted from the scheduling database; the above-mentioned average curvature radius is a quantitative indicator of the degree of path curvature, which is extracted from the path geometry information in high-precision map data (such as Open Street Map).

[0041] According to the material consumption index of the target project, the congestion increment is matched from the scheduling database. The above congestion increment is used to quantitatively evaluate the parameter of the additional contribution of the material consumption index to the regional traffic congestion level. The specific matching process is as follows: the material consumption index-congestion increment mapping table is stored in the scheduling database, and the material consumption index of the target project is directly queried to obtain the congestion increment corresponding to the material consumption index of the target project.

[0042] By quantifying the degree of influence of the proportional relationship between vehicle density and defined vehicle density on the congestion index, the degree of influence of the proportional relationship between historical maximum vehicle transportation time and defined historical maximum vehicle transportation time on the congestion index, and the degree of influence of the proportional relationship between average curvature radius and defined average curvature radius on the congestion index through measurement factors, each degree of influence is coupled with the congestion increment to obtain the congestion index of the transport path; it should be explained that when the material consumption index increases, the congestion increment matched from the scheduling database increases, which directly reflects the additional pressure on transportation demand. On the one hand, the increase in congestion increment will attract more vehicles to be put into transportation to meet material demand, which directly leads to a sharp increase in vehicle density on the transport path. After the vehicle density increases, the road space is further compressed and the distance between vehicles is shortened. , mutual interference intensifies, driving flexibility is significantly reduced, vehicles frequently start and stop, and traffic efficiency drops significantly, which in turn drives up the congestion index. On the other hand, the increase in vehicle density makes road resources increasingly scarce. Vehicles need to spend more time searching for suitable driving spaces and waiting for other vehicles to give way during driving. This directly increases the historical maximum vehicle transport time. The increase in historical maximum vehicle transport time means that vehicles stay longer on the transport route, further exacerbating road congestion. Moreover, longer transport times cause more vehicles to gather on the transport route per unit time, forming a vicious cycle that continuously increases vehicle density and jointly drives the congestion index up. The average curvature radius of the transport route, as a key parameter of road geometry, also has a significant impact on congestion. The smaller the average curvature radius, the more and sharper the road bends, and the more frequently vehicles need to slow down and adjust direction during driving. This not only reduces vehicle speed but also increases the difficulty of following other vehicles. When vehicles slow down on curves, they hinder the passage of vehicles behind them, increasing queue lengths and indirectly driving up vehicle density. Frequent deceleration and steering operations also prolong vehicle travel time on the transport route, further increasing the historical maximum transport time. The synergistic effect of increased vehicle density and historical maximum transport time ultimately leads to a significant increase in the congestion index. In summary, incremental congestion directly increases vehicle density by increasing vehicle input, which in turn increases historical maximum transport time. A smaller average curvature radius indirectly increases vehicle density and historical maximum transport time by reducing vehicle speeds and increasing travel difficulty. These four interrelated and progressive parameters contribute to a continuous increase in the transport route's congestion index, impacting the efficiency and smoothness of the entire project's transportation.

[0043] The congestion index of the transport path indicates the degree of congestion of the transport path. The specific expression is: ; Where, is the congestion index of the transport path, For the increase in congestion, is the vehicle density of the transport route, The vehicle density is defined in the dispatch database. is the historical maximum vehicle transportation time of the transportation route, The maximum transportation time of historical vehicles is preset in the dispatch database. is the average curvature radius of the transport path, is the defined mean curvature radius preset in the scheduling database, is the vehicle density measurement factor preset in the scheduling database, The maximum transport time factor of historical vehicles preset in the dispatch database, It is the average curvature radius measurement factor preset in the scheduling database.

[0044] The above definition of vehicle density indicates the maximum value allowed for vehicle density; the above definition of historical maximum vehicle transportation time indicates the maximum value allowed for historical maximum vehicle transportation time; the above definition of average curvature radius indicates the minimum value allowed for the average curvature radius.

