Big data-based road construction and maintenance scheme decision method, system, device and medium

Abstract

The present application relates to the technical field of highway maintenance, and discloses a road construction and maintenance scheme decision method, system, device and medium based on big data, which comprises the following steps: obtaining the evaluation unit data of each unit road; classifying the unit roads according to the basic attributes of the evaluation unit data, and determining the road construction and maintenance schemes corresponding to different basic attributes of the unit roads; determining the comprehensive investment index CII corresponding to the road construction and maintenance schemes based on the evaluation unit data; and selecting the road construction and maintenance scheme with the CII reaching a preset threshold as the target scheme. By taking the evaluation unit data of each unit road as data support and determining the target scheme according to the CII value of the corresponding scheme after classification according to the basic attributes, the objectivity and data accuracy of the target execution scheme are improved, and the economic benefits of road construction and maintenance are further improved.

Description

Technical Field

[0001] This invention relates to the field of road maintenance technology, and in particular to a method, system, equipment and medium for road construction and maintenance scheme decision-making based on big data. Background Technology

[0002] During road use, damage is inevitable over time, and road performance gradually declines. If repairs and maintenance are not carried out promptly, the degree of damage will gradually worsen, reducing the road's usability and lifespan, and in severe cases, even affecting traffic safety. For roads with minor damage that still meet usability requirements, only routine maintenance is needed. For roads with severe damage that no longer meet usability requirements, major and medium-scale repair and maintenance projects are necessary to ensure the road remains in good service. Generally, implementing an economical and reasonable original road construction plan and subsequent major and medium-scale repair and maintenance plan can ensure good road performance. A reasonable road construction and maintenance plan can delay the major and medium-scale repair cycle, reduce long-term maintenance costs, and achieve good economic and social benefits.

[0003] However, existing road construction and maintenance decision-making methods based on big data typically involve technical personnel developing plans based on current industry standards and years of experience. On the one hand, while industry standards serve as a basis for development, my country's vast territory and significant regional differences mean that these standards are not universally applicable, leaving considerable room for human intervention and resulting in a high degree of subjectivity in the actual implementation. On the other hand, the difficulty in developing economically sound and reasonable construction and maintenance plans based on the experience of technical personnel, coupled with variations in experience and road conditions, makes it challenging to formulate such plans.

[0004] In summary, existing road construction and maintenance plans, which are based on industry standards and the work experience of technical personnel, are highly subjective and have low economic benefits. Summary of the Invention

[0005] The main objective of this invention is to propose a road construction and maintenance scheme decision-making method, system, equipment, and medium based on big data, aiming to solve the problems of strong subjectivity and low economic efficiency in existing road construction and maintenance schemes.

[0006] To achieve the above objectives, the present invention provides a road construction and maintenance scheme decision-making method based on big data, which specifically includes the following steps:

[0007] Obtain the assessment unit data for each road unit;

[0008] Based on the basic attributes of the assessment unit data, the unit roads are classified, and road construction and maintenance schemes corresponding to different basic attributes of the unit roads are determined.

[0009] Based on the data from the assessment unit, the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan is determined;

[0010] The road construction and maintenance scheme that reaches the preset threshold of CII is selected as the target scheme.

[0011] Preferably, the step of determining the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan based on the evaluation unit data includes:

[0012] Based on the preset calculation rules, the road condition deterioration index (CAI) and the investment benefit index (IBI) are determined according to the condition index scores of the assessment unit data and the construction and maintenance costs of the road assessment unit.

[0013] Based on the road condition degradation index (CAI) and the investment benefit index (IBI), the comprehensive investment index (CII) corresponding to the road construction and maintenance plan is determined.

[0014] Preferably, the step of determining the Road Condition Degradation Index (CAI) and the Investment Benefit Index (IBI) based on preset calculation rules, according to the condition index scores of the assessment unit data and the construction and maintenance costs of the road assessment unit, includes:

[0015] Based on the preset road condition calculation rules, the road condition index CAI corresponding to the road construction and maintenance scheme is calculated according to the road condition index RCI of the condition index score and the year difference of the road assessment unit.

[0016] Based on the preset benefit calculation rules, the investment benefit index (IBI) of each road unit in the road construction and maintenance plan is calculated according to the construction and maintenance costs of the road assessment unit and the year difference of the road assessment unit.

[0017] Preferably, the step of determining the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan based on the Road Condition Degradation Index (CAI) and the Investment Benefit Index (IBI) includes:

[0018] Based on the preset investment index calculation rules, preset weights are added to the road condition deterioration index (CAI) and the investment benefit index (IBI) for calculation to determine the comprehensive investment index (CII) corresponding to the road maintenance plan.

[0019] Preferably, before the step of obtaining the evaluation unit data for each road unit, the method further includes:

[0020] Obtain the detection data for each unit road in a preset year;

[0021] The test data corresponding to the years in which the test data shows preset data anomalies are removed to determine the evaluation unit data for index calculation of each road unit.

[0022] Preferably, the step of classifying the unit roads according to the basic attributes of the evaluation unit data and determining the road construction and maintenance schemes corresponding to different basic attributes of the unit roads includes:

[0023] Select the classification criteria for classifying the roads in the assessment unit from the basic attributes of the assessment unit data;

[0024] Based on the classification criteria, the unit roads are classified, and the corresponding classification results are determined.

[0025] Based on the classification results of the unit roads according to the classification criteria, the road construction and maintenance plan corresponding to the classification criteria is determined.

