A highway expansion mode decision method based on life cycle cost benefit

Abstract

The application discloses a highway expansion mode decision method based on a whole life cycle cost benefit, and comprises the following steps: S1, highway expansion period construction cost is estimated; S2, highway expansion period construction carbon emission cost is estimated; S3, highway expansion period operation benefit loss is estimated; S4, highway operation period operation benefit is estimated; S5, highway expansion operation period operation cost is estimated; S6, highway expansion period and operation period vehicle operation carbon emission cost are estimated; S7, based on whole life cycle cost benefit analysis, the expansion scheme is decided.The application considers the construction and operation period carbon emission cost and the expansion period operation benefit loss, so that the whole life cycle cost benefit system of the highway expansion project is more perfect.Facing different expansion modes, the method can be used to complete the total cost benefit analysis of the construction period and the operation period, and the generality of the decision method is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of engineering economy, in particular to a highway expansion mode decision method based on life cycle cost benefit. BACKGROUND

[0002] Some of the early built highways in China have entered the period of reconstruction and expansion, and with the increasing perfection of the national highway network, the proportion of expansion construction in highway infrastructure construction is expected to continue to rise. In view of this, the analysis of the life cycle cost benefit of highway expansion project will ensure that the expansion decision is more accurate and efficient, and can provide solid decision support for promoting the sustainable development of China's transportation industry, which has important practical significance and theoretical significance.

[0003] At present, cost benefit analysis has been widely studied and applied in highway expansion project decision-making, but there are still some problems:

[0004] (1) There are relatively few studies based on the whole life cycle, most of the studies only focus on the construction period or operation period of the highway, and lack of overall analysis of the two, leading to one-sided analysis results;

[0005] (2) The cost benefit analysis is not comprehensive, and few studies consider the operation benefit loss during the expansion period of the highway;

[0006] (3) The social environmental factors are not paid enough attention, especially the carbon emission estimation is not included in the research scope of highway cost benefit and project decision-making.

[0007] Therefore, the existing highway cost benefit research needs to be further sorted out and improved in order to provide more reliable basis for expansion scheme decision. SUMMARY

[0008] The technical problem to be solved by the present application is to overcome the defects of the prior art and provide a highway expansion mode decision method based on life cycle cost benefit, thereby providing a basis for highway expansion decision.

[0009] In order to solve the above technical problems, the present application provides the following technical scheme:

[0010] The present application provides a highway expansion mode decision method based on life cycle cost benefit, comprising the following steps:

[0011] S1. Highway expansion construction cost estimation, collecting existing highway expansion project estimation, budget, budget, and final accounts data, estimating the highway expansion construction cost according to the GM(1,1) grey system model, and obtaining the construction cost prediction value under different expansion modes;

[0012] S2. The carbon emission cost estimation of the highway expansion period due to construction, according to the experience of existing highway expansion projects, the material consumption and energy consumption under different expansion modes are estimated; a highway expansion period carbon emission cost estimation method based on material consumption and energy consumption under different expansion modes is established;

[0013] S3. Highway expansion period operating income loss estimation, distinguish between forced diversion and induced diversion, estimate the operating income loss of the highway expansion period according to the loss traffic volume;

[0014] S4. Highway operating period operating income estimation, OD investigation, 24-hour traffic volume observation and social and economic investigation are carried out in the project influence area, the incremental rate and growth rate of future traffic volume are predicted, and the Fratar model is used to calculate the trend type OD distribution matrix of each traffic zone in the future, and the induced traffic volume is calculated, and the user equilibrium distribution model is used to calculate the highway traffic volume after the expansion is completed, and the operating income in the operating period is calculated;

[0015] S5. Highway operating period operating cost estimation, the operating cost in the operating period is estimated according to the personnel cost and maintenance cost in the operating period;

[0016] S6. Highway expansion period and operating period carbon emission cost estimation, according to the running speed to calculate the fuel consumption of different vehicle types, and then calculate the carbon emission and carbon emission cost in the expansion period and the operating period;

[0017] S7. Based on the conclusions of S1 to S6, the highway expansion scheme is evaluated and analyzed based on the whole life cycle cost benefit using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), including the following steps;

[0018] S7.1) The whole life cycle cost of highway expansion project mainly includes expansion period construction cost, expansion period carbon emission cost, expansion period operating income loss, operating cost after expansion and operating period carbon emission cost, which is a minimum type index, and is processed in a positive way by taking the reciprocal method;

[0019] S7.2) Highway expansion project whole life cycle benefit analysis mainly includes operating period operating income, which is a maximum type index;

[0020] S7.3) Standardization processing is carried out on the minimum type index after positive processing and the maximum type index without processing to eliminate the influence of dimension;

[0021] S7.4) According to the cost-benefit composition described above, the positive and negative ideal solutions are calculated: the positive ideal solution refers to the virtual solution composed of the maximum values of each data after the processing in step 7.3, and the negative ideal solution refers to the virtual solution composed of the minimum values on each attribute;

[0022] S7.5) The TOPSIS method is used to score different highway expansion schemes, and the one with the highest score is selected as the final decision scheme.

[0023] In the second aspect of the present application, a highway expansion scheme decision system based on life cycle cost-benefit calculation is provided, and the system comprises:

[0024] The acquisition module is used for collecting the existing highway expansion project estimation, budget, budget, and data of the expansion period material and energy consumption data, regional social and economic development, predicted traffic volume and traffic distribution, vehicle running speed, and data of each step target operation node into the system;

[0025] The data module is used for establishing a grey system model, a carbon emission cost estimation model, an expansion period operation benefit loss estimation model, an operation period operation cost estimation model, an operation period operation benefit estimation model, etc., and establishing a data operation process;

[0026] The data component module is used for storing table data, and forming a visual classification of the front end through the table data, and forming a DAG graph, and constructing a logical graph of the stored table data;

[0027] The decision module is used for evaluating and deciding different expansion schemes by using the TOPSIS method.

