Intelligent highway construction evaluation method and system, electronic equipment and storage medium

Abstract

The invention relates to the field of intelligent transportation, and provides an intelligent highway construction evaluation method and system, electronic equipment and a storage medium, and the method comprises the steps: obtaining evaluation elements in an intelligent highway construction process; constructing a hierarchical structure model based on the evaluation elements; constructing an index system based on the hierarchical structure model, comparing indexes of different hierarchies by applying an analytic hierarchy process, and determining a weight matrix of each index in the index system; and based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model, evaluating the construction process of the smart highway. The method and the device are used for solving the defect that the construction stage and the development level are difficult to comprehensively reflect when intelligent expressways are evaluated in the prior art, and the scheme of the invention can systematically reveal the hierarchical relationship among construction elements, objectively quantify the construction level and provide a reliable basis for scientific construction and management of the intelligent expressways.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to an evaluation method and system for intelligent highway construction, electronic equipment, and storage medium. Background Technology

[0002] As an important component of new transportation infrastructure, smart highways have become a key tool for promoting high-quality development of transportation.

[0003] However, current evaluations of smart highways largely rely on qualitative analysis or single-dimensional quantitative methods, lacking a systematic analysis of the structural relationships between construction elements and failing to effectively integrate multi-source data and expert experience. This results in evaluations that fail to comprehensively reflect the construction stage and development level. Therefore, there is an urgent need to develop a method that can systematically identify the structure of construction elements, scientifically determine indicator weights, and achieve comprehensive evaluation under fuzzy environments to support planning decisions, performance evaluations, and development strategy formulation for smart highways. Summary of the Invention

[0004] This invention provides a method and system for evaluating the construction of smart highways, as well as electronic devices and storage media, to address the shortcomings of related technologies in evaluating smart highways, which make it difficult to comprehensively reflect the construction stage and development level. The solution of this application can systematically reveal the hierarchical relationship between construction elements, objectively quantify the construction level, and provide a reliable basis for the scientific construction and management of smart highways.

[0005] This invention provides a method for evaluating the construction of smart highways, comprising: To obtain evaluation elements during the construction of smart highways; A hierarchical structure model is constructed based on the evaluation elements; Based on the hierarchical structure model, an indicator system is constructed, and the analytic hierarchy process is applied to compare the indicators at different levels to determine the weight matrix of each indicator in the indicator system. The construction process of smart highways is evaluated based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

[0006] According to the intelligent highway construction evaluation method provided by the present invention, the step of constructing a hierarchical structure model based on the evaluation elements includes: Based on the adjacency matrix formed by the evaluation elements, the reachability matrix is ​​constructed. After dividing the reachability matrix into regions, a hierarchical division is performed to obtain a triangular matrix of region blocks; The triangular matrix of the region block is reduced to establish a minimum implementation multi-level hierarchical structure matrix; A hierarchical structure model is established based on the minimum implementation of the multi-level hierarchical structure matrix.

[0007] According to the intelligent highway construction evaluation method provided by the present invention, the step of establishing a hierarchical structure model based on the minimum realization multi-level hierarchical structure matrix includes: The evaluation elements are arranged hierarchically in the minimum implementation multi-level hierarchical structure matrix; Add elements with strong connections that were deleted to the same level to obtain directed arcs that evaluate the relationships between elements; The hierarchical structure model is obtained by connecting the minimum realized multi-level hierarchical structure matrix based on the directed arc.

[0008] According to the intelligent highway construction evaluation method provided by this invention, the application of the analytic hierarchy process (AHP) to compare indicators at different levels and determine the weight matrix of each indicator in the indicator system includes: The indicator system is scored using predefined scoring criteria to obtain a judgment matrix; Calculate the row weight of each row of the judgment matrix and normalize the row weights to obtain the weight matrix of each indicator in the indicator system.

[0009] The intelligent highway construction evaluation method provided by the present invention further includes: Calculate the largest eigenvalue of the judgment matrix; Calculate the consistency index value and consistency ratio based on the maximum eigenvalue; If the consistency ratio is greater than the set value, the judgment matrix is ​​determined to be inconsistent.

