Overlimit and overload detection station layout planning method based on fuzzy comprehensive evaluation

Abstract

The invention relates to the field of road detection analysis, and particularly discloses an overrun and overload detection station layout planning method based on fuzzy comprehensive evaluation, and the method comprises the steps of road network data analysis, detection influence analysis and detection station layout planning. According to the method, complex and diverse road condition data are converted into road operation condition indexes, basic condition data and traffic demand data of each road in a road network region road are obtained, road traffic influence indexes are obtained through comprehensive analysis, and the basic condition data and the traffic demand data of each road in the road network region road are considered; the road operation condition index and the road traffic influence index are comprehensively analyzed to obtain the detection station planning index, and the actual operation condition of the road and the influence of various traffic factors on the set detection station are fully considered, so that the layout of the detection station is more reasonable, and the over-limit and overload behaviors are effectively monitored and attacked.

Description

Technical Field

[0001] The present invention relates to the field of highway detection and analysis, and specifically provides a layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation. Background Art

[0002] At present, with the rapid development of the economy and the prosperity of the transportation industry, the scale and quality of road-transported goods are continuously increasing, and the phenomenon of over-limit and over-load is becoming increasingly serious. Over-limit and over-load vehicles not only cause huge damage to highway infrastructure, shorten the service life of highways, bridges, etc., and increase maintenance costs, but also seriously affect road traffic safety, leading to frequent traffic accidents. Therefore, it is necessary to strengthen the supervision and management of over-limit and over-load behaviors by reasonably arranging over-limit and over-load detection stations.

[0003] For example, the invention patent with the publication number CN112270460B discloses a method for identifying overweight truck source stations based on multi-source data, which is used for identifying illegal overweight truck source stations. The main steps include four parts: data acquisition and preprocessing, truck overweight risk profiling, truck overweight risk discrimination, and illegal source station identification. The main work includes: first, collecting historical data of truck overweight detection and vehicle GPS data and performing data cleaning. Secondly, selecting the cumulative overweight per unit driving mileage, the illegal overweight frequency per unit driving mileage, and the one-way empty load frequency per unit driving mileage as key indicators to depict the truck overweight risk. Then, using the Fisher method to discriminate the truck overweight risk, classifying the vehicles with high overweight risk into the blacklist, and focusing on supervising their vehicle operation trajectories. Finally, based on the GPS data, the entire chain of vehicle operation trajectories is reproduced, and illegal source stations are identified by identifying stop points.

[0004] However, in the process of implementing the technical solutions of the present invention in the embodiments of the present application, it is found that the above technologies have at least the following technical problems: The existing over-limit and over-load detection station identification and planning methods mainly focus on using historical data of vehicle overweight detection and vehicle GPS data for detection station identification, without considering the comprehensive factors related to vehicle and detection station layout planning, which may lead to the inability to provide comprehensive and effective decision-making support for the layout planning of over-limit and over-load detection stations in practical applications. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the present invention provides a layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation, which can effectively solve the problems involved in the above background art.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: The present invention provides a layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation, including: S1. Road network data analysis: Obtain the initial road condition data of the roads in the road network area during the monitoring period, preprocess the initial road condition data of the roads in the road network area during the monitoring period to obtain the road condition data of the roads in the road network area during the monitoring period, and analyze the road condition data of the roads in the road network area during the monitoring period to obtain the road operation condition index; S2. Detection impact analysis: Obtain the basic condition data and traffic demand data of each road in the road network area, comprehensively analyze to obtain the road traffic impact index, compare the road traffic impact index with the preset road traffic impact index threshold in the evaluation database to obtain the comparison result, and finally give a warning prompt for road traffic according to the comparison result; S3. Detection station layout planning: Comprehensively analyze the road operation condition index and the road traffic impact index to obtain the detection station planning index, match the detection station planning index with the detection station coordinates corresponding to each interval of the preset detection station planning index in the evaluation database to obtain the over-limit and over-load detection station coordinates, and finally layout and plan the over-limit and over-load detection stations according to the over-limit and over-load detection station coordinates.

[0007] In this embodiment, fuzzy comprehensive evaluation is a comprehensive evaluation method based on fuzzy mathematics. It combines the fuzzy set theory and the idea of comprehensive evaluation, transforms qualitative evaluation into quantitative evaluation, and can better handle the fuzziness and uncertainty problems in the evaluation process.

[0008] As a further method, the specific analysis process of the road operation condition index is as follows: Comprehensively analyze the effective vehicle statistics, average vehicle speed calibration value, cross-section traffic optimization flow, standardized headway, and average over-load tonnage regularization value of the vehicles driving on the roads in the road network area during the monitoring period to obtain the road operation condition index.