[0026] Preferably, the step of selecting the road construction and maintenance scheme that reaches the preset threshold of CII as the target scheme includes:

[0027] The CII corresponding to the road construction and maintenance plan of each unit road is calculated according to the preset calculation formula to obtain the comprehensive investment index (CII) of the overall road corresponding to the unit road.

[0028] The overall road comprehensive investment index (CII) is sorted according to a preset order, and the comprehensive investment index (CII) that meets the preset standard is selected.

[0029] The road construction and maintenance plan corresponding to the CII that meets the preset standard is taken as the target plan.

[0030] Furthermore, to achieve the above objectives, embodiments of the present invention also propose a scheme decision-making system, the scheme decision-making system comprising:

[0031] The data acquisition module is used to acquire the evaluation unit data for each road unit;

[0032] The attribute classification module is used to classify the unit roads according to the basic attributes of the evaluation unit data, and determine the road construction and maintenance schemes corresponding to different basic attributes of the unit roads.

[0033] The index calculation module is used to determine the comprehensive investment index (CII) corresponding to the road construction and maintenance plan based on the data from the evaluation unit.

[0034] The scheme selection module is used to select the road construction and maintenance scheme that reaches the preset threshold of CII as the target scheme.

[0035] Preferably, the data acquisition module is used for:

[0036] Obtain the detection data for each unit road in a preset year;

[0037] The test data corresponding to the years in which the test data shows preset data anomalies are removed to determine the evaluation unit data for index calculation of each road unit.

[0038] Preferably, the attribute classification module is used for:

[0039] Select the classification criteria for classifying the roads in the assessment unit from the basic attributes of the assessment unit data;

[0040] Based on the classification criteria, the unit roads are classified, and the corresponding classification results are determined.

[0041] Based on the classification results of the unit roads according to the classification criteria, the road construction and maintenance plan corresponding to the classification criteria is determined.

[0042] Preferably, the exponent calculation module is used for:

[0043] Based on the preset calculation rules, the road condition deterioration index (CAI) and the investment benefit index (IBI) are determined according to the condition index scores of the assessment unit data and the construction and maintenance costs of the road assessment unit.

[0044] Based on the road condition degradation index (CAI) and the investment benefit index (IBI), the comprehensive investment index (CII) corresponding to the road construction and maintenance plan is determined.

[0045] Preferably, the exponent calculation module is used for:

[0046] Based on the preset road condition calculation rules, the road condition index CAI corresponding to the road construction and maintenance scheme is calculated according to the road condition index RCI of the condition index score and the year difference of the road assessment unit.

[0047] Based on the preset benefit calculation rules, the investment benefit index (IBI) of each road unit in the road construction and maintenance plan is calculated according to the construction and maintenance costs of the road assessment unit and the year difference of the road assessment unit.

[0048] Preferably, the exponent calculation module is used for:

[0049] Based on the preset investment index calculation rules, preset weights are added to the road condition deterioration index (CAI) and the investment benefit index (IBI) for calculation to determine the comprehensive investment index (CII) corresponding to the road maintenance plan.

[0050] Preferably, the scheme selection module is used for:

[0051] The CII corresponding to the road construction and maintenance plan of each unit road is calculated according to the preset calculation formula to obtain the comprehensive investment index (CII) of the overall road corresponding to the unit road.

[0052] The overall road comprehensive investment index (CII) is sorted according to a preset order, and the comprehensive investment index (CII) that meets the preset standard is selected.

[0053] The road construction and maintenance plan corresponding to the CII that meets the preset standard is taken as the target plan.

[0054] Furthermore, to achieve the above objectives, this embodiment of the invention also proposes an apparatus, which includes a memory, a processor, and a road construction and maintenance scheme decision program stored in the memory and executable on the processor. The road construction and maintenance scheme decision program is executed by the processor to implement the steps of the road construction and maintenance scheme decision method based on big data as described above.

[0055] In addition, to achieve the above objectives, the present invention also provides a medium, which is a computer-readable storage medium, on which a road construction and maintenance scheme decision program is stored. When the road construction and maintenance scheme decision program is executed by a processor, it implements the steps of the road construction and maintenance scheme decision method based on big data as described above.

[0056] This invention proposes a road construction and maintenance scheme decision-making method, system, equipment, and medium based on big data. The steps of the road construction and maintenance scheme decision-making method based on big data include: acquiring assessment unit data for each road unit; classifying the road units according to the basic attributes of the assessment unit data, and determining the road construction and maintenance schemes corresponding to different basic attributes of the road units; determining the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance scheme based on the assessment unit data; and selecting the road construction and maintenance scheme that reaches a preset threshold as the target scheme.