[0010] According to the intelligent highway construction evaluation method provided by the present invention, the evaluation of the intelligent highway construction process based on the fuzzy evaluation matrix of the weight matrix and the hierarchical structure model includes: A fuzzy set and evaluation set for the construction process of smart highways are established based on the weight matrix. Calculate the membership function of each indicator in the indicator system to form a fuzzy evaluation matrix; The fuzzy evaluation vector is obtained through fuzzy comprehensive operation; The construction process of smart highways is evaluated based on the aforementioned fuzzy evaluation vector.

[0011] This invention also provides a smart highway construction evaluation system, applied to a smart highway construction evaluation method, comprising: The element acquisition module is used to acquire evaluation elements during the construction of smart highways; The model building module is used to build a hierarchical structure model based on the evaluation elements; The matrix construction module is used to construct an indicator system based on the hierarchical structure model, compare indicators at different levels using the analytic hierarchy process, and determine the weight matrix of each indicator in the indicator system. The construction evaluation module is used to evaluate the construction process of smart highways based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

[0012] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement any of the above-described smart highway construction evaluation methods.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described smart highway construction evaluation methods.

[0014] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements any of the above-described smart highway construction evaluation methods.

[0015] The beneficial effects of the intelligent highway construction evaluation method provided by this invention include at least the following: 1. To address the problems of imperfect evaluation methods and strong subjectivity in existing smart highway construction evaluation methods, this paper combines interpretive structural model, analytic hierarchy process and fuzzy comprehensive evaluation method for the first time. This method can systematically reveal the hierarchical structural relationship and interaction between various elements of smart highway construction, and provide a scientific structural basis for subsequent weight calculation and comprehensive evaluation, thereby realizing the systematization and rationalization of the evaluation system. 2. In terms of methodology, a closed-loop connection has been achieved from structure identification → hierarchical expansion → weight assignment → fuzzy discrimination → stage mapping. This technology chain can accurately identify key priorities and bottlenecks in construction, reasonably reflect the influence intensity between elements, and effectively transform qualitative judgments into quantitative stage judgments, thereby enhancing the decision support value of the evaluation conclusions. 3. This method possesses excellent engineering adaptability and promotional value. Under conditions of multi-source uncertain information, it can conduct multi-dimensional integrated analysis of the system structure, element weights, and development stages of smart highway construction. Its comprehensive evaluation results can not only provide decision-making support for government departments in formulating smart highway development plans, but also provide a scientific basis for the phased assessment and performance evaluation of projects under construction, enabling dynamic monitoring and continuous optimization of smart highway construction. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1This is one of the flowcharts of the intelligent highway construction evaluation method provided in the embodiments of the present invention; Figure 2 This is the second flowchart illustrating the intelligent highway construction evaluation method provided in this embodiment of the invention; Figure 3 This is the initial topology diagram of the evaluation elements provided in the embodiments of the present invention; Figure 4 This is a schematic diagram of the hierarchical structure model provided in the embodiments of the present invention; Figure 5 This is a schematic diagram of the indicator system provided in the embodiments of the present invention; Figure 6 This is a schematic diagram of the structure of the intelligent highway construction evaluation system provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the physical structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0019] Figure 1 This is one of the flowcharts of the intelligent highway construction evaluation method provided in the embodiments of the present invention.

[0020] like Figure 1 As shown, this embodiment provides a method for evaluating the construction of smart highways, including: Step 101: Obtain the evaluation elements in the construction process of smart highways; In practical applications, various factors that influence the construction goals in the intelligent highway construction system can be identified, including but not limited to primary system factors such as the technology system, asset system, and organizational system. A system element set can be constructed, and there should be interactive relationships between the elements in the set. Specifically, based on the overall construction project or a phased construction project, various primary factors that influence the construction goals can be identified through expert advice, and a system element set S can be established. There should be interrelationships between the elements in the set.

[0021] Step 102: Construct a hierarchical structure model based on the evaluation elements; This step primarily involves analyzing the interrelationships between system elements based on the Interpretive Structural Model (ISM), establishing a hierarchical structural model reflecting the relationships between elements, constructing a reachability matrix using element association information, and sequentially executing four stages: region division, level division, skeleton matrix extraction, and multi-level hierarchical directed graph drawing, to obtain the hierarchical topological structure of the system elements. Based on this, the key influencing elements at the core layer of the system are identified according to the topological hierarchical relationships.