[0009] As a further method, the specific analysis process of the road traffic impact index is as follows: Comprehensively analyze the road length, lane width, road surface friction coefficient, average road surface bearing capacity, average daily traffic flow, average vehicle driving speed, and average cargo transportation volume of each road in the road network area to obtain the road traffic impact index.

[0010] As a further method, the process of comparing the road traffic impact index with the preset road traffic impact index threshold in the evaluation database to obtain the comparison result is as follows: If the road traffic impact index is less than the threshold value of the road traffic impact index preset in the evaluation database, the comparison result is recorded as the first comparison result.

[0011] If the road traffic impact index is greater than or equal to the threshold value of the road traffic impact index preset in the evaluation database, the comparison result is recorded as the second comparison result.

[0012] When the comparison result is recorded as the second comparison result, a warning prompt for road traffic needs to be given.

[0013] As a further method, the specific analysis process of the detection site planning index is as follows: The road operation condition index and the road traffic impact index are comprehensively analyzed to obtain the detection site planning index. The specific analysis method is as follows: In the formula, is the detection site planning index, e is the natural constant, is the road operation condition index, is the road traffic impact index, is the weight factor corresponding to the unit value of the road operation condition index preset in the evaluation database, is the weight factor corresponding to the unit value of the road traffic impact index preset in the evaluation database.

[0014] As a further method, the matching of the detection site planning index with the detection site coordinates corresponding to each interval of the detection site planning index preset in the evaluation database is as follows: The detection site planning index is compared with the numerical values of each interval of the detection site planning index preset in the evaluation database to determine the specific interval corresponding to the detection site planning index, and the interval where the detection site planning index is located is obtained, that is, the detection site coordinates corresponding to this interval are obtained from the evaluation database; The coordinates of the overloading detection site are obtained, and finally, the layout plan of the overloading detection site is carried out according to the coordinates of the overloading detection site.

[0015] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) By analyzing the road condition data of the roads in the road network area during the monitoring period, the present invention converts the complex and diverse road condition data into a specific numerical index, that is, the road operation condition index, making the description of the overall road operation condition more intuitive, accurate and easy to understand. Through this index, the comprehensive operation level of the roads in the road network area during the monitoring period can be quickly understood, and the road condition can be evaluated based on this index.

[0016] (2) By obtaining the basic road condition data and traffic demand data of each road within the road network area, and comprehensively analyzing to obtain the road traffic impact index, considering the basic road condition data and traffic demand data of each road within the road network area, it can comprehensively and systematically reflect the impact of various factors on road traffic, and compare the road traffic impact index with the preset threshold of the road traffic impact index in the evaluation database, so as to discover in advance the potential risks that road traffic may face and ensure the safety and smoothness of road traffic.

[0017] (3) By comprehensively analyzing the road operation condition index and the road traffic impact index, the detection site planning index is obtained, which can fully consider the actual operation condition of the road and the impact of various traffic factors on the setting of detection sites. In this way, it can avoid the irrationality brought by planning detection sites solely based on a certain factor, making the planning of detection sites more scientific, reasonable and comprehensive. Matching the detection site planning index with the preset detection site coordinates corresponding to each interval in the evaluation database to obtain the over-limit and over-load detection site coordinates can accurately determine the location of the detection site. Layout planning of the over-limit and over-load detection sites according to the over-limit and over-load detection site coordinates can achieve scientific layout of the detection sites. Considering various factors such as the traffic condition, road network structure and coverage range of the detection sites within the region, the layout of the detection sites is made more reasonable, and it can effectively monitor and crack down on over-limit and over-load behaviors. Brief Description of the Drawings

[0018] The present invention will be further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the following drawings.

[0019] Figure 1 It is a schematic flow chart of the method steps of the present invention. Detailed Embodiments

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a 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 those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0021] Refer to Figure 1As shown in the figure, the present invention provides a layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation, including: S1. Road network data analysis: Obtain the initial road condition data of the roads in the road network area during the monitoring period, preprocess the initial road condition data of the roads in the road network area during the monitoring period to obtain the road condition data of the roads in the road network area during the monitoring period, and analyze the road condition data of the roads in the road network area during the monitoring period to obtain the road operation condition index.

[0022] S2. Detection impact analysis: Obtain the basic condition data and traffic demand data of each road in the road network area, comprehensively analyze to obtain the road traffic impact index, compare the road traffic impact index with the preset threshold of the road traffic impact index in the evaluation database to obtain the comparison result, and finally give a warning prompt for road traffic according to the comparison result.

[0023] S3. Layout planning of detection stations: Comprehensively analyze the road operation condition index and the road traffic impact index to obtain the detection station planning index, match the detection station planning index with the detection station coordinates corresponding to each interval of the preset detection station planning index in the evaluation database to obtain the over-limit and over-load detection station coordinates, and finally make a layout planning for the over-limit and over-load detection stations according to the over-limit and over-load detection station coordinates.