[0057] Compared to existing technologies that rely on industry standards and technical personnel's experience to determine road construction and maintenance targets, this invention uses historical road network construction and maintenance big data as a foundation for evaluating each road unit. Based on this data, it determines the Comprehensive Investment Index (CII) for each road unit, thereby identifying road construction and maintenance plans for different basic attributes. Finally, the road construction and maintenance plan that reaches a preset threshold based on the CII is used as the target plan, such as the optimal construction or major / medium maintenance plan. This big data-driven approach to road construction and maintenance plan decision-making makes the target plan more realistic, improves the objectivity and data accuracy of road construction and maintenance plans, and further enhances the economic benefits of road construction and maintenance. Attached Figure Description

[0058] Figure 1 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the implementation scheme of the road construction and maintenance scheme decision-making method based on big data of the present invention;

[0059] Figure 2 This is a flowchart illustrating the first embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention;

[0060] Figure 3 This is a flowchart illustrating the second embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention;

[0061] Figure 4 This is a schematic diagram of a sub-process of step S31 in the second embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention;

[0062] Figure 5 This is a flowchart illustrating the third embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention;

[0063] Figure 6 This is a schematic diagram of the specific process of step S100 in the fourth embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention;

[0064] Figure 7 This is a flowchart illustrating the fourth embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention;

[0065] Figure 8 This is a schematic diagram of the functional modules of the road construction and maintenance scheme decision-making system based on big data, as described in this invention.

[0066] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0067] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0068] Specifically, refer to Figure 1 , Figure 1 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the implementation scheme of the road construction and maintenance scheme decision-making method based on big data of the present invention.

[0069] like Figure 1As shown, the device may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen or an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0070] like Figure 1 As shown, the memory 1005, as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a function control program. The operating system is a program that manages and controls the hardware and software resources of the device, supporting the operation of the function control program and other software or programs. The network communication module manages and controls the network interface 1002. The user interface 1003 is mainly used for data communication with clients. The network interface 1004 is mainly used for establishing a communication connection with a server. The processor 1001 can be used to call the function control program stored in the memory 1005 and execute the operations in the various embodiments of the digital card function control method described below.

[0071] Those skilled in the art will understand that Figure 1 The device structure shown does not constitute a limitation on the device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0072] To better understand the above technical solutions, exemplary embodiments of this disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of this disclosure to those skilled in the art.

[0073] Based on, but not limited to, the above-described terminal device architecture, this invention proposes an embodiment of a road construction and maintenance scheme decision-making method based on big data.

[0074] Specifically, refer to Figure 2 , Figure 2This is a flowchart illustrating the first embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention. The road construction and maintenance scheme decision-making method based on big data includes:

[0075] Step S10: Obtain the evaluation unit data for each road unit;

[0076] Step S20: Classify the unit roads according to the basic attributes of the evaluation unit data, and determine the road construction and maintenance schemes corresponding to different basic attributes of the unit roads.

[0077] Step S30: Based on the data from the evaluation unit, determine the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan;

[0078] Step S40: Select the road construction and maintenance scheme that has reached the preset threshold of CII as the target scheme.

[0079] This application embodiment is based on a road construction and maintenance scheme decision-making method using big data. The invention uses the road assessment unit data of each road unit in the historical big data of road network construction and maintenance as the basic support, and determines the comprehensive investment index of the road assessment unit based on the condition index score corresponding to the road assessment data of each road unit, thereby determining the optimal construction and major and medium maintenance target schemes among the schemes corresponding to roads with different basic attributes.

[0080] The following will provide a detailed explanation of each step:

[0081] Step S10: Obtain the evaluation unit data for each road unit;

[0082] In one specific embodiment, the user can select the route range to be analyzed through the interactive interface of the solution decision system. The road evaluation units within the route range have their corresponding basic attributes and condition index scores. In this embodiment, the road evaluation unit is specifically defined as one kilometer of road. Each road evaluation unit has its corresponding historical construction, major and medium maintenance data, and basic attribute data.

[0083] Specifically, the aforementioned historical construction and major / medium maintenance data may include the construction year of the road assessment unit, the condition index score corresponding to the construction year, the year of major / medium maintenance, and the road condition index score corresponding to the year of major / medium maintenance; the year in which the road assessment unit was tested for indicators, and the road condition index score corresponding to the year of testing; the original construction plan and cost of each unit road, the major / medium maintenance plan and cost over the years, and the daily maintenance cost over the years, etc.

[0084] It should be specifically explained that the aforementioned road condition indices may include, but are not limited to, the Pavement Maintenance Quality Index (PQI), Pavement Surlace Condition Index (PCI), Pavement Riding Quality Index (RQI), Pavement Rutting Depth Index (RDI), Pavement Skidding Resistance Index (SRI), Pavement Bumping Index (PBI), Pavement Surface Wearing Index (PWI), and Pavement Structure Strength Index (PSSI).

[0085] Furthermore, the basic attribute data of each road assessment unit within the aforementioned route range may include: administrative division, climate type, topography, technical grade, design speed, and other basic attributes. The basic attribute data of the aforementioned road assessment units is fixed and unchanging, meaning that the basic attribute data of the road assessment units will not change in nature over time, and can be used as the basis for classifying the aforementioned road assessment units.

[0086] Step S20: Classify the unit roads according to the basic attributes of the evaluation unit data, and determine the road construction and maintenance schemes corresponding to different basic attributes of the unit roads.

[0087] In a specific embodiment, the basic data of each known road assessment unit may include basic attributes such as administrative division, climate type, topography, technical grade, and design speed. The basic data, due to its fixed nature, can be used as the basis for category classification.

[0088] Furthermore, the basic attributes in the evaluation unit data of each road unit are divided with a bias to determine which basic attribute is more appropriate as the basis for dividing the road unit. In the above-mentioned judgment process in this embodiment, the judgment basis can be based on historical big data of road network construction and maintenance, or on the industry experience of technical personnel, and there is no limitation here.