[0022] Specifically, region partitioning refers to dividing the set of constituent elements S of a system into mutually independent regions with respect to a given binary relation R, that is, partitioning the elements based on the reachability matrix M. The types of associated system elements are considered. During this process, the reachability set, antecedent set, common set, initial set, and termination set of the elements can be calculated, where the system elements... The reachable set is formed by the reachability matrix or directed graph. The set of accessible elements is denoted as Its defining formula is

[0023] System elements The antecedent set is reachable in the reachability matrix or directed graph. The set of system elements is denoted as . Its defining formula is

[0024] System elements The common set is The common part of the reachable set and the antecedent set, i.e., the intersection, is denoted as Its defining formula is

[0025] The initial set of the system element set S is the set of elements in S that only affect other elements and are not affected by other elements, denoted as . Its defining formula is

[0026] The terminal set of a system element set S is the set of elements in S that can reach other elements but cannot be reached by other elements, denoted as . .

[0027]

[0028] In practical applications, there are two methods to determine whether a system element set S is divisible: 1) Determine whether the system... The elements and their 1) Whether the elements are independent of each other; 2) Determine the system The elements and their Are the elements independent of each other?

[0029] based on The rules for dividing the area are: 1) In Choose any two elements , ,if ,but , and , The elements in the equation belong to the same region. If this result holds for all u and v, then the region is indivisible. 2) If ,but , and , If the elements in the system do not belong to the same region, the system element set S can be divided into at least two relatively independent regions. Similarly, based on... The rules for dividing regions only need to be determined. Whether it is an empty set or not is sufficient. and for Any two elements in it.

[0030] The result of the regional division can be denoted as: , Let be the set of elements in the k-th relatively independent region. The reachability matrix after region partitioning is a block diagonal matrix. .

[0031] Hierarchical partitioning refers to finding the highest-level element (terminating element) of the entire system's element set, removing it, and then finding the highest-level element of the remaining element set (forming a partial graph), and so on, until the lowest-level element set is determined. Specifically, it can be shown in the following formula (6), let Then there is

[0032] in and It is a set The common set and reachable set of the submatrices formed by the elements in the matrix are obtained. If l represents the maximum number of levels, then the result of the level partitioning can be written as... After hierarchical partitioning, the reachability matrix becomes a triangular matrix of region blocks, denoted as... .

[0033] Skeleton matrix extraction may include the following steps: Examine the strongly connected elements at each level and construct the reachability matrix. Reduced matrix ; Remove The cross-level binary relationships between elements that already have adjacency binary relationships are used to obtain a new simplified matrix. ; Further removal The binary relation reached by itself, i.e., subtracting the identity matrix, will Change all the "1"s on the main diagonal to "0"s to obtain the simplified skeleton matrix containing the number of binary relations. .

[0034] Drawing a multi-level directed graph involves the following steps: The system's constituent elements are arranged hierarchically from top to bottom, divided into regions; Add the deleted elements that have a strong connection with a certain element to the same level, and the directed arc representing their relationship; according to The adjacent binary relations shown are connected by directed arcs between levels to form a directed graph. Based on this, a hierarchical structure model of the intelligent highway construction system can be established.

[0035] Step 103: Based on the hierarchical structure model, construct an indicator system, apply the analytic hierarchy process to compare indicators at different levels, and determine the weight matrix of each indicator in the indicator system. In practice, predefined scoring criteria can be applied to score the indicator system and obtain a judgment matrix; Calculate the row weight of each row of the judgment matrix and normalize the row weights to obtain the weight matrix of each indicator in the indicator system.

[0036] Specifically, the secondary content and specific construction links covered by the core primary influencing factors identified in step 2 can be refined to form a hierarchical indicator system covering primary, secondary and even tertiary levels.

[0037] Then, a scoring standard can be defined between the influencing indicators, and a five-level or nine-level scoring table can be selected as appropriate.

[0038] Based on the given scoring criteria, experts assign scores, and a judgment matrix A is constructed that satisfies the following formula:

[0039] i and j are element indices, and i, j = 1, 2, …, n, where n is the number of elements to be compared, i.e., the number of indicators. Should meet , , .

[0040] For A, we first need to calculate the row weight of each row of the judgment matrix according to formula (8). The row weights of each row have inconsistent measurement ranges due to different scoring situations, meaning the sum of the weights is not equal to 1. To ensure that the sum of the weights is equal to 1, it is necessary to adjust the weights according to formula (9). Normalization is then performed. Finally, the weight vector of the judgment matrix is ​​obtained. That is, the weights of n indicators in evaluating the construction content of smart highways.

