CN117455122A - Road surface state evaluation method, device, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides a pavement state evaluation method, a pavement state evaluation device, electronic equipment and a storage medium, and relates to the technical field of highway maintenance, wherein the pavement state evaluation method comprises the following steps: acquiring evaluation data of each target dimension of a road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension; and acquiring a road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension, wherein the target weight value corresponding to each target dimension is acquired based on an analytic hierarchy process, an entropy value process and a minimum distance function. The road surface state evaluation method, the device, the electronic equipment and the storage medium provided by the invention can better adapt to the change of the external environment state, can more accurately reflect the actual state of the road surface, have more excellent flexibility, objectivity, interpretability and adaptability, and can provide more accurate reference basis for road maintenance.
Description
Technical Field
The invention relates to the technical field of highway maintenance, in particular to a pavement state evaluation method, a pavement state evaluation device, electronic equipment and a storage medium.
Background
The road surface state generally refers to the condition of the road surface. The road surface state is evaluated, the development degree of road surface diseases can be obtained, and an important reference basis is provided for road maintenance, so that the safety, the comfort and the sustainability of vehicle running are ensured.
The conventional road surface state evaluation method in the related art has insufficient adaptability to the change of the external environment state, and is difficult to evaluate the road surface state accurately and comprehensively.
Therefore, how to evaluate the road surface more accurately and more comprehensively is a technical problem to be solved in the field.
Disclosure of Invention
The invention provides a pavement state evaluation method, a pavement state evaluation device, electronic equipment and a storage medium, which are used for solving the defect that the pavement state is difficult to evaluate accurately and comprehensively in the prior art and realizing more accurate and more comprehensive pavement state evaluation.
The invention provides a pavement state evaluation method, which comprises the following steps:
acquiring evaluation data of each target dimension of a road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension;
Acquiring a road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension;
the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
According to the road surface state evaluation method provided by the invention, the target weight value corresponding to each target dimension is obtained based on the following steps:
calculating to obtain a subjective weight value corresponding to each target dimension based on an analytic hierarchy process, and calculating to obtain an objective weight value corresponding to each target dimension based on an entropy method;
and based on a minimum distance function, carrying out combined solution on the subjective weight value and the objective weight value corresponding to each target dimension to obtain a combined weight value corresponding to each target dimension, and taking the combined weight value as a target weight value corresponding to each target dimension.
According to the road surface state evaluation method provided by the invention, the road surface state evaluation result of the road section to be evaluated is obtained based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension, and the road surface state evaluation result comprises the following steps:
Acquiring an original evaluation value corresponding to each target dimension based on the evaluation data of each target dimension;
updating the target weight value corresponding to each target dimension based on the original evaluation value corresponding to each target dimension, and acquiring the target weight value corresponding to each updated target dimension;
calculating the product of the evaluation value corresponding to each target dimension and the updated target weight value corresponding to each target dimension as an original evaluation value corresponding to each target dimension;
and calculating the sum of original evaluation values corresponding to the target dimensions to serve as the road surface state evaluation value of the road section to be evaluated, and determining the road surface state evaluation value of the road section to be evaluated as the road surface state evaluation result of the road section to be evaluated.
According to the road surface state evaluation method provided by the invention, the updating of the target weight value corresponding to each target dimension based on the original evaluation value corresponding to each target dimension, and the obtaining of the updated target weight value corresponding to each target dimension comprise the following steps:
and updating the target weight value corresponding to each target dimension by utilizing a variable weight balance function based on the original evaluation value corresponding to each target dimension, and acquiring the updated target weight value corresponding to each target dimension.
According to the road surface state evaluation method provided by the invention, after calculating the sum of the original evaluation values corresponding to the target dimensions as the road surface state evaluation value of the road section to be evaluated, the method further comprises:
and determining the road surface state grade of the road section to be evaluated based on the road surface state evaluation value of the road section to be evaluated, and determining the road surface state grade of the road section to be evaluated as the road surface state evaluation result of the road section to be evaluated.
According to the road surface state evaluation method provided by the invention, after the road surface state grade of the road section to be evaluated is determined based on the road surface state evaluation value of the road section to be evaluated, the method further comprises the following steps:
and predicting the development of the road surface diseases of the road section to be evaluated based on the road surface state grade of the road section to be evaluated, and obtaining the prediction result of the development of the road surface diseases of the road section to be evaluated.
The invention also provides a road surface state evaluation device, comprising:
the data acquisition module is used for acquiring evaluation data of each target dimension of the road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension;
The state evaluation module is used for acquiring a road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension;
the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
The invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the road surface state assessment method as described above when executing the program.
The present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a road surface state assessment method as described in any of the above.
The invention also provides a computer program product comprising a computer program which, when executed by a processor, implements a method of road surface condition assessment as described in any of the above.