[0024] Further, the initial road condition data of the roads in the road network area during the monitoring period specifically includes the number of vehicles traveling on the roads in the road network area during the monitoring period, the average vehicle speed, the sectional traffic flow, the average headway time, and the average over-load tonnage.

[0025] It should be noted that the roads in the above road network area refer to the road network system within a specific area composed of multiple interconnected roads. This area can be a city, a region, or even a large-scale cross-regional transportation network. For example, the urban road network in a city includes roads of different levels such as arterial roads, secondary arterial roads, and branch roads, which are intertwined with each other to form the roads in the road network area of the city; or the regional road network composed of expressways, national highways, and provincial roads within a certain provincial region. In the layout planning of over-limit and over-load detection stations, clarifying the scope of the roads in the road network area helps to accurately analyze the traffic conditions and freight demands within this area; the monitoring period refers to the continuous observation time period set to obtain representative and regular traffic data. In this embodiment, this time period is set according to the research purpose and data requirements; the number of running vehicles is obtained through traffic flow monitoring devices installed on the road, such as loop detectors. The loop detectors are buried under the road surface. When a vehicle passes, the inductance of the coil changes, thereby detecting the vehicle and counting; the acquisition of the average vehicle speed also depends on the above-mentioned traffic flow monitoring devices. For example, the vehicle-mounted Beidou navigation system can record the driving trajectory and time information of the vehicle in real time, and then calculate the driving speed of different sections of the road. Through the statistical analysis of all vehicle speed data, the average vehicle speed of the roads in the road network area is obtained; the cross-section traffic flow is counted by the detection devices set at the road cross-section. Taking the loop detector as an example, multiple coils are laid at a certain cross-section of the road. When vehicles pass through the coils in sequence, the device records the number of vehicles passing through. The total number of vehicles passing through this cross-section within a unit time (such as per hour, per minute) is the cross-section traffic flow; the average headway is calculated from the vehicle passing time data collected by the traffic flow monitoring devices. For example, the video detector records the exact time when each vehicle passes through a specific position. The difference in passing time between two adjacent vehicles is the headway. By statistically averaging a large amount of headway data, the average headway can be obtained. This parameter can reflect the density and safety of vehicles driving on the road; the average over-load tonnage is obtained by weighing the passing vehicles in real time through dynamic weighing devices installed on the road (such as quartz crystal type and bending plate type weighing sensors), and combining with the approved load weight marked on the vehicle driving license, calculating the over-load tonnage of each vehicle, and then averaging the over-load tonnages of all detected over-loaded vehicles to obtain the average over-load tonnage.

[0026] Specifically, the initial road condition data of the roads in the road network area during the monitoring period is preprocessed. The specific preprocessing includes processing the missing values of the initial road condition data of the roads in the road network area during the monitoring period using the linear interpolation method, detecting and correcting outliers, and spatio-temporal alignment and fusion.

[0027] The data obtained by preprocessing the initial road condition data of the road network area within the monitoring period is denoted as the road condition data of the road network area within the monitoring period.

[0028] The road condition data of the road network area within the monitoring period specifically includes the effective vehicle volume statistic, average vehicle speed calibration value, cross-section traffic optimization flow, standardized headway, and average overloaded tonnage regularization value of the road network area within the monitoring period.

[0029] It should be noted that the detection of the above outliers is based on the 3σ principle for traffic flow anomaly detection, and the correction method is through Winsorize trimming (replaced with the 99th percentile value). Time alignment and fusion are operated through time standardization and spatial matching. The specific operation steps of time standardization are to unify the timestamp to the UTC+8 time zone, resample the irregular sampling data to a fixed interval (such as 5-minute granularity), and align the clock deviations of each system (such as the time difference between GPS and the detector <30s). The spatial matching operation is completed through the Join Attributes by Nearest tool in QGIS.

[0030] In this embodiment, through systematic preprocessing of the initial road condition data of the road network, the accuracy and reliability of subsequent fuzzy comprehensive evaluation and site layout planning can be significantly improved. The cleaned data enables the fuzzy membership function (such as the "congested / normal / smooth" division of vehicle speed) to truly reflect the road conditions, avoiding noise interference. At the same time, the accuracy of identifying overloaded hotspots after cleaning is improved, making the site layout more targeted.