[0041]

[0042]

[0043] In practical applications, a consistency check can also be performed on A to ensure the correctness of the indicator weight calculation. First, the maximum eigenvalue of A is calculated according to formula (10). Then, substitute it into formula (11) to calculate the consistency index value of the feature matrix. Finally, substitute it into formula (12) to calculate the consistency ratio. .

[0044]

[0045]

[0046]

[0047] As the average consistency index, when When this condition is met, it indicates that the consistency of the judgment matrix A is within the acceptable error range, and A can be used to calculate the weight vector. If... If the matrix A is inconsistent, it needs to be corrected to ensure its consistency.

[0048] Step 104: Evaluate the construction process of the smart highway based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

[0049] In practical applications, the indicator elements that affect the construction effect of smart highways in step 3 can be used as factor set U, and the evaluation level of the system construction status can be used as evaluation set V.

[0050]

[0051] m is the number of factors affecting the evaluation object. The i-th factor influencing the evaluation object typically exhibits varying degrees of ambiguity. k represents the number of evaluation results. This represents the i-th evaluation result. The elements of the evaluation set can be different construction stages or numbers.

[0052] Based on expert evaluation or sample data, determine China's various indicators The membership values ​​are used to form a fuzzy comprehensive evaluation matrix. The matrix elements reflect the fuzzy membership degree of each evaluation index at different levels.

[0053]

[0054] The index weight vector obtained by AHP in the above steps Introduced into the FCE model, the comprehensive membership vector of the system at each evaluation level is obtained through weighted fuzzy computation. .

[0055]

[0056] For the fuzzy comprehensive evaluation synthesis operator, general matrix multiplication can be used to achieve the comprehensive mapping between weights at different levels and evaluation results.

[0057] The comprehensive membership vector connecting all evaluation indicators For B, based on the numerical score vector corresponding to each evaluation level. The fuzzy comprehensive score of the system is calculated according to formula (17). The score reflects the degree of perfection of the construction of smart highway.

[0058] The intelligent highway construction evaluation method provided in this embodiment has the following beneficial effects: 1. To address the problems of imperfect evaluation methods and strong subjectivity in existing smart highway construction evaluation methods, this paper combines interpretive structural model, analytic hierarchy process and fuzzy comprehensive evaluation method for the first time. This method can systematically reveal the hierarchical structural relationship and interaction between various elements of smart highway construction, and provide a scientific structural basis for subsequent weight calculation and comprehensive evaluation, thereby realizing the systematization and rationalization of the evaluation system. 2. In terms of methodology, a closed-loop connection has been achieved from structure identification → hierarchical expansion → weight assignment → fuzzy discrimination → stage mapping. This technology chain can accurately identify key priorities and bottlenecks in construction, reasonably reflect the influence intensity between elements, and effectively transform qualitative judgments into quantitative stage judgments, thereby enhancing the decision support value of the evaluation conclusions. 3. This method possesses excellent engineering adaptability and promotional value. Under conditions of multi-source uncertain information, it can conduct multi-dimensional integrated analysis of the system structure, element weights, and development stages of smart highway construction. Its comprehensive evaluation results can not only provide decision-making support for government departments in formulating smart highway development plans, but also provide a scientific basis for the phased assessment and performance evaluation of projects under construction, enabling dynamic monitoring and continuous optimization of smart highway construction.

[0059] The following is a detailed description of the intelligent highway construction evaluation method provided by the present invention, using a specific embodiment.

[0060] Figure 2 This is the second flowchart of the intelligent highway construction evaluation method provided in this embodiment of the invention.

[0061] like Figure 2 As shown, the method provided in this embodiment includes the following steps: Step 1: Feature identification and system construction; Step 2: Structural modeling and hierarchical division; Step 3: Hierarchical expansion and AHP weight calculation; Step 4: Fuzzy comprehensive evaluation and stage identification.

[0062] Specifically, in step 1, to cover the six dimensions of smart highway construction—"technology, assets, organization, economy, regulation, and society"—eight primary influencing factors can be identified based on expert opinions: ① Construction content; ② Technical system and standards; ③ Infrastructure and equipment; ④ Data platform and information technology capabilities; ⑤ Investment and economic feasibility; ⑥ Operation and maintenance and organizational capabilities; ⑦ Safety, emergency response, and regulations; ⑧ Environment / society and collaboration. These eight factors together constitute the factor set. .