According to the road surface state evaluation method, the device, the electronic equipment and the storage medium, the road surface state evaluation result of the road section to be evaluated is obtained based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension, the weight corresponding to each target dimension is obtained based on the analytic hierarchy process, the entropy method and the minimum distance function, the change of the external environment state can be better adapted, the actual state of the road surface can be reflected more accurately, and the road surface state evaluation method, the device and the storage medium have more excellent flexibility, objectivity, interpretability and adaptability and can provide more accurate reference basis for road maintenance.
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In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a road surface state evaluation method according to the present invention;
FIG. 2 is a second flow chart of the road surface condition assessment method according to the present invention;
fig. 3 is a schematic view of the construction of the road surface condition evaluating device provided by the present invention;
fig. 4 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the invention, it should be noted that, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
In the description of the present application, the terms "first," "second," and the like are used for distinguishing between similar objects and not for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged, as appropriate, such that embodiments of the present application may be implemented in sequences other than those illustrated or described herein, and that the objects identified by "first," "second," etc. are generally of a type and not limited to the number of objects, e.g., the first object may be one or more. In addition, in the description of the present application, "and/or" means at least one of the connected objects, and the character "/", generally means a relationship in which the front and rear associated objects are one kind of "or".
Pavement damage refers to various damages and defects occurring in the pavement structure. The number and severity of road surface imperfections in a road segment directly affect the road surface condition of the road segment. Therefore, the road surface condition evaluation of the road segment may be equivalent to the evaluation of the development of the road surface failure in the above road segment.
In the related art, a constant weight evaluation method is generally used for road surface state evaluation. However, the constant weight evaluation method has insufficient adaptability to the change of the external environment state, so that the conventional road surface state evaluation method is difficult to evaluate the road surface state accurately and comprehensively.
In this regard, the present invention provides a road surface condition evaluation method. The road surface state evaluation method provided by the invention adopts a variable weight solving mode to evaluate the road surface state, can better adapt to the change of the external environment state, can more accurately reflect the actual state of the road surface, has more excellent flexibility, objectivity, interpretability and adaptability, and can provide more accurate reference basis for road maintenance.
Fig. 1 is a schematic flow chart of a road surface state evaluation method provided by the invention. The road surface condition evaluation method of the present invention is described below with reference to fig. 1. As shown in fig. 1, the method includes: step 101, acquiring evaluation data of each target dimension of a road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension.
The execution subject of the embodiment of the present invention is a road surface state evaluation device.
Specifically, the road section to be evaluated is an evaluation object of the road surface state evaluation method provided by the invention. Based on the road surface state evaluation method provided by the invention, the road surface state of the road section to be evaluated can be evaluated, and further the road surface state evaluation result of the road section to be evaluated is obtained.
It is understood that the road segment to be evaluated may be determined based on actual requirements. In the embodiment of the invention, the road section to be evaluated is not particularly limited.
According to the method and the device, the evaluation data of each target dimension of the pavement to be evaluated can be obtained through a data query mode. For example, by querying a construction file of a road section to be evaluated, evaluation data of a construction condition dimension, a road surface material dimension and a road surface condition dimension of the road section to be evaluated can be obtained, by querying weather data, evaluation data of a weather dimension of the road section to be evaluated can be obtained, and by querying a traffic history of the road section to be evaluated, evaluation data of a traffic load dimension and a maintenance frequency dimension of the road section to be evaluated can be obtained.
The construction condition dimension can be used for describing various environments and technical conditions faced when road construction is carried out; the evaluation data of the construction condition dimension can comprise topography data, soil condition data and the like of a construction site;
Pavement material dimensions may be used to describe materials used by a pavement of a roadway; the evaluation data of the dimensions of the pavement material may include the type, performance, etc. of the material used by the pavement;
the roadbed condition dimension may be used to describe characteristics of the road roadbed; the evaluation data of the roadbed condition dimension can comprise soil type, geological type and the like of the roadbed;
the meteorological dimension can be used for describing meteorological conditions of the environment where the road is located; the evaluation data of the meteorological dimension can comprise the climate type, the ambient temperature, the ambient humidity, the wind speed, the wind direction and the like of the environment where the road is located;
the traffic load dimension can be used for describing the force exerted on road structures and materials by vehicles running on the road, and the evaluation data of the traffic load dimension can comprise the type of the vehicles on the road, the traffic volume, the vehicle load, the driving speed, the driving acceleration, the braking force and the like;
the maintenance frequency dimension may be used to describe the maintenance frequency of the road; the evaluation data of the maintenance frequency dimension may include a maintenance frequency of the road.
FIG. 2 is a second flow chart of the road surface condition evaluation method according to the present invention. As shown in fig. 2, the target dimension in the embodiment of the present invention is determined based on a priori knowledge and/or actual situation before acquiring the evaluation data of the target dimension of the road segment to be evaluated.