[0045] The above-mentioned vehicle density measurement factor is used to quantify the degree of influence of the unit value of vehicle density on the congestion index; the above-mentioned historical vehicle maximum transport time measurement factor is used to quantify the degree of influence of the unit value of the historical vehicle maximum transport time on the congestion index; the above-mentioned average curvature radius measurement factor is used to quantify the degree of influence of the unit value of the average curvature radius on the congestion index. The scheduling database stores the correspondence between vehicle density, historical vehicle maximum transport time and average curvature radius and their corresponding measurement factors. For example, when the vehicle density, historical vehicle maximum transport time and average curvature radius are input into the scheduling database, the scheduling database can retrieve the vehicle density measurement factor, historical vehicle maximum transport time measurement factor and average curvature radius measurement factor, and the value range is between 0 and 1.

[0046] Step 3: Obtain and analyze the vehicle's operating status parameters, and at the same time, modify the vehicle's operating status parameters based on the material usage parameters of the target project's construction process and the characteristic parameters of the vehicle's transportation route, so as to determine whether to issue a scheduling warning for the vehicle.

[0047] In a specific embodiment, the present invention can accurately reflect the real-time transportation performance of vehicles by judging the vehicle's operating status and updating the efficiency factor after the operation is completed, providing a reliable basis for subsequent scheduling decisions. By comparing the efficiency factor of the vehicle to be scheduled with the threshold, it can scientifically determine whether to issue an early warning, identify low-efficiency vehicles in advance, and effectively prevent transportation risks. Low-efficiency vehicles to be scheduled are marked as waiting for inspection and early warning, and maintenance can be arranged in time to avoid faults affecting construction. The idle and operating status classification is clearly defined, making vehicle management clear and organized, which helps to achieve reasonable allocation of vehicle resources, ensure efficient and stable transportation of construction materials, and promote the smooth progress of the project.

[0048] Specifically, it is determined whether to issue a dispatch warning to the vehicle. The specific judgment process is as follows: the vehicle's operating status is determined. If the vehicle is in the operating state, when the vehicle completes the operation, the vehicle's operating efficiency factor is updated by the efficiency reduction coefficient, and the vehicle is marked as a state to be dispatched. The above-mentioned operation efficiency factor of the vehicle is updated, that is, The value of is updated to The corresponding results.

[0049] The vehicle's operating status parameters are analyzed to obtain the vehicle's operating efficiency factor, thereby obtaining the operating efficiency factor of the idle vehicle and comparing it with the operating efficiency threshold. If the operating efficiency factor of the idle vehicle is greater than or equal to the operating efficiency threshold, the idle vehicle is marked as a vehicle to be dispatched; the above-mentioned operating efficiency threshold represents the minimum value of the reasonable range of the operating efficiency factor and is extracted from the dispatch database.

[0050] If the operating efficiency factor of an idle vehicle is less than the operating efficiency threshold, a scheduling warning will be issued. The specific warning process is: the idle vehicle corresponding to the operating efficiency factor less than the operating efficiency threshold will be marked as a vehicle awaiting maintenance, and a warning instruction will be generated for warning prompts; the above-mentioned warning instruction, including but not limited to the vehicle's operating efficiency factor and the vehicle's specific license plate, will be sent to the technician in the form of a visual image or text message, thereby completing the warning prompt.

[0051] Furthermore, the specific analysis process of the operating efficiency index is as follows: the vehicle's operating status parameters include the vehicle's volume loss and the vehicle's container deformation; the above-mentioned volume loss refers to the actual reduction in available volume of the vehicle container due to physical deformation, leakage or structural aging, and the volume loss = original volume - current effective volume; the above-mentioned container deformation refers to the degree of volume change of the vehicle container after being subjected to force, usually expressed as deformation rate (%), deformation rate = (container volume after deformation - original container volume) / original size × 100%. The volume loss and container deformation can both be obtained through detection by quality inspectors.