[0031] Furthermore, the specific analysis process of the road operation condition index is as follows: The effective vehicle volume statistic, average vehicle speed calibration value, cross-section traffic optimization flow, standardized headway, and average overloaded tonnage regularization value of the road network area within the monitoring period are comprehensively analyzed to obtain the road operation condition index. The specific analysis method is as follows: In the formula, is the road operation condition index, e is the natural constant, is the effective vehicle volume statistic, is the reference vehicle volume preset in the evaluation database, is the influence factor corresponding to the unit value of the effective vehicle volume statistic preset in the evaluation database, is the average vehicle speed calibration value, is the reference vehicle speed preset in the evaluation database, is the influence factor corresponding to the unit value of the average vehicle speed calibration value preset in the evaluation database, is the cross-section traffic optimization flow, For evaluating the reference traffic flow of the cross-section preset in the database, For the impact factor corresponding to the unit value of the optimized traffic flow of the cross-section preset in the evaluation database, For the standardized headway, For the reference headway preset in the evaluation database, For the impact factor corresponding to the unit value of the standardized headway preset in the evaluation database, For the regularized value of the average overload tonnage, For the reference value of the overload tonnage preset in the evaluation database, For the impact factor corresponding to the unit value of the regularized value of the average overload tonnage preset in the evaluation database.

[0032] It should be noted that the above road operation condition index is a numerical index comprehensively reflecting the overall operation state of the roads in the road network area during the monitoring period. It is obtained through comprehensive analysis and calculation of multiple parameters such as the effective statistics of driving vehicles, the calibrated value of average vehicle speed, the optimized traffic flow of specific sections, the standardized headway, and the regularized value of average overloaded tonnage, and is used to evaluate the traffic congestion degree of the road, the smoothness of vehicle driving, and the impact of overloading, etc. on the road operation, so as to have a comprehensive and quantitative understanding of the usage condition of the road; the effective statistics of driving vehicles refers to the effective data volume obtained by counting the number of vehicles driving on the roads in the road network area during the monitoring period and through certain data processing and screening; the reference quantity of driving vehicles preset in the evaluation database is a reference value preset in the evaluation database for comparison with the effective statistics of driving vehicles actually counted; the calibrated value of average vehicle speed is the value obtained after measuring the average vehicle speed on the roads in the road network area during the monitoring period and through data preprocessing and calibration; the reference vehicle speed value preset in the evaluation database refers to a vehicle speed standard value preset in the evaluation database in advance; the optimized traffic flow of specific sections refers to the value obtained after analyzing and optimizing the traffic flow data of specific sections of the roads in the road network area during the monitoring period, and the reference traffic flow of specific sections preset in the evaluation database refers to the traffic flow reference standard for specific sections of the roads in the road network area preset in the evaluation database in advance; the standardized headway refers to the value obtained after standardizing the headway of vehicles on the roads in the road network area during the monitoring period; the reference headway preset in the evaluation database refers to a reference headway value preset in the evaluation database in advance; the regularized value of average overloaded tonnage refers to the value obtained after measuring and regularizing the average overloaded tonnage of vehicles on the roads in the road network area during the monitoring period, and the reference overloaded tonnage value preset in the evaluation database refers to a reference standard for vehicle overloaded tonnage preset in the evaluation database in advance; in this embodiment, the influence factors corresponding to the unit value of the effective statistics of driving vehicles preset in the evaluation database, the influence factors corresponding to the unit value of the calibrated value of average vehicle speed preset in the evaluation database, the influence factors corresponding to the unit value of the optimized traffic flow of specific sections preset in the evaluation database, the influence factors corresponding to the unit value of the standardized headway preset in the evaluation database, and the influence factors corresponding to the unit value of the regularized value of average overloaded tonnage respectively represent the influence degrees of the effective statistics of driving vehicles, the calibrated value of average vehicle speed, the optimized traffic flow of specific sections, the standardized headway, and the regularized value of average overloaded tonnage on the road operation condition index, where , , , , , and .

[0033] In this embodiment, when the effective statistic of the running vehicles is large, even greater than the preset reference quantity of the running vehicles, it means that the number of vehicles on the road is excessive, which may exceed the designed load-bearing capacity of the road, leading to increased traffic congestion, a decrease in the vehicle running speed, and a reduction in the road passing efficiency. When the average vehicle speed calibration value is large, even greater than the preset vehicle speed reference value, it will cause the traffic flow to be unstable, such as frequent overtaking and sudden braking, which may increase the risk of traffic accidents and have an adverse impact on the road operation condition index. When the cross-section traffic optimization flow is large, even greater than the preset cross-section traffic reference flow, it indicates that the traffic flow of this cross-section is too large and exceeds the normal passing capacity of the road, which will lead to traffic congestion, an increase in the vehicle queuing length, an extension of the passing time, and the smoothness of the traffic flow is damaged, easily triggering traffic jams and chaos, thereby reducing the road operation condition index. When the standardized headway is small, even less than the preset headway reference value, it means that the interval between vehicles is small and the traffic flow density is low. When the average overloaded tonnage regularization value is large, even greater than the preset overloaded tonnage reference value, vehicle overload will cause additional pressure and damage to the road infrastructure, shorten the service life of the road, increase the road maintenance cost. At the same time, overload will also affect the handling performance and braking distance of the vehicle, increase the risk of traffic accidents, seriously affect the operation safety and efficiency of the road, and thus have a significant negative impact on the road operation condition index, reducing it. Therefore, through the detailed analysis of each parameter in the road operation condition index, the road operation state can be accurately evaluated, providing a scientific basis for traffic management.