102, acquiring a road surface state evaluation result of a road section to be evaluated based on a target weight value corresponding to each target dimension and evaluation data of each target dimension;
the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
Specifically, after the evaluation data of each target dimension is obtained, the road surface state evaluation result of the road section to be evaluated can be obtained through numerical calculation, mathematical statistics and other modes based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension.
It should be noted that, in the embodiment of the present invention, the target weight value corresponding to each target dimension is calculated by a numerical calculation method based on an analytic hierarchy process, an entropy method, a minimum distance function and a variable weight equalization function.
Among these, analytic hierarchy process (Analytic Hierarchy Process, AHP) is a multi-criteria decision analysis method. The basic idea of the analytic hierarchy process is to decompose the complex decision problem layer by layer into a plurality of layers, so as to more clearly understand the structure of the problem, and compare and weigh step by step.
The Entropy Method (Entropy Method) is a multi-criterion decision Method for determining index weights, the core idea of the Entropy Method is derived from Entropy concepts in information theory, and the weight of each index is determined by calculating the Entropy value of each index, so that objective ordering and weighing of the indexes are realized. The entropy method has the advantages of being capable of better processing the correlation among indexes and objectivity of weight determination, and particularly has certain advantages in multi-index and multi-scheme decision problems. Meanwhile, the entropy method is relatively simple and visual, easy to understand and operate, and suitable for decision-making problems of a certain scale.
The minimum distance function is typically used to measure the similarity or difference between two sets, distributions, or data points. In mathematics and statistics, the minimum distance function has a variety of forms, and common examples include euclidean distance, manhattan distance, chebyshev distance, and the like. In practical applications, minimum distance functions are often used in the fields of cluster analysis, pattern recognition, data mining, etc., to classify or group objects according to their similarity.
As an alternative embodiment, the target weight value corresponding to each target dimension is obtained based on the following steps: and calculating to obtain a subjective weight value corresponding to each target dimension based on an analytic hierarchy process, and calculating to obtain an objective weight value corresponding to each target dimension based on an entropy value process.
Specifically, in the embodiment of the invention, hierarchical expression can be performed on each target dimension through an analytic hierarchy process, and the subjective weight value of each target dimension is obtained.
In the embodiment of the invention, the road surface state evaluation level can be used as a target level, and each target dimension is used as a middle layer to construct a hierarchical structure model. Wherein, B is used in the embodiment of the invention 1 Representing construction condition dimension, use B 2 Representing traffic load dimension, use B 3 Representing dimensions of pavement materials, with B 4 Representing meteorological dimensions, use B 5 Represents the dimension of the roadbed condition, and B is used 6 Representing the maintenance frequency dimension.
In the embodiment of the invention, the evaluation standard of each target dimension can be determined based on the 1-9 scale table. The 1-9 scale is shown in Table 1.
Table 1 1-9 Scale
It should be noted that a 1-9 scale is a commonly used scale method for measuring and evaluating the level of attitudes, favorites, satisfaction, etc. for a particular attribute or thing. The 1-9 scale table is typically composed of a continuous scale of 1 to 9, where 1 indicates the lowest level or extreme disagreement and 9 indicates the highest level or extreme agreement.
According to the embodiment of the invention, the scale value between any two target dimensions in each target dimension can be determined based on priori knowledge and/or actual conditions, and then the judgment matrix corresponding to each target dimension can be constructed based on the scale value between any two target dimensions in each target dimension. The judgment matrix corresponding to the target dimension is shown in table 2.
Table 2 judgment matrix corresponding to each target dimension
The scale values in table 2 are scale values of row data with respect to column data. For example: construction Condition dimension B as shown in Table 2 1 Dimension B with traffic load 2 The scale value between the two is 3, and the traffic load dimension B 2 Dimension B with construction condition 1 The scale value between the two is 1/3, representing the dimension B of the construction condition 1 Specific traffic load dimension B 2 Slightly important; construction Condition dimension B 1 Dimension B with pavement material 3 The scale value between is 1, and the dimension B of the pavement material 3 Dimension B with construction condition 1 The scale value between the two is also 1, which represents the dimension B of the pavement material 3 Dimension B with construction condition 1 The importance is the same.
After the judgment matrix corresponding to each target dimension is constructed, the maximum feature root corresponding to each target dimension and the weight vector corresponding to the maximum feature root can be calculated based on the judgment matrix corresponding to each target dimension.
The embodiment of the invention calculates and obtains the maximum characteristic root corresponding to each target dimension=6.559, the weight value for each target dimension is as shown in table 3.
Table 3 schematic table of weight vector values for each target dimension
Obtaining the maximum characteristic root corresponding to each target dimensionThereafter, the maximum feature root corresponding to each target dimension can be +>And (5) performing consistency test.
By the maximum characteristic root corresponding to each target dimensionConsistency verification is performed to obtain，/>Thus, the maximum feature root corresponding to each target dimension can be determined >And passing the consistency check. Wherein (1)>Representing the number of dimensions of each object, in the present embodiment +.>；/>(Consistency Index) represents a consistency index; />(Consistency Ratio) represents a consistency ratio; />(Random Index) represents a Random uniformity Index, +.>=1.24 is predefined.