[0052] The influence of the proportional relationship between the volume loss and the defined volume loss on the operating efficiency factor and the proportional relationship between the container deformation and the defined container deformation on the operating efficiency factor are quantified by the measurement coefficient. The various influence degrees are summarized to obtain the vehicle's operating efficiency factor. The vehicle's operating efficiency factor refers to the efficiency of the vehicle in carrying materials. The specific expression is: ; Where, is the vehicle's operating efficiency factor, k is a non-zero constant to ensure the effectiveness of the operating efficiency factor, is the volume loss of the vehicle, The volume loss is defined in the scheduling database. is the container deformation of the vehicle, Define container shape variables preset in the scheduling database, is the volume loss measurement coefficient preset in the dispatch database, It is the container shape variable measurement coefficient preset in the scheduling database.

[0053] The above-mentioned definition of volume loss represents the maximum value allowed for the volume loss, and the above-mentioned definition of container deformation represents the maximum value allowed for the container deformation.

[0054] The above-mentioned volume loss measurement coefficient represents the degree of influence of the unit value of the volume loss on the operating efficiency factor; the above-mentioned container deformation measurement coefficient represents the degree of influence of the unit value of the container deformation on the operating efficiency factor. The scheduling database stores the correspondence between the volume loss and the container deformation and its corresponding container deformation. For example, when the volume loss and the container deformation are input into the scheduling database, the scheduling database can retrieve the volume loss measurement coefficient and the container deformation measurement coefficient, and the value range is between 0 and 1.

[0055] It needs to be explained that when the volume loss increases, it means that the actual space available for loading materials on the vehicle decreases. Under the same transportation task, it may be necessary to increase the number of transportation times to complete the transportation of a given amount of materials, resulting in reduced vehicle transportation efficiency and a negative impact on the operating efficiency factor. The container deformation increases, which changes the distribution state of the material in the container, destroys the stability of the material stacking, and reduces transportation safety and reliability. At the same time, the space utilization rate of the deformed container decreases, further weakening the volume loss, which also has a negative effect on the operating efficiency factor. The decrease in volume loss and container deformation jointly indicates that the vehicle's efficiency in carrying materials has decreased.

[0056] According to the material consumption index of the target project, the efficiency reduction coefficient is matched from the scheduling database; the above-mentioned efficiency reduction coefficient represents the proportional value of the reduction of the operating efficiency factor. The specific matching process is: the material consumption index-efficiency reduction coefficient mapping table is stored in the scheduling database, and the material consumption index of the target project is directly queried to obtain the efficiency reduction coefficient corresponding to the material consumption index of the target project.

[0057] The operating efficiency factor is corrected by the efficiency reduction coefficient. At the same time, the measurement coefficient is introduced to quantify the impact of the correction result on the operating efficiency index and the impact of the congestion index on the operating efficiency index. The various impacts are summarized to obtain the operating efficiency index. The operating efficiency index is a quantitative measurement indicator of the vehicle's ability to perform material transportation tasks during highway and municipal engineering construction. The specific expression is: ; Where, is the operational efficiency index, is the vehicle's operating efficiency factor, is the efficiency reduction coefficient, is the congestion index of the transport path, is the operational efficiency factor measurement coefficient preset in the scheduling database, It is the congestion index measurement coefficient preset in the scheduling database.

[0058] The above-mentioned operating efficiency factor measurement coefficient represents the degree of influence of the unit value of the operating efficiency factor on the operating efficiency index; the above-mentioned congestion index measurement coefficient represents the degree of influence of the unit value of the congestion index on the operating efficiency index. The scheduling database stores the correspondence between the operating efficiency factor and the congestion index and their corresponding measurement coefficients. For example, by inputting the operating efficiency factor and the congestion index into the scheduling database, the scheduling database can retrieve the operating efficiency factor measurement coefficient and the congestion index measurement coefficient, and the value range of both is between 0 and 1.