[0034] Specifically, the road basic condition data of each road in the road network area specifically includes the road length, lane width, road surface friction coefficient, and average road surface bearing capacity of each road in the road network area.

[0035] It should be explained that the road length of each road in the above-mentioned road network area is measured along the road center line by using professional measuring tools, such as total stations, GPS measuring instruments, etc. The lane width is measured on-site on the road by using measuring tools such as laser rangefinders. The road surface friction coefficient is measured by using a professional road surface friction coefficient tester, such as a pendulum friction coefficient tester. Multiple test points are selected on the road surface, and measurements are carried out in accordance with the operation specifications of the instrument. The road surface friction coefficient is calculated by measuring the friction force between the tire and the road surface. In this embodiment, the pendulum friction coefficient tester calculates the road surface friction coefficient by measuring the energy loss of the pendulum at the moment of contact with the road surface when the pendulum swings freely from a certain height. There is a rubber slider on the pendulum of the instrument. When the pendulum swings down, the rubber slider contacts the road surface and generates friction, reducing the swing amplitude of the pendulum. By measuring the height difference between the initial height and the final stopping position of the pendulum, as well as parameters such as the mass and length of the pendulum, the work done by the friction force is calculated using the principle of energy conservation, and then the road surface friction coefficient is obtained. The calculation formula is: , where F is the friction force, W is the weight of the pendulum, L is the length of the pendulum, h1 and h2 are the initial height and final height of the pendulum, S is the contact area between the rubber slider and the road surface, g is the acceleration of gravity, and the road friction coefficient is , N is the positive pressure of the rubber slider on the road surface. In the pendulum instrument, the positive pressure is equal to the component of the gravity of the pendulum in the direction perpendicular to the road surface; the average bearing capacity of the road surface is measured by professional testing equipment, such as the falling weight deflectometer (FWD), Beckman beam deflectometer, etc., by applying a certain load on the road, measuring the deformation of the road surface, and then obtaining the bearing capacity of the road surface.

[0036] Furthermore, the traffic demand data specifically includes the average daily traffic flow, average vehicle speed and average cargo transportation volume of each road during the historical monitoring period.

[0037] It should be explained that the above-mentioned average daily traffic flow is obtained by installing traffic flow monitoring equipment on the road, such as induction coils, video surveillance cameras, microwave detectors, etc. The average vehicle speed is obtained by utilizing the speed measurement function in the traffic flow monitoring equipment, such as radar speed meters, laser speed meters, etc. These devices can measure the speed of the vehicle while monitoring its passage. The average amount of cargo transportation can be obtained by obtaining the vehicle weight information through the vehicle weighing system at the toll station, and combining the vehicle type classification and statistical data of past vehicles to obtain the average amount of cargo transportation. In this embodiment, the above-mentioned historical monitoring period refers to a specific time period used to collect and analyze traffic data in the past, which is determined based on the specific research purpose and data availability.

[0038] Specifically, the road traffic impact index has a specific analysis process as follows: Comprehensively analyze the road length, lane width, road friction coefficient, average road bearing capacity, average daily traffic flow, average vehicle speed and average freight transport volume of each road in the road network area to obtain the road traffic impact index. The specific analysis method is as follows: ; In the formula, is the road traffic impact index, a is the number of each road, a=1,2,3,...,b, b is the total number of roads, is the length of the a-th road, Correction factor corresponding to the road length unit value preset in the evaluation database, is the lane width of the ath road, Correction factor corresponding to lane width unit value preset in evaluation database, is the road friction coefficient of the ath road, The road friction reference coefficient preset in the evaluation database is The correction factor corresponding to the unit value of the road surface friction coefficient preset in the evaluation database The average road surface bearing capacity of the a-th road The reference road surface bearing capacity preset in the evaluation database The correction factor corresponding to the unit value of the average road surface bearing capacity preset in the evaluation database The average daily traffic flow of the a-th road The reference average daily traffic flow preset in the evaluation database The correction factor corresponding to the unit value of the average daily traffic flow preset in the evaluation database The average vehicle driving speed of the a-th road The reference vehicle driving speed preset in the evaluation database The correction factor corresponding to the unit value of the average vehicle driving speed preset in the evaluation database The average volume of goods transportation of the a-th road The reference volume of goods transportation preset in the evaluation database The correction factor corresponding to the unit value of the average vehicle driving speed preset in the evaluation database