Maximum feature root corresponding to each target dimensionUnder the condition of consistency verification, the weight vector value corresponding to each target dimension can be determined as the subjective weight value corresponding to each target dimension.
According to the embodiment of the invention, the objective weight value of each target dimension can be obtained through an entropy method.
According to the embodiment of the invention, the entropy value corresponding to each target dimension in different application scenes can be determined based on priori knowledge and/or actual conditions, and then the entropy value matrix corresponding to each target dimension can be constructed based on the entropy value corresponding to each target dimension in different application scenes. The entropy matrix corresponding to each target dimension is shown in table 4.
TABLE 4 entropy matrix for each target dimension
Normalizing the entropy value corresponding to each target dimension in different application scenes to obtain the normalized entropy value corresponding to each target dimension in different application scenes, wherein the specific calculation formula is as follows:
Wherein,representing the first +.in the entropy matrix corresponding to each target dimension>Line->Element values of columns; />Representation->Is a normalized value of (2); />Representing the minimum value in entropy values corresponding to each target dimension in the same application scene; />And representing the maximum value in the entropy values corresponding to the target dimensions under the same application scene.
After the normalized entropy corresponding to each target dimension in different application scenes is obtained, a normalized entropy matrix corresponding to each target dimension can be constructed based on the normalized entropy corresponding to each target dimension in different application scenes. The normalized entropy matrix for each target dimension is shown in table 5.
Table 5 normalized entropy matrix for each target dimension
After the normalized entropy matrix corresponding to each target dimension is obtained, the entropy weight value corresponding to each target dimension can be calculated according to the following formula:
wherein,indicate->Entropy weight values corresponding to the target dimensions; />Indicate->Comprehensive entropy values of the target dimensions in each application scene; />Indicate->Index value specific gravity corresponding to each target dimension and is +.>In the case of (a) the number of the cells,。
the entropy weight value corresponding to each target dimension is shown in table 6.
TABLE 6 corresponding entropy weight value for each target dimension
After the entropy weight value corresponding to each target dimension is obtained, the entropy weight value corresponding to each target dimension can be determined as an objective weight value corresponding to each target dimension.
Based on the minimum distance function, the subjective weight value and the objective weight value corresponding to each target dimension are combined and solved, and the combined weight value corresponding to each target dimension is obtained and used as the target weight value corresponding to each target dimension.
Specifically, after the subjective weight value and the objective weight value corresponding to each target dimension are obtained, the combined weight value corresponding to each target dimension can be calculated based on the minimum distance function, and a specific calculation formula is as follows:
wherein,indicate->The combination weight values corresponding to the target dimensions; />Indicate->Subjective weight values corresponding to the target dimensions; />Indicate->Objective weight values corresponding to the respective target dimensions; />And->Representing the distribution coefficient, satisfying。
Can be calculated based on the above formula；/>，/>The method comprises the steps of carrying out a first treatment on the surface of the Or,，/>。
optionally, in the embodiment of the present invention, subjective weight values corresponding to target dimensions are more focused, so that，。
Accordingly, the combination weight value corresponding to each target dimension calculated based on the above formula is shown in table 7.
TABLE 7 corresponding combined weight value for each target dimension
Obtaining a combined weight value corresponding to each target dimensionThen, the combined weight value corresponding to each target dimension can be determined as the target weight value +_corresponding to each target dimension>。
As an optional embodiment, obtaining a road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension includes: and acquiring an original evaluation value corresponding to each target dimension based on the evaluation data of each target dimension.
Specifically, after the evaluation data of each target dimension is obtained, the section where the evaluation data of each target dimension is located can be determined by means of condition judgment, deep learning technology, mathematical statistics and the like.
After the interval in which the evaluation data of each target dimension is located is obtained, the original evaluation value corresponding to each target dimension can be obtained through numerical calculation, mathematical statistics, deep learning technology and other modes based on the interval in which the evaluation data of each target dimension is located.
It should be noted that, in the embodiment of the present invention, the interval division of the evaluation data of each target dimension is shown in table 8.
TABLE 8 interval partitioning of evaluation data for each target dimension
Wherein, condition 1 in table 8 includes: the quality of the material is checked to be qualified; condition 2 includes: the surface layer of the ground engineering has no defects of blast ash, cracks, hollows and the like; condition 3 includes: the strength and density of each layer of the ground and the firmness of the combination of the upper layer and the lower layer are checked to be qualified; condition 4 includes: grade, thickness, elevation and flatness are checked to be qualified; condition 5 includes: the size of gaps between the plates and the blocks is checked to be qualified; condition 6 includes: the defects of the surface layer of the ground engineering, such as blast, crack, hollowing and the like are less than a first preset value (a small number of defects exist in the surface layer of the ground engineering); condition 7 includes: the defects of the surface layer of the ground engineering, such as blast, crack, hollowing and the like are less than a second preset value (the surface layer of the ground engineering has a certain number of defects).