[0089] Furthermore, based on the aforementioned established basic attributes as the classification basis, the corresponding basic attributes for road assessment units are determined. Then, based on the historical construction and maintenance plans in the road network construction and maintenance big data corresponding to the aforementioned basic attribute classification, the road construction and maintenance plans corresponding to the basic attributes are matched to determine the road construction and maintenance plans.

[0090] Specifically, when a user selects a section of road to be analyzed in the system, the system automatically determines the corresponding basic attributes of that road. The specific basic attributes are shown in Table 1:

[0091] Administrative divisions Climate type Topography Technical level Design speed Maintenance properties Shanghai Subtropical monsoon Plains highway 120km / h Intermediate revision

[0092] Table 1

[0093] Furthermore, based on historical big data of road network construction and maintenance, the basic attributes used as the classification basis for the roads to be analyzed are selectively categorized. It is determined that when maintenance nature and / or technical grade are used as the classification basis, they better meet the data requirements. Further, based on the basic attributes used as the classification basis for the roads to be analyzed, the corresponding road construction and maintenance schemes under each basic attribute category are determined. The correspondence between the road construction and maintenance schemes and the basic attributes can be the road construction and maintenance schemes corresponding to the historical data of road construction and major / medium maintenance schemes under that basic attribute type, or it can be a specific correspondence between basic data and road construction and maintenance schemes. Here, no specific limitation is made on the correspondence between the basic attributes used as the classification basis and the road construction and maintenance schemes. Specifically, the medium-scale maintenance scheme for the aforementioned expressways can be either directly adding a 5cm asphalt macadam overlay or milling and repaving a 6cm fine-grained asphalt concrete surface layer.

[0094] Step S30: Based on the data from the evaluation unit, determine the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan;

[0095] In one specific embodiment, based on the condition index scores in the historical construction and major / medium maintenance data corresponding to each road assessment unit, the Comprehensive Investment Index (CII) of the road construction and maintenance scheme corresponding to a certain type of basic attribute after classification according to basic attributes is calculated. The road construction and maintenance scheme corresponding to the aforementioned type of basic attribute includes multiple different specific road construction and maintenance schemes, and each specific road construction and maintenance scheme has its corresponding Comprehensive Investment Index (CII).

[0096] Furthermore, the aforementioned Comprehensive Investment Index (CII) can be obtained by calculating the Road Condition Degradation Index (CAI) of the road assessment unit in the implementation of the specific road construction and maintenance plan, and the Investment Benefit Index (IBI) of the implementation of the specific road construction and maintenance plan, thereby determining the CII for the specific road construction and maintenance plan for the road assessment unit. The specific formula for calculating the CII using the Road Condition Degradation Index (CAI) and the Investment Benefit Index (IBI) is as follows:

[0097] CII = a × CAI + b × IBI, where a and b are weight parameters.

[0098] The aforementioned weighting parameters can be adjusted according to different user needs. The value of the Road Condition Degradation Index (CAI) can reflect the social benefits of the corresponding road construction and maintenance scheme to a certain extent, while the value of the Investment Benefit Index (IBI) can reflect the economic benefits of the corresponding road construction and maintenance scheme to a certain extent. By determining the Comprehensive Investment Index (CII) through the above calculation rules, customers can make a choice between social and economic benefits when selecting the corresponding road construction and maintenance scheme based on the Comprehensive Investment Index (CII).

[0099] Step S40: Select the road construction and maintenance scheme that has reached the preset threshold of CII as the target scheme.

[0100] In one specific embodiment, based on the Comprehensive Investment Index (CII) corresponding to different construction schemes and major and medium-sized construction and maintenance schemes under each category calculated above, the magnitude of the CII values ​​corresponding to different road construction and maintenance schemes is compared, and the road construction and maintenance scheme corresponding to the smallest CII value is taken as the optimal construction scheme or major and medium-sized construction and maintenance scheme under that basic attribute type.

[0101] In this embodiment, road assessment unit data for each road unit in the historical big data of road network construction and maintenance is used as the basic support. Based on the condition index score corresponding to the road assessment data of each road unit, the comprehensive investment index of the road assessment unit is determined. This determines the optimal construction and major and medium maintenance target schemes for roads with different basic attributes. In the process of road construction and maintenance scheme decision-making based on big data, the target schemes are more in line with reality, improving the objectivity and data accuracy of the target execution schemes, and further improving the economic benefits of road construction and maintenance.

[0102] Furthermore, based on the first embodiment of the road construction and maintenance scheme decision-making method based on big data in this application, a second embodiment of the road construction and maintenance scheme decision-making method based on big data in this application is proposed.

[0103] The second embodiment of the road construction and maintenance scheme decision-making method based on big data differs from the first embodiment in that this embodiment is a refinement of step S30, "determining the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance scheme based on the evaluation unit data," referring to... Figure 3 Specifically, it includes:

[0104] Step S31: Based on the preset calculation rules, determine the road condition deterioration index (CAI) and the investment benefit index (IBI) according to the condition index scores of the assessment unit data and the construction and maintenance costs of the road assessment unit.

[0105] Specifically, refer to Figure 4 Step S31 specifically includes:

[0106] Step S311: Based on the preset road condition calculation rules, the road condition index CAI corresponding to the road construction and maintenance scheme is calculated according to the road condition index RCI of the condition index score and the year difference of the road assessment unit.