[0039] It should be noted that the above road traffic impact index is a value calculated through a specific analysis formula by comprehensively considering multiple factors such as road length, lane width, road surface friction coefficient, average road surface bearing capacity, daily average traffic flow, average vehicle driving speed, and average cargo transportation volume, and is used to comprehensively evaluate the comprehensive impact degree of a road on traffic operation in the road network area; the road length refers to the actual physical length of each road in the road network area; the lane width refers to the actual width of each lane on the road; the road surface friction coefficient is an index that measures the magnitude of the friction force between the road surface and the vehicle tires; the preset reference bearing capacity of the road surface in the evaluation database refers to a standard value preset in the traffic evaluation database; the daily average traffic flow refers to the average value of the daily traffic flow of a certain road during the historical monitoring period; the preset daily average reference traffic flow in the evaluation database refers to a reference value set in the traffic evaluation database, which is used to measure the rationality of the actual daily average traffic flow; the average vehicle driving speed refers to the average value calculated by measuring the speed of the vehicles driving on the road through specific monitoring equipment during the historical monitoring period; the preset reference driving speed of the vehicle in the evaluation database is a standard speed value preset in the traffic evaluation database, which is used as a reference basis for evaluating the actual average vehicle driving speed; the average cargo transportation volume refers to the average value of the cargo transportation volume on a certain road during the historical monitoring period; the preset reference cargo transportation volume in the evaluation database refers to a reference value set in the traffic evaluation database, which is used to evaluate the rationality of the actual average cargo transportation volume; the correction factors corresponding to the preset road length unit value, the correction factors corresponding to the preset lane width unit value, the correction factors corresponding to the preset road surface friction coefficient unit value, the correction factors corresponding to the preset average road surface bearing capacity unit value, the correction factors corresponding to the preset daily average traffic flow unit value, the correction factors corresponding to the preset average vehicle driving speed unit value, and the correction factors corresponding to the preset average vehicle driving speed unit value respectively represent the impact degrees of road length, lane width, road surface friction, average road surface bearing capacity, daily average traffic flow, average vehicle driving speed, and average vehicle driving speed on the road traffic impact index, where , , , , , , , and .

[0040] In this embodiment, a shorter road length results in a limited continuous driving distance for vehicles. Vehicles frequently encounter intersections, traffic lights, etc., increasing the number of stops and starts, reducing the overall traffic efficiency, and easily causing traffic congestion and chaos. A narrower lane width reduces the lateral safety distance between vehicles, increasing the interference between vehicles during driving, resulting in a decrease in the driving speed of vehicles and a consequent decline in the traffic capacity of the road. When the road surface friction coefficient is too large or too small, that is, when the deviation from the preset reference road surface friction coefficient is large, vehicles are prone to skidding during driving, especially during acceleration, braking, and turning. This seriously affects driving safety and increases the probability of traffic accidents. When the average road surface load-bearing capacity is small, even less than the preset reference road surface load-bearing capacity, it means that the road is more likely to suffer from fatigue damage, cracks, potholes, and other diseases under the action of vehicle loads, which will have a certain impact on traffic. Measures such as load limit and speed limit need to be taken for the road, which will affect the use efficiency of the road and restrict the passage of large vehicles and heavy-duty vehicles. When the average daily traffic flow is large, even exceeding the preset average daily reference traffic flow, it means that the designed traffic capacity of the road is exceeded, resulting in frequent traffic congestion. When the average vehicle driving speed is large, even greater than the preset reference vehicle driving speed, the impact force of high-speed vehicles on the road surface increases, accelerating the wear and damage of the road surface and shortening the service life of the road. When the average volume of goods transportation is large, even greater than the preset reference volume of goods transportation, the pressure on the road surface increases, accelerating the damage of the road surface structure, resulting in diseases such as cracks and deformation of the road surface, affecting the flatness and service life of the road. Therefore, through a detailed analysis of each parameter in the road traffic impact indicators, accurate basis can be provided for traffic planning.

[0041] Specifically, comparing the road traffic impact indicators with the preset road traffic impact indicator thresholds in the evaluation database to obtain a comparison result, the specific comparison process is as follows: If the road traffic impact indicator is less than the preset road traffic impact indicator threshold in the evaluation database, record the comparison result as the first comparison result.

[0042] It should be explained that when the road traffic impact indicator is less than the preset road traffic impact indicator threshold in the evaluation database, it means that the current road traffic condition is in a relatively good state. At this time, the comprehensive impact of various road parameters, such as road length, lane width, road surface friction coefficient, road surface load-bearing capacity, average daily traffic flow, average vehicle driving speed, average volume of goods transportation, etc., on traffic is within an acceptable range, the traffic operation is relatively smooth, the risk of traffic accidents is relatively low, and the road facilities can better meet the current traffic demand.

[0043] If the road traffic impact indicator is greater than or equal to the preset road traffic impact indicator threshold in the evaluation database, record the comparison result as the second comparison result.