The target axle times in table 8 include cumulative standard axle times per lane over the design year.
Updating the target weight value corresponding to each target dimension based on the original evaluation value corresponding to each target dimension, and acquiring the updated target weight value corresponding to each target dimension.
Specifically, after the original evaluation value corresponding to each target dimension is obtained, the weight corresponding to each target dimension may be updated in a numerical calculation manner based on the original evaluation value corresponding to each target dimension, so as to obtain the target weight value corresponding to each target dimension after updating.
As an optional embodiment, updating the target weight value corresponding to each target dimension based on the original evaluation value corresponding to each target dimension, and obtaining the updated target weight value corresponding to each target dimension includes: and updating the target weight value corresponding to each target dimension by utilizing a variable weight balance function based on the original evaluation value corresponding to each target dimension, and acquiring the updated target weight value corresponding to each target dimension.
It should be noted that the variable weight equalization function (Variable Weighting Balance Function) is generally used to perform adjustment and equalization of index weights in multi-index decision. The weight-variable balance function can flexibly adjust the weight of the index according to the preference and the demand of a decision maker, so that the decision result better accords with the actual situation and the decision target. The variable weight equalization function has the advantage that the variable weight equalization function can flexibly adapt to different decision environments and requirements of decision makers, so that the decision making process is more objective and accurate. The variable weight equalization function can also fully consider the relation among indexes and the importance of weights, and avoids the limitation of the traditional fixed weight method.
The variable weight equalization function in the embodiment of the invention can be expressed by the following formula:
Wherein,represent the firstjState variable weight vector of each target dimension, +.>Continuous and conductive in the interval (0, 1);c、c 1 、c 2 is a weight adjustment parameter and should satisfy 0<c<c 1 <c 2 <1；αRepresenting a penalty level;βrepresenting an excitation level; (0,μ]representing an extremely strong penalty interval; (μ,λ]Representing a strong penalty interval; (lambda of the term,α]representing an initial punishment interval; (α,β]Representing a qualified interval; (β,1]Representing an excitation interval; />Represent the firstjOriginal evaluation values corresponding to the respective target dimensions.
Index state valuexThe correspondence between the interval partitions and the original evaluation values is shown in table 9.
Table 9 correspondence table between interval division of index state value x and original evaluation value
The target weight value corresponding to each target dimension after updating can be calculated based on the following formula:
wherein,W(X) Representing a variable weight vector;representing Chang Quan vectors;S(X) Representing a state-change weight vector.
Dividing the variable weight function into intervals based on table 9, and taking、/>、/>、/>、/>、、/>、/>。
The variable weight equalization function may be expressed by the following formula:
calculating to obtain the firstjState variable weight vector of each target dimensionThereafter, it can be based on the firstjState variable weight vector of individual target dimensions +.>Determine the updated firstjWeight value of individual target dimension +.>。/>
And calculating the product of the original evaluation value corresponding to each target dimension and the updated target weight value corresponding to each target dimension as the original evaluation value corresponding to each target dimension.
Specifically, after the weight value of each target dimension after updating is obtained, the original evaluation value corresponding to each target dimension can be obtained through calculation according to the following formula:
wherein,represent the firstjTarget evaluation values corresponding to the respective target dimensions.
And calculating the sum of the original evaluation values corresponding to the target dimensions to serve as a road surface state evaluation value of the road surface to be evaluated, and determining the road surface state evaluation value of the road surface to be evaluated as a road surface state evaluation result of the road surface to be evaluated.
Specifically, after the original evaluation value corresponding to each target dimension is obtained, the road surface state evaluation value of the road section to be evaluated can be calculated by the following formula：
Obtaining road surface state evaluation value of road section to be evaluatedAfter that, the road surface state evaluation value of the road section to be evaluated can be +.>And determining the road surface state evaluation result of the road section to be evaluated.
As an alternative embodiment, after calculating the sum of the target evaluation values corresponding to the respective target dimensions as the road surface state evaluation value of the road segment to be evaluated, the method further includes: and determining the road surface state grade of the road section to be evaluated based on the road surface state evaluation value of the road section to be evaluated, and determining the road surface state grade of the road section to be evaluated as the road surface state evaluation result of the road section to be evaluated.
Specifically, a road surface state evaluation value of a road section to be evaluated is obtainedThereafter, it can also be based on the evaluationRoad surface state evaluation value of road segment->And determining the road surface state grade of the road section to be evaluated.