[0063] In step 2, a set of binary relations for system elements can be generated based on the set of elements constructed in step 1, as shown below: ={( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , ),( , )} A directed graph representing their relationships is as follows: Figure 3 As shown, the corresponding adjacency matrix P is as follows:

[0064] From the directed graph and adjacency matrix, it can be seen that there are no strong connections. Therefore, a reachability matrix M needs to be constructed, where P and M are both 0-1 matrices and conform to Boolean algebra rules. After calculation... Therefore, the maximum number of transmissions is 2.

[0065]

[0066] For the given and Figure 3 The corresponding reachability matrix is ​​used to divide the region, and any element can be listed. The reachable set, antecedent set, common set, and initial set are shown in Table 1. Because Therefore, the system element set S region is indivisible.

[0067] Table 1 Elements The reachable set, the antecedent set, the common set, and the initial set

[0068] The highest-level element in the system's element set is the terminal element of the system. The basic approach is to first identify the highest-level element in the entire system's element set, remove it, then find the highest-level element in the remaining element set (forming a partial diagram), and so on, until the lowest-level element set is determined. The hierarchical partitioning operation for the system's constituent element set S can be recorded in Table 2. The result of the hierarchical partitioning is as follows: Based on the hierarchical division results, M can be transformed into a triangular matrix M(L) of regional blocks. The skeleton matrix extraction is achieved by reducing M(L) to establish the minimum realization multi-level hierarchical structure matrix H of M. The entire extraction process consists of two steps: the first step is to remove the cross-level binary relationships between elements that already have adjacency binary relationships in M(L), resulting in a further simplified matrix. The second step is to remove The binary relation reached within the system itself, i.e., subtracting the identity matrix I, ultimately yields the skeleton matrix H. Finally, based on H, a multi-level hierarchical directed graph D(H) is drawn, thus establishing a hierarchical structural model of the system elements, such as... Figure 4 As shown.

[0069] Table 2 Derivation and Calculation Table of Hierarchical Explanation Structure Model

[0070]

[0071]

[0072] In step 3, based on expert opinions and relevant industry reports, the secondary content and specific construction stages can be refined, resulting in the scenario layer X of smart highway construction content: basic business scenarios, special scenarios, and innovative business scenarios. The various sub-construction contents of scenario layer X constitute the construction indicator layer Y. The complete evaluation system structure is as follows: Figure 5 As shown.

[0073] according to Figure 5 The evaluation system architecture can be used to construct a scenario layer: basic business scenarios. Innovative application scenarios Specialized scenarios Smart Cloud Platform The various sub-indicators of the scenario layer constitute the construction indicator layer Y: digital infrastructure. Early warning of ramp merging / diverting zones Driving safety guidance in foggy areas Accompanying travel information services De-icing and snow removal system Intelligent asset management and intelligent operation and maintenance system for electromechanical equipment Smart toll stations Smart Service Area Smart tunnel Smart Bridge All-weather traffic operation status perception for special road sections Active traffic flow control Vehicle-Road Coordination System Infrastructure as a Service (IaaS) Data and Platform Layer (PaaS DaaS) Smart Application Layer (SaaS) .

[0074] To calculate the impact of each indicator on the construction of smart highways, it is necessary to define a scoring standard between the influencing indicators, which is divided into a 9-level scoring table. The scoring standard between indicator i and indicator j is shown in Table 3.

[0075] Table 3 Evaluation Criteria Among Influencing Indicators

[0076] For the evaluation indicators describing the impact of smart highway construction, multiple experts scored the indicators, and then the relative weights were calculated using the analytic hierarchy process (AHP). The judgment matrices of the multiple experts were integrated according to formula (17) to obtain a judgment matrix representing the expert scoring results.

[0077]

[0078] in, This is the integrated judgment matrix. for The element in the i-th row and j-th position of the matrix, z represents the number of experts; here, z = 45. Let z be the judgment matrix of the z-th expert. for The element in the i-th row and j-th position of the matrix.

[0079] The scene layer can be obtained through calculation. , , Integrated Judgment Matrix for,

[0080] Construction indicator layer , , , , , Integration judgment matrix for,

[0081] Construction indicator layer , , , Integration judgment matrix for,

[0082] Construction indicator layer , , Integration judgment matrix for,

[0083] Construction indicator layer , , Integration judgment matrix for,

[0084] The weights of the integrated judgment matrix are calculated according to formulas (8) and (9), and the weights are calculated according to formula (10). Then, substitute it into formula (11) to calculate the CI of the feature matrix, and finally substitute it into formula (12) to calculate the CR. The values ​​of the average consistency index RI are shown in Table 4.