[0044] It needs to be explained that when the road traffic impact index is greater than or equal to the road traffic impact index threshold preset in the evaluation database, it indicates that there may be problems or hidden dangers in the current road traffic conditions. This may be due to one or more traffic influencing factors exceeding the normal range, such as excessive traffic flow causing congestion, vehicles driving too fast or too slow affecting traffic efficiency, insufficient road bearing capacity may cause road damage, excessive cargo transportation volume increases the road burden, etc. These situations may increase the probability of traffic accidents.

[0045] When the comparison result is recorded as the second comparison result, it is necessary to issue an early warning prompt for road traffic.

[0046] It needs to be explained that the above-mentioned road traffic early warning reminders can be specifically released to the public through traffic broadcasts, mobile phone applications, electronic display screens and other channels to release information on traffic overloads.

[0047] Specifically, the specific analysis process of the detection site planning index is as follows: The road operation status index and the road traffic impact index are comprehensively analyzed to obtain the inspection site planning index. The specific analysis method is as follows: In the formula, is the detection site planning index, e is a natural constant, is the road operation condition index, is the road traffic impact index, The weight factor corresponding to the road operation condition index unit value preset in the evaluation database, The weight factor corresponding to the unit value of the road traffic impact index preset in the evaluation database.

[0048] It should be explained that the inspection site planning index refers to a numerical index used to evaluate and guide the planning and layout of road inspection sites after comprehensively considering multiple factors such as the road operation condition index and the road traffic impact index. The weight factor corresponding to the preset unit value of the road operation condition index in the evaluation database and the weight factor corresponding to the preset unit value of the road traffic impact index respectively represent the degree of influence of the unit value of the road operation condition index and the unit value of the road traffic impact index on the inspection site planning index. , , .

[0049] It should be noted that a small road operation condition index usually means that the road is in a poor operation state, such as severe traffic congestion and slow vehicle movement. This may lead planners to overly concentrate on setting up detection sites to focus on such problem areas, resulting in an unbalanced layout of detection sites and neglecting the monitoring needs of other areas. A large road traffic impact index indicates that the road is affected by various factors in a more complex or serious manner. This makes it difficult to plan detection sites, as it is hard to accurately determine the location and quantity of sites because numerous factors need to be considered and are intertwined, easily leading to indecision and repeated adjustments in planning decisions. Therefore, a detailed analysis of each parameter in the detection site planning index can clarify which areas have poor traffic conditions, such as traffic congestion and frequent accidents, and which factors have a greater impact on traffic. This helps to determine the key areas that need to be monitored closely, so as to set up detection sites at the locations where they can play the most effective role and improve the monitoring efficiency.

[0050] Furthermore, the matching of the detection site planning index with the detection site coordinates corresponding to each interval of the preset detection site planning index in the evaluation database is as follows: Compare the detection site planning index with the numerical values of each interval of the preset detection site planning index in the evaluation database to determine the specific interval corresponding to the detection site planning index, obtain the interval where the detection site planning index is located, and then obtain the detection site coordinates corresponding to this interval from the evaluation database. In this embodiment, the database may divide the detection site planning index into different intervals such as [0 - 30], (30 - 60], (60 - 90], (90 - 100], etc., and each interval corresponds to different detection site setting strategies and coordinate ranges.

[0051] The obtained coordinates of the overloading detection sites are finally used to plan the layout of the overloading detection sites according to the coordinates of the overloading detection sites.

[0052] In this embodiment, based on the coordinates of the over-limit and over-load detection sites, the traffic conditions in the area are comprehensively evaluated. The factors to be considered include the surrounding road network structure, traffic flow distribution, main freight routes, the locations of sections prone to overloading, etc. For example, if a certain coordinate is at the intersection of multiple freight main roads and the detection site planning index in this area is relatively high, it indicates that this is an ideal location for setting up an over-limit and over-load detection site because a large number of freight vehicles that may be overloaded can be effectively monitored. Based on the coordinates of the over-limit and over-load detection sites, the effective coverage range of each site is determined. Generally speaking, the coverage range of the site should be able to cover the surrounding road areas prone to over-limit and over-load behaviors, and the specific coverage radius can be determined according to factors such as the road grade, traffic flow, and geographical conditions. For example, for highways with large traffic flow and concentrated freight vehicles, the coverage radius may be set relatively large to ensure effective monitoring of a longer section of the road; for roads within the city, due to the dense road network, the coverage radius can be relatively small, but it should ensure that the main freight channels and areas prone to overloading can be covered.

[0053] The above content is only an example and explanation of the structure of the present invention. Those skilled in the art of this technology can make various modifications or supplements to the described specific embodiments or use similar methods for substitution. As long as they do not deviate from the structure of the invention or exceed the scope defined in this specification, they should fall within the protection scope of the present invention.