Optionally, atIn the case of (2), it is possible to determine that the road surface condition level of the road section to be evaluated is first order, at 0.6 </o>In the case of 0.8 or less, it is possible to determine that the road surface condition level of the road section to be evaluated is two-level, 0.4 </o>In the case of 0.6 or less, it is possible to determine the road surface condition level of the road section to be evaluated as three levels, at 0.2 </o>In the case of 0.4 or less, it is possible to determine that the road surface condition of the road section to be evaluated is rated four, at +.>In the case of 0.2 or less, it is possible to determine that the road surface condition grade of the road section to be evaluated is five. Wherein, as the road surface state level increases, the road surface state gradually becomes worse.
According to the road surface state evaluation method and the road surface state evaluation device, the road surface state evaluation result of the road section to be evaluated is obtained based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension, the weight corresponding to each target dimension is obtained based on the analytic hierarchy process, the entropy method and the minimum distance function, the change of the external environment state can be better adapted, the actual state of the road surface can be reflected more accurately, the flexibility, the objectivity, the interpretability and the adaptability are superior, and a more accurate reference basis can be provided for road maintenance.
In order to better illustrate the superiority of the road surface state evaluation method provided by the invention, the road surface state evaluation result obtained based on the road surface state evaluation method provided by the invention is compared with the road surface state evaluation result obtained based on the constant weight evaluation method. The comparison of the road surface state evaluation results obtained based on the road surface state evaluation method provided by the invention with the road surface state evaluation results obtained based on the constant weight evaluation method is shown in table 10.
Table 10 comparison table of road surface condition evaluation results obtained based on the road surface condition evaluation method provided by the present invention and road surface condition evaluation results obtained based on the constant weight evaluation method
As shown in Table 10, under construction condition B 1 General, traffic load dimension B 2 Large, climatic conditions dimension B 4 Under the condition of bad weather, the road surface state evaluation grade obtained by adopting a single Chang Quan evaluation method is three, the road surface state evaluation value is 0.551 and 0.538, the road surface state evaluation value obtained by adopting a weight combination is 0.545 and is between two single Chang Quan evaluation methods, namely, the comprehensive evaluation obtained by combining a subjective evaluation method and an objective evaluation method is carried out, at the moment, the development degree of two road surface diseases in 6 evaluation indexes is high, the development degree of the two road surface diseases is three, and at the moment, the evaluation is that the medium development degree is obviously too optimistic, and the development of preventive maintenance is not facilitated; the road surface state evaluation result after the weight change adjustment shows the influence of the actual environmental condition on the development degree of the road surface diseases, the road surface state evaluation grade obtained after the adjustment is four, and the like, and the road surface state evaluation value is 0.288, so that the reliability and the rationality of the road surface state evaluation result are obviously improved, and the road surface state evaluation method has positive significance for preventive maintenance of the road.
As an alternative embodiment, after determining the road surface state grade of the road segment to be evaluated based on the road surface state evaluation value of the road segment to be evaluated, the method further includes: and predicting the development of the road surface damage of the road section to be evaluated based on the road surface state grade of the road section to be evaluated, and obtaining the prediction result of the development of the road surface damage of the road section to be evaluated.
It is understood that the higher the road surface condition level of the road section to be evaluated, the less likely road surface damage occurs in the road section to be evaluated.
Therefore, in the embodiment of the invention, after the road surface state grade of the road section to be evaluated is obtained, the development of the road surface damage of the road section to be evaluated can be predicted based on the road surface state grade of the road section to be evaluated, and the prediction result of the development of the road surface damage of the road section to be evaluated can be obtained.
Specifically, in the case where the road surface state grade of the road section to be evaluated is first order, it can be determined that the road surface damage development prediction result of the road section to be evaluated includes a low probability of occurrence of road surface damage; under the condition that the road surface state grade of the road section to be evaluated is two-level, the road surface disease development prediction result of the road section to be evaluated can be determined to have lower probability of occurrence of road surface disease; under the condition that the road surface state grade of the road section to be evaluated is three-level, the road surface disease development prediction result of the road section to be evaluated can be determined to have moderate probability of occurrence of the road surface disease; in the case where the road surface state level of the road section to be evaluated is four, it can be determined that the road surface damage development prediction result of the road section to be evaluated includes a high probability of occurrence of the road surface damage, and in the case where the road surface state level of the road section to be evaluated is five, it can be determined that the road surface damage development prediction result of the road section to be evaluated includes a high probability of occurrence of the road surface damage.
Fig. 3 is a schematic diagram of the structure of the road surface state evaluation device provided by the invention. The road surface state evaluation device provided by the present invention will be described below with reference to fig. 3, and the road surface state evaluation device described below and the road surface state evaluation method provided by the present invention described above may be referred to correspondingly to each other. As shown in fig. 3, a data acquisition module 301 and a state evaluation module 302.
The data acquisition module 301 is configured to acquire evaluation data of each target dimension of a road segment to be evaluated, where each target dimension includes a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension, and a maintenance frequency dimension;
the state evaluation module 302 is configured to obtain a road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension;
the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
Specifically, the data acquisition module 301 and the state evaluation module 302 are electrically connected.