[0085] Table 4. Average Consistency Index Values

[0086] for There are 4 indicators to be compared, and taking n = 4, we can calculate... , , .Pick ,calculate Therefore, it can be judged Passed the consistency check. For , , , The following steps can be used to calculate: , , , ; , , , ; , , , ; , , , . , , , All passed the consistency test. The standardized weights for each scenario layer and construction indicator layer are shown in Table 5 below: Table 5 Weight Table of Criterion Layer and Indicator Layer

[0087] In step 4, when performing fuzzy comprehensive evaluation and stage identification, the indicator elements affecting the construction effect of smart highways in step 3 can be used as factor set U, and the evaluation level of the system construction status can be used as evaluation set V. In this embodiment, m is the total number of construction indicator layers; k is the number of smart highway development level layers. Let the score vector be a set of four evaluation results. The larger the number, the more complete the construction. 1 corresponds to Information technology as the foundation, 2 corresponds to Networked collaboration, 3 corresponds to Intelligent services, 4 Ecological integration. Based on sample data from expert evaluation and scoring, let the membership degree of the i-th factor in factor set U to the j-th evaluation in evaluation set V be . Then the membership vector of the i-th factor to all k evaluation results is... By integrating expert scoring results, a fuzzy comprehensive evaluation matrix is ​​formed. The matrix elements reflect the fuzzy membership degree of each evaluation index at different levels.

[0088] For the matrix of index layer Y1-Y6 ,

[0089] For the matrix of index layer Y7-Y10 ,

[0090] For the matrix of index layer Y11-Y13 :

[0091] For the matrix of index layer Y14-Y16 :

[0092] The index weight vector obtained from AHP in step 3 Introduced into FCE, the comprehensive membership vector of the system at each evaluation level is obtained through weighted fuzzy computation.

[0093] Membership degree of indicator layer Y1-Y6 The calculation process is as follows:

[0094] Membership degree of indicator layers Y7-Y10 The calculation process is as follows:

[0095] Membership degree of indicator layers Y11-Y13 The calculation process is as follows:

[0096] Membership degree of indicator layer Y14-Y16 The calculation process is as follows:

[0097] The fuzzy evaluation matrix R of scene layer X is:

[0098] The calculation process for the comprehensive fuzzy evaluation result B of the system is as follows:

[0099] Based on the score vector The fuzzy comprehensive score F of the calculation system is:

[0100] The fuzzy comprehensive score F of the system, obtained by weighted calculation, is 3.014, which corresponds to the following result in the smart highway construction phase: basically completed. The intelligent service phase is currently underway. Developing in the direction of ecological integration.

[0101] The intelligent highway construction evaluation system provided by this invention is described below. The intelligent highway construction evaluation system described below can be referred to in correspondence with the intelligent highway construction evaluation method described above.

[0102] Figure 6 This is a schematic diagram of the structure of the intelligent highway construction evaluation system provided in an embodiment of the present invention.

[0103] like Figure 6 As shown, the intelligent highway construction evaluation system provided in this embodiment includes: The element acquisition module 601 is used to acquire evaluation elements during the construction of smart highways; Model 602 is used to construct a hierarchical structure model based on the evaluation elements; The matrix construction module 603 is used to construct an indicator system based on the hierarchical structure model, compare indicators at different levels using the analytic hierarchy process, and determine the weight matrix of each indicator in the indicator system. The construction evaluation module 604 is used to evaluate the construction process of smart highways based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

[0104] The specific implementation method of the intelligent highway construction evaluation system provided in this embodiment can be implemented with reference to the above embodiment, and will not be repeated here.