[0107] In one specific embodiment, the road condition index attenuation value ΔRCI for each assessment unit is calculated, which is the index score of the road assessment unit in the initial year. Reduce the index score of the road assessment unit in the final year. To obtain the attenuation value (CAI) of the road condition index for the road assessment unit from the initial year to the final year, the specific steps are as follows;

[0108] Step A: Calculate the year difference ΔT for each assessment unit, i.e., the final year t. n Subtract the initial year t1;

[0109] Step B: Calculate the Road Condition Degradation Index (CAI) for each assessment unit. The specific formula for calculating the Road Condition Degradation Index is as follows:

[0110] Step C: Calculate the road condition deterioration index for different construction schemes and major / medium maintenance road construction and maintenance schemes under a certain basic attribute type, which is classified based on basic attributes. The specific calculation formula is as follows:

[0111] Among them, RCI refers to road condition indicators, which include, but are not limited to, the Pavement Maintenance Quality Index (PQI), Pavement Surlace Condition Index (PCI), Pavement Riding Quality Index (RQI), Pavement Rutting Depth Index (RDI), Pavement Skidding Resistance Index (SRI), Pavement Bumping Index (PBI), Pavement Surface Wearing Index (PWI), and Pavement Structure Strength Index (PSSI). Furthermore, in the above formulas for calculating the attenuation value (CAI) of road condition indicators for each road assessment unit, t represents the year, and m represents the number of assessment units corresponding to different construction schemes and major / medium maintenance road construction and maintenance schemes under a certain basic attribute type, which is classified based on the basic attribute.

[0112] Step S312: Based on the preset benefit calculation rules, the investment benefit index (IBI) of each road unit in the road construction and maintenance plan is calculated according to the construction and maintenance costs of the road assessment unit and the year difference of the road assessment unit.

[0113] In one specific embodiment, the investment benefit index (IBI) of different construction schemes and major / medium repair road maintenance schemes is calculated by calculating the construction cost or the cost of the road maintenance scheme for each assessment unit, as well as the annual routine maintenance cost for each assessment unit. The specific steps are as follows:

[0114] Step D involves converting the aforementioned construction costs, major and medium-sized road maintenance costs, and routine maintenance costs into present value, that is, converting the costs from previous years into the value for the current year, to obtain the construction cost B for each assessment unit. 修 Or major and minor repair costs B 大修 B 中修 And the annual routine maintenance costs after each plan is implemented.

[0115] Step E: Calculate the road construction and maintenance costs for each assessment unit under this type, including the construction plan or major / medium repair and maintenance plan, and the total daily maintenance cost B after implementing the plan. The formula for calculating the total daily maintenance cost is as follows:

[0116]

[0117]

[0118]

[0119] Step F: Calculate the year difference ΔT for major and minor repairs in each assessment unit, i.e., the final year t. n Subtract the construction year t0 or the specific year in which the road assessment unit carried out major or medium repairs;

[0120] Step G: Calculate the Investment Benefit Index (IBI) for each assessment unit, and the formula for calculating the Investment Benefit Index (IBI) for each assessment unit is as follows:

[0121] Step H: Calculate the Investment Benefit Index (IBI) for different construction schemes and major / medium repair and maintenance schemes under each category. The specific calculation formula is as follows:

[0122]

[0123] In the above calculation formulas for the Investment Benefit Index (IBI) of road construction and maintenance schemes, t represents the year, and m represents the number of assessment units corresponding to different construction schemes and major and minor road construction and maintenance schemes under a certain basic attribute type that is classified based on basic attributes.

[0124] Step S32: Based on the road condition degradation index (CAI) and investment benefit index (IBI), determine the comprehensive investment index (CII) corresponding to the road construction and maintenance plan.

[0125] Specifically, the step of determining the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan based on the Road Condition Degradation Index (CAI) and the Investment Benefit Index (IBI) includes:

[0126] Based on the preset investment index calculation rules, preset weights are added to the road condition deterioration index (CAI) and the investment benefit index (IBI) for calculation to determine the comprehensive investment index (CII) corresponding to the road maintenance plan.

[0127] In one specific embodiment, the comprehensive investment index (CII) of the specific road construction and maintenance plan for the road assessment unit is determined by calculating the road condition deterioration index (CAI) of the road assessment unit and the investment benefit index (IBI) of the specific road construction and maintenance plan. The specific formula for calculating the comprehensive investment index (CII) using the road condition deterioration index (CAI) and the investment benefit index (IBI) is as follows:

[0128] CII = a × CAI + b × IBI, where a and b are weight parameters.

[0129] The aforementioned weighting parameters can be adjusted according to different user needs. The Road Condition Degradation Index (CAI) can reflect the social benefits of the corresponding road construction and maintenance scheme to a certain extent, while the Investment Benefit Index (IBI) can reflect the economic benefits of the corresponding road construction and maintenance scheme to a certain extent. By determining the Comprehensive Investment Index (CII) through the above calculation rules, customers can make a choice between social and economic benefits when selecting the corresponding road construction and maintenance scheme based on the Comprehensive Investment Index (CII).

[0130] Furthermore, the steps of the road construction and maintenance scheme decision-making method based on big data also include:

[0131] The CII corresponding to the road construction and maintenance plan of each unit road is calculated according to the preset calculation formula to obtain the comprehensive investment index (CII) of the overall road corresponding to the unit road.

[0132] The overall road comprehensive investment index (CII) is sorted according to a preset order, and the comprehensive investment index (CII) that meets the preset standard is selected.

[0133] The road construction and maintenance plan corresponding to the CII that meets the preset standard is taken as the target plan.