According to the road surface state evaluation device, the road surface state evaluation result of the road section to be evaluated is obtained based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension, the weight corresponding to each target dimension is obtained based on the analytic hierarchy process, the entropy method and the minimum distance function, the change of the external environment state can be better adapted, the actual state of the road surface can be reflected more accurately, and the road surface state evaluation device has more excellent flexibility, objectivity, interpretability and adaptability and can provide more accurate reference basis for road maintenance.
Fig. 4 illustrates a physical schematic diagram of an electronic device, as shown in fig. 4, which may include: processor 410, communication interface (Communications Interface) 420, memory 430 and communication bus 440, wherein processor 410, communication interface 420 and memory 430 communicate with each other via communication bus 440. Processor 410 may invoke logic instructions in memory 430 to perform a road surface condition assessment method comprising: acquiring evaluation data of each target dimension of a road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension; acquiring a road surface state evaluation result of a road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension; the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
Further, the logic instructions in the memory 430 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of performing the road surface state assessment method provided by the above methods, the method comprising: acquiring evaluation data of each target dimension of a road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension; acquiring a road surface state evaluation result of a road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension; the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
In yet another aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the road surface state assessment method provided by the above methods, the method comprising: acquiring evaluation data of each target dimension of a road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension; acquiring a road surface state evaluation result of a road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension; the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A road surface condition evaluation method, characterized by comprising:
acquiring evaluation data of each target dimension of a road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension;
acquiring a road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension;
the target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
2. The road surface state evaluation method according to claim 1, wherein the target weight value corresponding to each of the target dimensions is obtained based on the steps of:
calculating to obtain a subjective weight value corresponding to each target dimension based on an analytic hierarchy process, and calculating to obtain an objective weight value corresponding to each target dimension based on an entropy method;
and based on a minimum distance function, carrying out combined solution on the subjective weight value and the objective weight value corresponding to each target dimension to obtain a combined weight value corresponding to each target dimension, and taking the combined weight value as a target weight value corresponding to each target dimension.
3. The road surface state evaluation method according to claim 1, wherein the obtaining the road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension includes:
acquiring an original evaluation value corresponding to each target dimension based on the evaluation data of each target dimension;
updating the target weight value corresponding to each target dimension based on the original evaluation value corresponding to each target dimension, and acquiring the target weight value corresponding to each updated target dimension;
Calculating the product of the original evaluation value corresponding to each target dimension and the updated target weight value corresponding to each target dimension as a target evaluation value corresponding to each target dimension;
and calculating the sum of target evaluation values corresponding to the target dimensions to serve as the road surface state evaluation value of the road section to be evaluated, and determining the road surface state evaluation value of the road section to be evaluated as the road surface state evaluation result of the road section to be evaluated.
4. The method of claim 3, wherein updating the target weight value corresponding to each target dimension based on the original evaluation value corresponding to each target dimension, and obtaining the updated target weight value corresponding to each target dimension, comprises:
and updating the target weight value corresponding to each target dimension by utilizing a variable weight balance function based on the original evaluation value corresponding to each target dimension, and acquiring the updated target weight value corresponding to each target dimension.
5. The road surface state evaluation method according to claim 3 or 4, characterized in that after the calculation of the sum of the target evaluation values corresponding to the respective target dimensions as the road surface state evaluation value of the road section to be evaluated, the method further comprises:
And determining the road surface state grade of the road section to be evaluated based on the road surface state evaluation value of the road section to be evaluated, and determining the road surface state grade of the road section to be evaluated as the road surface state evaluation result of the road section to be evaluated.
6. The road surface state evaluation method according to claim 5, wherein after the road surface state grade of the road surface to be evaluated is determined based on the road surface state evaluation value of the road surface to be evaluated, the method further comprises:
and predicting the development of the road surface diseases of the road section to be evaluated based on the road surface state grade of the road section to be evaluated, and obtaining the prediction result of the development of the road surface diseases of the road section to be evaluated.
7. A road surface condition evaluation device, characterized by comprising:
the data acquisition module is used for acquiring evaluation data of each target dimension of the road section to be evaluated, wherein each target dimension comprises a construction condition dimension, a traffic load dimension, a pavement material dimension, a meteorological dimension, a roadbed condition dimension and a maintenance frequency dimension;
the state evaluation module is used for acquiring a road surface state evaluation result of the road section to be evaluated based on the target weight value corresponding to each target dimension and the evaluation data of each target dimension;
The target weight value corresponding to each target dimension is obtained based on an analytic hierarchy process, an entropy value process and a minimum distance function.