[0105] Figure 7 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 7 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740, wherein the processor 710, the communication interface 720, and the memory 730 communicate with each other via the communication bus 740. The processor 710 can call logical instructions in the memory 730 to execute a smart highway construction evaluation method, which includes: To obtain evaluation elements during the construction of smart highways; A hierarchical structure model is constructed based on the evaluation elements; Based on the hierarchical structure model, an indicator system is constructed, and the analytic hierarchy process is applied to compare the indicators at different levels to determine the weight matrix of each indicator in the indicator system. The construction process of smart highways is evaluated based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

[0106] Furthermore, the logical instructions in the aforementioned memory 730 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0107] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer is able to execute the intelligent highway construction evaluation method provided by the above methods, the method including: To obtain evaluation elements during the construction of smart highways; A hierarchical structure model is constructed based on the evaluation elements; Based on the hierarchical structure model, an indicator system is constructed, and the analytic hierarchy process is applied to compare the indicators at different levels to determine the weight matrix of each indicator in the indicator system. The construction process of smart highways is evaluated based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

[0108] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to perform the intelligent highway construction evaluation method provided by the methods described above, the method comprising: To obtain evaluation elements during the construction of smart highways; A hierarchical structure model is constructed based on the evaluation elements; Based on the hierarchical structure model, an indicator system is constructed, and the analytic hierarchy process is applied to compare the indicators at different levels to determine the weight matrix of each indicator in the indicator system. The construction process of smart highways is evaluated based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

[0109] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0110] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An evaluation method for the construction of smart highways, characterized in that, include: To obtain evaluation elements during the construction of smart highways; A hierarchical structure model is constructed based on the evaluation elements; Based on the hierarchical structure model, an indicator system is constructed, and the analytic hierarchy process is applied to compare the indicators at different levels to determine the weight matrix of each indicator in the indicator system. The construction process of smart highways is evaluated based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

2. The evaluation method for smart highway construction according to claim 1, characterized in that, The construction of the hierarchical structure model based on the evaluation elements includes: Based on the adjacency matrix formed by the evaluation elements, the reachability matrix is ​​constructed. After dividing the reachability matrix into regions, a hierarchical division is performed to obtain a triangular matrix of region blocks; The triangular matrix of the region block is reduced to establish a minimum implementation multi-level hierarchical structure matrix; A hierarchical structure model is established based on the minimum implementation of the multi-level hierarchical structure matrix.

3. The evaluation method for smart highway construction according to claim 2, characterized in that, The establishment of a hierarchical structure model based on the minimum realization multi-level hierarchical structure matrix includes: The evaluation elements are arranged hierarchically in the minimum implementation multi-level hierarchical structure matrix; Add elements with strong connections that were deleted to the same level to obtain directed arcs that evaluate the relationships between elements; The hierarchical structure model is obtained by connecting the minimum realized multi-level hierarchical structure matrix based on the directed arc.

4. The evaluation method for smart highway construction according to claim 1, characterized in that, The application of the Analytic Hierarchy Process (AHP) compares indicators at different levels to determine the weight matrix of each indicator in the indicator system, including: The indicator system is scored using predefined scoring criteria to obtain a judgment matrix; Calculate the row weight of each row of the judgment matrix and normalize the row weights to obtain the weight matrix of each indicator in the indicator system.

5. The evaluation method for smart highway construction according to claim 4, characterized in that, Also includes: Calculate the largest eigenvalue of the judgment matrix; Calculate the consistency index value and consistency ratio based on the maximum eigenvalue; If the consistency ratio is greater than the set value, the judgment matrix is ​​determined to be inconsistent.

6. The evaluation method for smart highway construction according to claim 1, characterized in that, The fuzzy evaluation matrix based on the weight matrix and the hierarchical structure model is used to evaluate the construction process of smart highways, including: A fuzzy set and evaluation set for the construction process of smart highways are established based on the weight matrix. Calculate the membership function of each indicator in the indicator system to form a fuzzy evaluation matrix; The fuzzy evaluation vector is obtained through fuzzy comprehensive operation; The construction process of smart highways is evaluated based on the aforementioned fuzzy evaluation vector.

7. A smart highway construction evaluation system, applied to the smart highway construction evaluation method according to any one of claims 1-6, characterized in that, include: The element acquisition module is used to acquire evaluation elements during the construction of smart highways; Model construction model, used to construct a hierarchical structure model based on the evaluation elements; The matrix construction module is used to construct an indicator system based on the hierarchical structure model, apply the analytic hierarchy process to compare indicators at different levels, and determine the weight matrix of each indicator in the indicator system. The construction evaluation module is used to evaluate the construction process of smart highways based on the weight matrix and the fuzzy evaluation matrix of the hierarchical structure model.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the smart highway construction evaluation method as described in any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the smart highway construction evaluation method as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the smart highway construction evaluation method as described in any one of claims 1-6.

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