Claims

1. A layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation, characterized in that, Including: S1. Road network data analysis: Obtain the initial road condition data of the roads in the road network area during the monitoring period, preprocess the initial road condition data of the roads in the road network area during the monitoring period to obtain the road condition data of the roads in the road network area during the monitoring period, and analyze the road condition data of the roads in the road network area during the monitoring period to obtain the road operation status index; S2. Detection impact analysis: Obtain the basic condition data and traffic demand data of each road in the road network area, comprehensively analyze to obtain the road traffic impact index, compare the road traffic impact index with the preset threshold of the road traffic impact index in the evaluation database to obtain the comparison result, and finally give a warning prompt for road traffic according to the comparison result; S3. Detection site layout planning: Comprehensively analyze the road operation status index and the road traffic impact index to obtain the detection site planning index, match the detection site planning index with the detection site coordinates corresponding to each interval of the preset detection site planning index in the evaluation database to obtain the coordinates of the over-limit and over-load detection sites, and finally layout and plan the over-limit and over-load detection sites according to the coordinates of the over-limit and over-load detection sites.

2. The layout planning method of over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 1, characterized in that: The initial road condition data of the roads in the road network area during the monitoring period specifically includes the number of driving vehicles, average vehicle speed, sectional traffic flow, average headway time, and average overloaded tonnage of the roads in the road network area during the monitoring period.

3. The layout planning method of over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 2, characterized in that: Preprocessing the initial road condition data of the roads in the road network area during the monitoring period specifically includes processing the missing values of the initial road condition data of the roads in the road network area during the monitoring period using linear interpolation, detecting and correcting outliers, and spatio-temporal alignment and fusion; The data obtained by preprocessing the initial road condition data of the roads in the road network area during the monitoring period is denoted as the road condition data of the roads in the road network area during the monitoring period; The road condition data of the roads in the road network area during the monitoring period specifically includes the effective statistical quantity of driving vehicles, average vehicle speed calibration value, sectional traffic optimized flow, standardized headway time, and average overloaded tonnage regularization value of the roads in the road network area during the monitoring period.

4. The layout planning method of over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 1, characterized in that: The specific analysis process of the road operation status index is as follows: Comprehensively analyze the effective statistical quantity of driving vehicles, average vehicle speed calibration value, sectional traffic optimized flow, standardized headway time, and average overloaded tonnage regularization value of the roads in the road network area during the monitoring period to obtain the road operation status index.

5. The layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 4, characterized in that: The basic condition data of each road in the road network area specifically includes the road length, lane width, pavement friction coefficient, and average pavement bearing capacity of each road in the road network area.

6. The layout planning method of over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 1, characterized in that: The traffic demand data specifically includes the daily average traffic flow, average vehicle driving speed, and average cargo transportation volume of each road in the historical monitoring period.

7. A layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 1, characterized in that: The specific analysis process of the road traffic impact index is as follows: Comprehensively analyze the road length, lane width, pavement friction coefficient, average pavement bearing capacity of each road in the road network area, the daily average traffic flow, average vehicle driving speed, and average cargo transportation volume of each road in the historical monitoring period to obtain the road traffic impact index.

8. A layout planning method for over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 7, characterized in that: Compare the road traffic impact index with the threshold of the road traffic impact index preset in the evaluation database to obtain a comparison result. The specific comparison process is as follows: If the road traffic impact index is less than the threshold of the road traffic impact index preset in the evaluation database, record the comparison result as the first comparison result; If the road traffic impact index is greater than or equal to the threshold of the road traffic impact index preset in the evaluation database, record the comparison result as the second comparison result; When the comparison result is recorded as the second comparison result, a warning prompt for road traffic needs to be given.

9. The layout planning method of over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 1, characterized in that: The specific analysis process of the detection site planning index is as follows: Comprehensively analyze the road operation condition index and the road traffic impact index to obtain the detection site planning index. The specific analysis method is as follows: In the formula, is the detection site planning index, e is the natural constant, is the road operation condition index, is the road traffic impact index, is the weight factor corresponding to the unit value of the road operation condition index preset in the evaluation database, is the weight factor corresponding to the unit value of the road traffic impact index preset in the evaluation database.

10. The layout planning method of over-limit and over-load detection stations based on fuzzy comprehensive evaluation according to claim 1, characterized in that: Match the detection site planning index with the detection site coordinates corresponding to each interval of the detection site planning index preset in the evaluation database. The specific matching process is as follows: Compare the detection site planning index with the numerical values of each interval of the detection site planning index preset in the evaluation database to determine the specific interval corresponding to the detection site planning index, and obtain the interval where the detection site planning index is located, that is, obtain the detection site coordinates corresponding to this interval from the evaluation database; Obtain the coordinates of the over-limit and over-load detection sites, and finally layout and plan the over-limit and over-load detection sites according to the coordinates of the over-limit and over-load detection sites.

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