8. The pavement condition assessment apparatus of claim 7, wherein the condition assessment module is specifically configured to: acquiring an original evaluation value corresponding to each target dimension based on the evaluation data of each target dimension; updating the target weight value corresponding to each target dimension based on the original evaluation value corresponding to each target dimension, and acquiring the target weight value corresponding to each updated target dimension; calculating the product of the original evaluation value corresponding to each target dimension and the updated target weight value corresponding to each target dimension as a target evaluation value corresponding to each target dimension; and calculating the sum of target evaluation values corresponding to the target dimensions to serve as the road surface state evaluation value of the road section to be evaluated, and determining the road surface state evaluation value of the road section to be evaluated as the road surface state evaluation result of the road section to be evaluated.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the road surface condition assessment method of any one of claims 1 to 6 when the program is executed by the processor.
10. A non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the road surface state assessment method according to any one of claims 1 to 6.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107180292A (en) * | 2016-03-11 | 2017-09-19 | 国家电网公司 | Multidimensional power network intelligent development level evaluation method |
| CN109697515A (en) * | 2018-12-28 | 2019-04-30 | 深圳高速工程顾问有限公司 | Pavement of road management method, device, storage medium and computer equipment |
| CN110728437A (en) * | 2019-09-26 | 2020-01-24 | 华南师范大学 | Quality evaluation method and system for open data |
| CN110777625A (en) * | 2019-11-13 | 2020-02-11 | 招商局重庆交通科研设计院有限公司 | Clustering dimension reduction evaluation method for service state of asphalt pavement |
| CN111680863A (en) * | 2020-04-26 | 2020-09-18 | 南京南数数据运筹科学研究院有限公司 | Network environment safety condition evaluation method based on analytic hierarchy process |
| CN113030450A (en) * | 2021-03-15 | 2021-06-25 | 海南省交通工程检测中心 | Asphalt pavement full-period performance monitoring and evaluating method and system |
| CN114037220A (en) * | 2021-10-19 | 2022-02-11 | 华北电力大学（保定） | Distribution network reliability grade division standard and evaluation method |
| WO2022135473A1 (en) * | 2020-12-22 | 2022-06-30 | 国网上海市电力公司 | Method for evaluating acceptance capability of electric vehicle in urban distribution network |
| CN115049315A (en) * | 2022-07-29 | 2022-09-13 | 广东电网有限责任公司 | Power utilization safety risk assessment method, device, equipment and storage medium |
| CN115423318A (en) * | 2022-08-31 | 2022-12-02 | 中孚信息股份有限公司 | Method and system for evaluating health degree of computer equipment based on combination weight |
| CN116029598A (en) * | 2023-01-10 | 2023-04-28 | 城云科技（中国）有限公司 | Method, device and application for evaluating disaster-adaptive toughness of urban flood disasters |
| CN117252331A (en) * | 2023-09-12 | 2023-12-19 | 浙江省水利河口研究院(浙江省海洋规划设计研究院) | Water resource load assessment method for water source area |
-
2023
- 2023-12-22 CN CN202311776881.1A patent/CN117455122B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107180292A (en) * | 2016-03-11 | 2017-09-19 | 国家电网公司 | Multidimensional power network intelligent development level evaluation method |
| CN109697515A (en) * | 2018-12-28 | 2019-04-30 | 深圳高速工程顾问有限公司 | Pavement of road management method, device, storage medium and computer equipment |
| CN110728437A (en) * | 2019-09-26 | 2020-01-24 | 华南师范大学 | Quality evaluation method and system for open data |
| CN110777625A (en) * | 2019-11-13 | 2020-02-11 | 招商局重庆交通科研设计院有限公司 | Clustering dimension reduction evaluation method for service state of asphalt pavement |
| CN111680863A (en) * | 2020-04-26 | 2020-09-18 | 南京南数数据运筹科学研究院有限公司 | Network environment safety condition evaluation method based on analytic hierarchy process |
| WO2022135473A1 (en) * | 2020-12-22 | 2022-06-30 | 国网上海市电力公司 | Method for evaluating acceptance capability of electric vehicle in urban distribution network |
| CN113030450A (en) * | 2021-03-15 | 2021-06-25 | 海南省交通工程检测中心 | Asphalt pavement full-period performance monitoring and evaluating method and system |
| CN114037220A (en) * | 2021-10-19 | 2022-02-11 | 华北电力大学（保定） | Distribution network reliability grade division standard and evaluation method |
| CN115049315A (en) * | 2022-07-29 | 2022-09-13 | 广东电网有限责任公司 | Power utilization safety risk assessment method, device, equipment and storage medium |
| CN115423318A (en) * | 2022-08-31 | 2022-12-02 | 中孚信息股份有限公司 | Method and system for evaluating health degree of computer equipment based on combination weight |
| CN116029598A (en) * | 2023-01-10 | 2023-04-28 | 城云科技（中国）有限公司 | Method, device and application for evaluating disaster-adaptive toughness of urban flood disasters |
| CN117252331A (en) * | 2023-09-12 | 2023-12-19 | 浙江省水利河口研究院(浙江省海洋规划设计研究院) | Water resource load assessment method for water source area |
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