[0059] In the field of highway and municipal engineering transportation scheduling, the material consumption index of the target project, as a key driving variable, profoundly affects the dynamic relationship between the efficiency reduction coefficient, the operating efficiency factor and the congestion index, and ultimately acts on the operating efficiency index. The efficiency reduction coefficient is essentially a negative correction factor for the operating efficiency factor. Its numerical change is directly due to the change in the intensity of the transportation task reflected by the material consumption index. Since the increase in the material consumption index means that the project has higher requirements for the timeliness, frequency and carrying capacity of material transportation, vehicles need to cope with higher-intensity transportation loads in the short term, which inevitably leads to increased vehicle wear and tear, increased risk of failures, and flexible transportation plans. The efficiency is reduced, thereby weakening the comprehensive efficiency of the vehicle in carrying and transporting materials. The efficiency reduction coefficient is precisely through quantifying the efficiency attenuation caused by high-intensity transportation demand, which reduces the value of the operation efficiency factor. The operation efficiency factor is the core indicator for measuring the efficiency of vehicles in carrying materials in a transportation environment. Its reduction directly reflects that when the vehicle copes with tasks with high material consumption index, it is affected by its own performance loss and planning constraints, and its actual transportation capacity declines. At the same time, the congestion index is a real-time reflection of the traffic conditions of the transportation path. Its value fluctuation and the operation efficiency factor jointly interact with the operation efficiency index. An increase in the congestion index indicates that there is a shortage of transportation resources on the transportation path. The vehicle speed slows down, the waiting time for parking is prolonged, and the traffic efficiency of the transportation route drops significantly. This change weakens the operation efficiency index from two levels: first, congestion increases the time cost of vehicles in the transportation process, and the transportation volume completed by vehicles per unit time decreases, which indirectly aggravates the "dilution effect" of the vehicle carrying efficiency represented by the operation efficiency factor, and further reduces the contribution of the operation efficiency factor in the comprehensive efficiency evaluation; second, the congestion index is an independent variable in the operation efficiency index. Its value increase directly has a negative weight effect on the operation efficiency index, further lowering the final result of the operation efficiency index, and the efficiency reduction coefficient and operation efficiency are reduced. The interaction mechanism of the efficiency factor, congestion index and other factors presents the characteristics of hierarchical progression and synergistic coupling. The efficiency reduction coefficient directly lowers the operating efficiency factor by quantifying the efficiency attenuation under a high material consumption index. The reduction of the operating efficiency factor and the increase of the congestion index jointly weaken the vehicle transportation capacity represented by the operating efficiency index. Conversely, if the material consumption index decreases, the efficiency reduction coefficient will decrease accordingly, the operating efficiency factor will rebound, and the congestion index will decrease. The three will synergistically promote the increase of the operating efficiency index, reflecting the improvement of vehicle transportation efficiency. This dynamic relationship provides a quantitative decision-making basis for the engineering scheduling system to optimize the allocation of transportation resources and balance transportation demand and supply.

[0060] In a specific embodiment, the present invention provides an intelligent monitoring and scheduling method for highway and municipal engineering construction processes. By monitoring material usage parameters and determining whether to intelligently optimize vehicle scheduling, it can make accurate scheduling decisions based on the comparison results of the material consumption index and the reference interval, avoid blind scheduling, improve resource utilization efficiency, and reduce the risk of material shortages or backlogs. When correcting the intelligently optimized vehicle scheduling, it combines the transportation path congestion index to match the expected transportation time, and corrects the scheduling instructions in advance or delay to ensure that vehicles depart at the optimal time, reduce transportation delays, ensure timely supply of materials, maintain a stable construction progress, determine whether to perform a scheduling warning link, comprehensively integrate the vehicle operation status and operation efficiency factors, accurately identify low-efficiency vehicles and issue warnings, arrange maintenance in advance, avoid vehicle failures affecting construction, ensure transportation continuity, and effectively ensure the smooth progress of the project.