[0134] In one specific embodiment, firstly, the comprehensive investment index (CII) of each unit road is calculated according to the road construction and maintenance plan corresponding to each unit road after the division based on the basic attributes used as the basis for division. Then, by performing a preset summation operation on the comprehensive investment index (CII) of each unit road, the comprehensive investment index (CII) of the overall road to which the unit road is located is calculated according to the road construction and maintenance plan corresponding to the division.

[0135] Furthermore, based on the comprehensive investment index (CII) corresponding to the overall road, the comprehensive investment index (CII) of each corresponding road construction and maintenance scheme is determined. In the specific implementation of this embodiment, the road construction and maintenance scheme corresponding to the minimum value of the comprehensive investment index (CII) is selected as the target construction and maintenance scheme for the overall road corresponding to the unit road.

[0136] For example, if a road consists of four road units: Unit 1, Unit 2, Unit 3, and Unit 4, after specific classification, its corresponding construction schemes include Scheme 1, Scheme 2, Scheme 3, and Scheme 4; the corresponding major repair schemes include Scheme 1, Scheme 2, Scheme 3, and Scheme 4; and the corresponding medium repair schemes include Scheme 1, Scheme 2, Scheme 3, and Scheme 4. Furthermore, each of the above construction schemes, major repair schemes, and medium repair schemes can have its corresponding Comprehensive Investment Index (CII) calculated. By combining each scheme, the construction scheme of the above-mentioned road is realized. The comprehensive investment indices corresponding to the schemes used are preset and summed to determine the comprehensive investment index (CII) of the above-mentioned road for construction and maintenance according to the corresponding schemes. The combination scheme corresponding to the minimum value of the comprehensive investment index (CII) is taken as the target scheme for the construction and maintenance of the road.

[0137] This embodiment, in the process of seeking the optimal construction and major / medium maintenance scheme, on the one hand, makes full use of the large amount of data resources from road inspection and construction and maintenance, realizing the mining and application of big data to determine the road construction and maintenance scheme, so that the specific target scheme is more in line with the actual situation of the road where the road assessment unit is located. The target scheme is determined based on big data, and the data is more refined. On the other hand, this embodiment, by substituting weight parameters, not only determines the optimal scheme under various types, but also determines the comprehensive investment index (CII) of the target by calculating the road condition degradation index (CAI) and the investment benefit index (IBI), and selects a road construction and maintenance scheme that achieves a relative balance between social and economic benefits based on the comprehensive investment index (CII).

[0138] Furthermore, based on the first and second embodiments of the road construction and maintenance scheme decision-making method based on big data in this application, a third embodiment of the road construction and maintenance scheme decision-making method based on big data in this application is proposed.

[0139] The third embodiment of the road construction and maintenance scheme decision-making method based on big data differs from the first, second, and third embodiments of the diagnostic teaching method in that this embodiment is a refinement of step S20, "classifying the unit roads according to the basic attributes of the evaluation unit data and determining the road construction and maintenance schemes corresponding to different basic attributes of the unit roads," referring to... Figure 5 Specifically, it includes:

[0140] Step S21: Select the classification criteria for classifying the road in the unit from the basic attributes of the evaluation unit data;

[0141] Step S22: Based on the classification criteria, classify the unit roads and determine the corresponding classification results;

[0142] In one specific embodiment, the basic attribute data of the aforementioned road assessment unit may include basic attributes such as administrative division, climate type, topography, technical grade, and design speed. The basic attribute data of the aforementioned road assessment unit is fixed and unchanging, that is, the basic attribute data of the road assessment unit will not change in nature over time, and can be used as the classification basis for classifying the aforementioned road assessment unit.

[0143] Furthermore, a biased classification is made in the basic attributes of the evaluation unit data for each road unit to determine which basic attribute is more suitable as the classification basis for the road unit. In the above judgment process in this embodiment, the judgment basis can be based on historical big data of road network construction and maintenance, or on the industry experience of technical personnel. Further, based on historical big data of road network construction and maintenance, a specific basic attribute is selected from the above basic attribute data as the classification basis for classification, and the classification result is determined.

[0144] Step S22: Based on the classification results of the unit road according to the classification criteria, determine the road construction and maintenance plan corresponding to the classification criteria.

[0145] In one specific embodiment, based on the basic attributes of the aforementioned unit roads used as the basis for division, the corresponding road construction and maintenance scheme under the basic attribute category is determined. The correspondence between the aforementioned road construction and maintenance scheme and the aforementioned basic attributes can be the historical data of road construction and public maintenance schemes under the basic attribute type, or it can be that the basic data and road construction and maintenance schemes are stored in correspondence according to a specific correspondence. Here, no specific limitation is made on the correspondence between the basic attributes used as the basis for division and the road construction and maintenance schemes.

[0146] In this embodiment, road assessment units are classified by basic attributes, and then road construction and major / medium repair road maintenance plans corresponding to a certain basic attribute are obtained. Big data is used as the basis for road maintenance plan decision-making, making the data for calculation more refined and improving the objectivity of road construction and maintenance plans.

[0147] Furthermore, based on the first, second, and third embodiments of the road construction and maintenance scheme decision-making method based on big data in this application, a fourth embodiment of the road construction and maintenance scheme decision-making method based on big data in this application is proposed.