[0061] Reference Figure 2 As shown, the second aspect of the present invention provides an intelligent monitoring and scheduling system for highway and municipal engineering construction processes, including: an optimization scheduling module, an intelligent correction module, a scheduling warning module and a scheduling database.

[0062] The optimized scheduling module is connected to the intelligent correction module, the intelligent correction module is connected to the scheduling warning module, and the optimized scheduling module, the intelligent correction module and the scheduling warning module are all connected to the scheduling database.

[0063] The optimization scheduling module is used to mark highways and municipal projects as target projects, monitor and analyze the material usage parameters during the construction process of the target projects, and thus determine whether to perform intelligent optimization vehicle scheduling.

[0064] The intelligent correction module is used to transport materials according to the established transportation route, collect and analyze the characteristic parameters of the transportation route to which the vehicle belongs, and make intelligent corrections to the vehicle scheduling process.

[0065] The scheduling and warning module is used to obtain and analyze the vehicle's operating status parameters. At the same time, it corrects the vehicle's operating status parameters through the material usage parameters of the target project construction process and the characteristic parameters of the vehicle's transportation route, so as to determine whether to issue a scheduling warning for the vehicle.

[0066] Figure 3This is a detailed flow chart of the present invention. First, the material consumption index of the target project is monitored and compared with a preset reference range. If the index is within the normal range, the current scheduling plan is maintained until the construction is completed. If the index is abnormal, the material consumption rate is further determined. When the consumption rate exceeds the upper limit, the supplementary scheduling mechanism is triggered. After correcting the transportation time through path congestion analysis, transportation tasks are assigned according to vehicle efficiency priority. When the consumption rate falls below the lower limit, a delayed departure instruction is generated, and path time correction is performed simultaneously. All scheduling instructions must undergo dynamic path congestion correction before execution. The system then detects the operating efficiency status of the executing vehicle. If the vehicle efficiency meets the standard, the normal transportation task is executed according to the corrected instruction. If the efficiency does not reach the threshold, an early warning is immediately generated and the vehicle is marked for maintenance. Finally, all processes are aggregated to a unified end node to complete closed-loop management.

[0067] Figure 4 This is a detailed schematic diagram of the material allocation process of the present invention. The process describes the coordinated optimization mechanism of vehicle marking and material allocation in material replenishment scheduling: the system first sorts the scheduled vehicles in descending order of their operating efficiency index, and uses a circular marking mechanism to screen a specified number of high-efficiency vehicles as replenishment scheduling targets; an efficiency margin assessment is performed on the marked vehicles, and the transport capacity margin of each vehicle is determined by calculating the ratio of the difference between the operating efficiency factor and a preset threshold. A dynamic allocation model is established based on the efficiency margin ratio, and a circular allocation method is used to allocate the total replenishment material mass to each replenishment vehicle in descending order of priority until all material allocation tasks are completed, forming a closed-loop resource allocation process of "efficiency sorting-vehicle screening-capacity assessment-on-demand allocation."

[0068] The above content is merely an example and explanation of the structure of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the scope of protection of the present invention.

Claims

1. An intelligent monitoring and scheduling method for highway and municipal engineering construction process, characterized in that: include: Step 1: Mark highways and municipal projects as target projects, monitor and analyze material usage parameters during the construction process of the target projects, and determine whether to perform intelligent optimization of vehicle scheduling; Step 2: The vehicle transports materials according to the established transportation route, collects and analyzes the characteristic parameters of the transportation route to which the vehicle belongs, and makes intelligent corrections to the vehicle scheduling process; Step 3: Obtain and analyze the vehicle's operating status parameters, and at the same time, modify the vehicle's operating status parameters based on the material usage parameters of the target project's construction process and the characteristic parameters of the vehicle's transportation route, so as to determine whether to issue a scheduling warning for the vehicle.

2. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 1 is characterized by: The specific process of determining whether to perform intelligent optimization of vehicle dispatch is as follows: Analyze the material usage parameters during the construction process of the target project, derive the material consumption index of the target project, and compare it with the material consumption reference range; If the material consumption index of the target project belongs to the material consumption reference range, intelligent optimization vehicle scheduling will not be performed; if the material consumption index of the target project does not belong to the material consumption reference range, intelligent optimization vehicle scheduling will be performed.

3. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 2 is characterized by: The specific optimization process of intelligent optimization vehicle scheduling is as follows: If the material consumption index of the target project is greater than the maximum value of the material consumption reference interval, then the number of vehicles in the supplementary scheduling state and the total supplementary scheduling material mass are matched from the scheduling database based on the material consumption index growth rate of the target project, and the first scheduling instruction is generated according to the number of vehicles in the supplementary scheduling state and the total supplementary scheduling material mass; If the material consumption index of the target project is less than the minimum value of the material consumption reference interval, a delay prompt will be given for the expected departure time point, and a second scheduling instruction will be generated based on the delay prompt.

4. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 1 is characterized by: The vehicle dispatching process is intelligently corrected, and the specific correction process is as follows: Analyze the characteristic parameters of the transport route to which the vehicle belongs, obtain the congestion index of the transport route, and match the estimated transport time of the transport route from the scheduling database based on the congestion index of the transport route; According to the estimated transportation time of the transportation route, the first and second dispatch instructions are modified. The specific modification process is as follows: Obtain the basic transportation time and perform a difference calculation with the estimated transportation time of the transportation route. The result is marked as the transportation time deviation value. Obtaining the estimated departure time of the vehicle in the supplementary scheduling state, and performing a pre-correction process on the estimated departure time of the vehicle in the supplementary scheduling state according to the transportation time deviation value, thereby correcting the first scheduling instruction; The estimated departure time of the vehicle in the ready-to-depart state is obtained, and the estimated departure time of the vehicle in the ready-to-depart state is corrected according to the transport duration deviation value, thereby correcting the second scheduling instruction.

5. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 1 is characterized by: The specific process of determining whether to issue a dispatch warning to a vehicle is as follows: Determine the vehicle's operating status. If the vehicle is in an operating state, then when the vehicle completes its operation, update the vehicle's operating efficiency factor using the efficiency reduction coefficient and mark the vehicle as being in a waiting-for-dispatch state. Analyze the vehicle's operating status parameters to obtain the vehicle's operating efficiency factor, thereby obtaining the operating efficiency factor of the idle vehicle and comparing it with the operating efficiency threshold. If the operating efficiency factor of the idle vehicle is greater than or equal to the operating efficiency threshold, the idle vehicle will be marked as a vehicle to be dispatched; If the operating efficiency factor of an idle vehicle is less than the operating efficiency threshold, a scheduling warning will be issued. The specific warning process is: the idle vehicle corresponding to the operating efficiency factor less than the operating efficiency threshold will be marked as a vehicle in a waiting for maintenance state, and a warning instruction will be generated to issue a warning prompt.

6. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 3 is characterized by: The specific allocation process of the number of vehicles in the supplementary scheduling state and the total supplementary scheduling material quality is as follows: Obtain the operating efficiency index of each vehicle in the waiting-for-dispatch state and sort them in descending order according to the operating efficiency index. Based on the number of vehicles in the supplementary dispatch state, mark the vehicles in the waiting-for-dispatch state starting with the one with the highest operating efficiency index as supplementary dispatch state vehicles until the number of marked vehicles equals the number of vehicles in the supplementary dispatch state. At the same time, the operating efficiency factor of each vehicle in the supplementary scheduling status is obtained, and the difference processing is performed with the operating efficiency threshold. The processing result is compared with the operating efficiency threshold to finally obtain the operating efficiency margin of each vehicle in the supplementary scheduling status, obtain the basic scheduling material quality, and according to the operating efficiency margin of each vehicle in the supplementary scheduling status, the actual scheduling material quality of each vehicle in the supplementary scheduling status is obtained, and then the total supplementary scheduling material quality is distributed, starting from the supplementary scheduling status vehicle with the highest operating efficiency index until the total supplementary scheduling material quality distribution is completed.

7. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 3 is characterized by: The material consumption index of the target project is analyzed in the following way: The material usage parameters of the target project construction process include the material footprint reduction rate, the construction area growth rate, and the material usage rate; The influence of the deviation between the material footprint reduction rate and the reference material footprint reduction rate on the material consumption index, the deviation between the constructed area growth rate and the reference constructed area growth rate on the material consumption index, and the deviation between the material utilization rate and the reference material utilization rate on the material consumption index are quantified through measurement values. The material consumption index of the target project is obtained by coupling each influence degree. The material consumption index of the target project indicates the material consumption of the target project.

8. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 4 is characterized by: The specific analysis process of the congestion index of the transport route is as follows: The characteristic parameters of the transport path to which the vehicle belongs include the vehicle density of the transport path, the historical maximum transport time of the vehicle on the transport path, and the average curvature radius of the transport path; According to the material consumption index of the target project, the congestion increment is matched from the scheduling database; The congestion index of the transport route is derived by quantifying the influence of the proportional relationship between vehicle density and the defined vehicle density, the proportional relationship between the historical maximum vehicle transport time and the defined historical maximum vehicle transport time, and the proportional relationship between the average curvature radius and the defined average curvature radius on the congestion index through measurement factors. Each influence is coupled with the congestion increment to obtain the congestion index of the transport route. The congestion index of the transport path indicates the degree of congestion of the transport path.

9. The method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to claim 6 is characterized by: The specific analysis process of the operating efficiency index is as follows: The operating state parameters of the vehicle include the volume loss of the vehicle and the deformation of the container of the vehicle; The degree of influence of the proportional relationship between the volume loss amount and the defined volume loss amount on the operating efficiency factor and the degree of influence of the proportional relationship between the container deformation amount and the defined container deformation amount on the operating efficiency factor are quantified by the measurement coefficient, and the respective influence degrees are summarized to obtain the vehicle's operating efficiency factor, wherein the vehicle's operating efficiency factor refers to the efficiency of the vehicle in carrying materials; According to the material consumption index of the target project, the efficiency reduction coefficient is matched from the scheduling database; The operating efficiency factor is corrected by the efficiency reduction coefficient. At the same time, a measurement coefficient is introduced to quantify the impact of the correction result on the operating efficiency index and the impact of the congestion index on the operating efficiency index. The various impact levels are summarized to obtain the operating efficiency index. The operating efficiency index represents a quantitative measurement indicator of the vehicle's ability to perform material transportation tasks during the construction of highways and municipal projects.

10. A system using the method for intelligent monitoring and scheduling of highway and municipal engineering construction processes according to any one of claims 1 to 9, characterized in that: include: The optimization and scheduling module is used to mark highways and municipal projects as target projects, monitor and analyze material usage parameters during the construction process of the target projects, and determine whether to perform intelligent optimization of vehicle scheduling; The intelligent correction module is used to transport materials along the established transportation routes, collect and analyze the characteristic parameters of the transportation routes to which the vehicles belong, and make intelligent corrections to the vehicle scheduling process; The scheduling and warning module is used to obtain and analyze the vehicle's operating status parameters. At the same time, it corrects the vehicle's operating status parameters through the material usage parameters of the target project construction process and the characteristic parameters of the vehicle's transportation route, so as to determine whether to issue a scheduling warning for the vehicle.

Images