[0148] The fourth embodiment of the road construction and maintenance scheme decision-making method based on big data differs from the first, second, and third embodiments of the diagnostic teaching method in that this embodiment includes the following step before step S10, "acquiring the evaluation unit data for each road unit":

[0149] Step S100: Perform data anomaly processing on the road data of each unit.

[0150] Reference Figure 6 , Figure 6 This is a schematic diagram of the specific process of step S100. Specifically, it involves processing abnormal data in the road assessment unit data required for road construction and maintenance scheme decision-making based on big data in this embodiment to ensure the accuracy of the basic data and guarantee the precision of the target scheme.

[0151] Reference Figure 7 Step S100 specifically includes:

[0152] Step S101: Obtain the detection data of each unit road for a preset year;

[0153] Step S102: Remove the abnormal detection data corresponding to the years in which the detection data shows preset data abnormalities, and determine the evaluation unit data for index calculation of each unit road.

[0154] In one specific embodiment, historical construction and major / medium maintenance data are acquired. The aforementioned historical construction and major / medium maintenance data may include construction and major / medium maintenance data of the road where the road assessment unit is located, as well as inspection data of the road where the road assessment unit is located. The preset year for inspection can be once a year or once every three years. There is no limitation on the annual time interval of the inspection data.

[0155] Furthermore, the aforementioned construction and maintenance data includes: the construction year of the road assessment unit, the condition index score corresponding to the construction year, the year of major and medium maintenance, and the road condition index score corresponding to the year of major and medium maintenance; the aforementioned testing data includes: the year in which the road assessment unit was tested, and the road condition index score corresponding to the year of testing; in addition, it also includes the original construction plan and cost of the road where each road assessment unit is located, the major and medium maintenance plans and costs over the years, and the daily maintenance costs over the years.

[0156] Specifically, the index scores corresponding to the construction year and the year of major or medium repairs for each road assessment unit are deleted. Then, data anomaly units where the index score of the final year of the road assessment unit is greater than the initial year value are removed.

[0157] This embodiment uses a large amount of construction, major and minor maintenance data as support, and removes abnormal data to ensure the accuracy of the data, making the basic data more objective and scientific.

[0158] Furthermore, embodiments of the present invention also propose a scheme decision-making system, referring to... Figure 8 , Figure 8This is a schematic diagram of the functional modules of the road construction and maintenance scheme decision-making system involved in an embodiment of the road construction and maintenance scheme decision-making method based on big data of the present invention. Figure 8 As shown, the solution decision system includes:

[0159] The data acquisition module 10 is used to acquire the evaluation unit data for each road unit;

[0160] The attribute classification module 20 is used to classify the unit road according to the basic attributes of the evaluation unit data, and determine the road construction and maintenance schemes corresponding to different basic attributes of the unit road.

[0161] The index calculation module 30 is used to determine the comprehensive investment index (CII) corresponding to the road construction and maintenance plan based on the data from the evaluation unit.

[0162] The scheme selection module 40 is used to select the road construction and maintenance scheme that has reached the preset threshold of CII as the target scheme.

[0163] Preferably, the attribute classification module includes:

[0164] Classification basis selection unit: used to select the classification basis for classifying the roads in the unit from the basic attributes of the evaluation unit data;

[0165] A data partitioning unit is used to classify the unit roads based on the classification criteria and determine the corresponding classification results;

[0166] The scheme matching unit is used to determine the road construction and maintenance scheme corresponding to the classification criteria based on the classification results of the unit road according to the classification criteria.

[0167] Preferably, the index calculation module includes:

[0168] The index calculation unit is used to determine the road condition deterioration index (CAI) and the investment benefit index (IBI) based on preset calculation rules, the condition index scores of the assessment unit data, and the construction and maintenance costs of the road assessment unit.

[0169] The index determination unit is used to determine the comprehensive investment index CII corresponding to the road construction and maintenance plan based on the road condition deterioration index CAI and the investment benefit index IBI.

[0170] Preferably, the scheme selection module includes:

[0171] The index sorting unit is used to sort the comprehensive investment index (CII) corresponding to the road construction and maintenance schemes classified based on different basic attributes according to a preset order.

[0172] The scheme selection unit is used to select the Comprehensive Investment Index (CII) that meets the preset standard from the preset order; and to take the road construction and maintenance scheme corresponding to the CII that meets the preset standard as the target scheme.

[0173] This embodiment demonstrates the principle and implementation process of road construction and maintenance plan decision-making based on big data. Please refer to the above embodiments for details, which will not be repeated here.

[0174] Furthermore, this embodiment of the invention also proposes an apparatus, which includes a memory, a processor, and a road construction and maintenance scheme decision program stored in the memory and executable on the processor. When the road construction and maintenance scheme decision program is executed by the processor, it implements the steps of the road construction and maintenance scheme decision method based on big data as described in the above embodiments.

[0175] In addition, to achieve the above objectives, the present invention also provides a medium, which is a computer-readable storage medium, on which a road construction and maintenance scheme decision program is stored. When the road construction and maintenance scheme decision program is executed by a processor, it implements the steps of the road construction and maintenance scheme decision method based on big data as described above.

[0176] Since the decision-making process of this construction and maintenance scheme adopts all the technical solutions of all the aforementioned embodiments when it is executed by the processor, it has at least all the beneficial effects brought about by all the technical solutions of all the aforementioned embodiments, which will not be repeated here.

[0177] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0178] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0179] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, 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 is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0180] The above are merely preferred embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A road construction and maintenance scheme decision-making method based on big data, characterized in that, The big data-based road construction and maintenance scheme decision-making method includes: Obtain the assessment unit data for each road unit; Based on the basic attributes of the assessment unit data, the unit roads are classified, and road construction and maintenance schemes corresponding to different basic attributes of the unit roads are determined. Based on the data from the assessment unit, the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan is determined, wherein the Comprehensive Investment Index (CII) is determined by the Road Condition Degradation Index (CAI) and the Investment Benefit Index (IBI). The road construction and maintenance scheme that reaches the preset threshold of CII is selected as the target scheme. Specifically, the CII corresponding to the road construction and maintenance scheme of each unit road is calculated according to a preset calculation formula to obtain the comprehensive investment index (CII) of the overall road corresponding to the unit road. The comprehensive investment index (CII) of the overall road is sorted according to a preset order, and the comprehensive investment index (CII) that reaches the preset standard is selected. The road construction and maintenance scheme corresponding to the CII that reaches the preset standard is selected as the target scheme. The step of determining the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan based on the evaluation unit data includes: Based on preset calculation rules, the road condition degradation index (CAI) and investment benefit index (IBI) are determined according to the condition index scores of the assessment unit data and the construction and maintenance costs of the road assessment unit. Specifically, based on preset road condition calculation rules, the road condition degradation index (CAI) corresponding to the road construction and maintenance plan is calculated based on the road surface condition index (RCI) of the condition index scores and the year difference of the road assessment unit. Based on preset benefit calculation rules, the investment benefit index (IBI) for each road unit in the road construction and maintenance plan is calculated based on the construction and maintenance costs of the road assessment unit and the year difference of the road assessment unit. Based on preset investment index calculation rules, preset weights are added to the road condition degradation index (CAI) and investment benefit index (IBI) for calculation to determine the comprehensive investment index (CII) corresponding to the road construction and maintenance plan. The preset weights are dynamically adjusted according to the basic attributes of the road.

2. The road construction and maintenance scheme decision-making method based on big data as described in claim 1, characterized in that, Before the step of acquiring the assessment unit data for each road unit, the method further includes: Obtain the detection data for each unit road in a preset year; The test data corresponding to the years in which the test data shows preset data anomalies are removed to determine the evaluation unit data for index calculation of each road unit.

3. The road construction and maintenance scheme decision-making method based on big data as described in claim 1, characterized in that, The step of classifying the unit roads according to the basic attributes of the evaluation unit data and determining the road construction and maintenance schemes corresponding to different basic attributes of the unit roads includes: Select the classification criteria for classifying the roads in the assessment unit from the basic attributes of the assessment unit data; Based on the classification criteria, the unit roads are classified, and the corresponding classification results are determined. Based on the classification results of the unit roads according to the classification criteria, the road construction and maintenance plan corresponding to the classification criteria is determined.

4. A scheme decision-making system, characterized in that, The solution decision-making system includes: The data acquisition module is used to acquire the evaluation unit data for each road unit; The attribute classification module is used to classify the unit roads according to the basic attributes of the evaluation unit data, and determine the road construction and maintenance schemes corresponding to different basic attributes of the unit roads. The index calculation module is used to determine the comprehensive investment index (CII) corresponding to the road construction and maintenance plan based on the evaluation unit data. The comprehensive investment index (CII) is determined by the road condition deterioration index (CAI) and the investment benefit index (IBI). The scheme selection module is used to select road construction and maintenance schemes that reach a preset threshold for CII as target schemes. Specifically, the CII corresponding to the road construction and maintenance scheme of each unit road is calculated according to a preset calculation formula to obtain the comprehensive investment index (CII) of the overall road corresponding to that unit road; the comprehensive investment index (CII) of the overall road is sorted according to a preset order, and the comprehensive investment index (CII) that reaches a preset standard is selected; the road construction and maintenance scheme corresponding to the CII that reaches the preset standard is selected as the target scheme. The index calculation module is further configured to determine the Road Condition Decay Index (CAI) and Investment Benefit Index (IBI) based on preset calculation rules, according to the condition index scores of the assessment unit data and the construction and maintenance costs of the road assessment unit. Specifically, based on preset road condition calculation rules, the Road Condition Decay Index (CAI) corresponding to the road construction and maintenance plan is calculated based on the Road Surface Condition Index (RCI) of the condition index scores and the year difference of the road assessment unit. Based on preset benefit calculation rules, the Investment Benefit Index (IBI) for each road unit in the road construction and maintenance plan is calculated based on the construction and maintenance costs of the road assessment unit and the year difference of the road assessment unit. Based on preset investment index calculation rules, preset weights are added to the Road Condition Decay Index (CAI) and Investment Benefit Index (IBI) for calculation to determine the Comprehensive Investment Index (CII) corresponding to the road construction and maintenance plan. The preset weights are dynamically adjusted according to the basic attributes of the road.

5. A device, characterized in that, The device includes a memory, a processor, and a road construction and maintenance scheme decision program stored in the memory and executable on the processor. When the road construction and maintenance scheme decision program is executed by the processor, it implements the road construction and maintenance scheme decision method based on big data as described in any one of claims 1-3.

6. A medium, said medium being a computer-readable storage medium, characterized in that, The computer-readable storage medium stores a road construction and maintenance scheme decision program, which, when executed by a processor, implements the steps of the road construction and maintenance scheme decision method based on big data as described in any one of claims 1 to 3.

Images