[0028] In the third aspect of the present application, a computer device is provided, comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to the first aspect or the functions of the system according to the second aspect when executing the computer program.

[0029] In the fourth aspect of the present application, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method according to the first aspect or the functions of the system according to the second aspect.

[0030] Compared with the prior art, the present application has the following advantages:

[0031] 1: The present application calculates the highway expansion cost and benefit based on the life cycle, and can calculate the total cost and total benefit of the highway construction period and operation period for different types of expansion schemes, can complete the selection of different expansion schemes in a more accurate way, and improves the generality of the decision method.

[0032] 2: The application further designs a cost calculation method based on carbon emissions, improves the expressway expansion cost calculation system by calculating carbon emissions during construction and operation, and makes the overall cost calculation more accurate. BRIEF DESCRIPTION OF DRAWINGS

[0033] The accompanying drawings are included to provide a further understanding of the application, and are incorporated in and constitute a part of this specification, illustrate embodiments of the application, and together with the description serve to explain the application, and do not limit the application. In the drawings:

[0034] Figure 1 is the overall flowchart of the application. DETAILED DESCRIPTION

[0035] The preferred embodiments of the application are described below in conjunction with the accompanying drawings, and it should be understood that the preferred embodiments described herein are only used to illustrate and explain the application, and do not limit the application.

[0036] Example 1

[0037] The application provides an expressway expansion mode decision method based on life cycle cost benefit, comprising the following steps:

[0038] Step 1) Estimating the construction cost of expressway expansion period according to the GM(1,1) gray system model.

[0039] Step 1.1) According to the experience of existing engineering construction, extracting the original data series X0 of construction cost per kilometer under different expansion modes such as expressway relocation new line reconstruction and in-situ widening;

[0040] Step 1.2) Deforming the original series X0 by using one-time accumulation to obtain a new series X1;

[0041] Step 1.3) Establishing a gray generation model and solving it, that is,

[0042] wherein

[0043] Step 1.3) The predicted value is X0(j+1)=(1-e a )[X0(1)-μ / a]e -aj ,(j=1,2……,n);

[0044] Step 1.4) Assuming that the project start year is n, then the construction cost of expressway expansion period is:

[0045] S sj =L×X0(n)

[0046] wherein: S sj is the construction cost of the highway expansion period; X0(n) is the construction cost per kilometer of the highway expansion period; and L is the highway expansion mileage.

[0047] Step 2) Estimation method of carbon emission cost of the highway expansion period.

[0048] Step 2.1) The carbon emission amount generated by material materialization in the highway expansion period is estimated according to the following formula:

[0049]

[0050] wherein: e1 is the carbon emission amount generated by material materialization; i is the material type; M i is the consumption amount of the material i; γ i is the carbon emission coefficient of the material i;

[0051] Step 2.2) The carbon emission amount generated by mechanical construction in the highway expansion period is estimated according to the following formula:

[0052]

[0053] R j = NCV j × FC j ;

[0054] β j = CC j × OF j × 44 / 12;

[0055] wherein: e2 is the carbon emission amount generated by mechanical construction; j is the energy type; R j is the activity data of the energy j; β j is the carbon dioxide emission factor of the energy j; NCV j is the low calorific value of the energy j; FC j is the consumption amount of the energy j; CC j is the unit heat value carbon content of the energy j; OF j is the carbon oxidation rate of the energy j;

[0056] Step 2.3) The construction carbon emission cost of the expansion period is estimated according to the carbon emission amount generated by material materialization and the carbon emission amount generated by mechanical construction in the highway expansion period according to the following formula:

[0057] e = e1 + e2;

[0058] S cj = VC * e;

[0059] wherein: S cjThe total cost of carbon emissions during the highway expansion period; e is the total amount of carbon emissions generated during the highway expansion construction; VC is the average unit price of carbon emission cost.

[0060] Step 3) Estimation of loss of operating income during the highway expansion period.

[0061] Step 3.1) Estimate the loss of traffic volume during the highway expansion period;

[0062] Step 3.1.1) Under the condition of forced diversion, estimate the loss of traffic volume according to the forced diversion ratio;

[0063] Step 3.1.2) Under the condition of induced diversion, estimate the loss of traffic volume based on evolutionary game theory;

[0064] Step 3.1.2.1) Establish an evolutionary game model G = {N, S, U}, where N, S and U represent the participants, strategy set and payment matrix in the evolutionary game:

[0065] N = {Participant 1, Participant 2};

[0066] S = {Accept induction, refuse induction};

[0067] The payment matrix is as follows:

[0068]

[0069] Where T1 and F1 represent the time cost and fuel consumption cost when both participants choose to accept the induction strategy; T4 and F4 represent the time cost and fuel consumption cost when both participants choose to refuse the induction strategy; T2 and F2 represent the time cost and fuel consumption cost when one participant chooses to accept the induction strategy and the other chooses to refuse the induction strategy; T3 and F3 represent the time cost and fuel consumption cost when one participant chooses to accept the induction strategy and the other chooses to refuse the induction strategy; W represents the toll generated when a participant chooses to refuse the induction strategy and travels on the improved and expanded highway; S represents other payments made by a participant when traveling on the flow road, such as the payment made by the driver when traveling on the national and provincial highways due to the decrease in traffic conditions and the increase in traffic interference. Before the expansion, the driver tended to choose the highway for travel, so the other payments on the flow road should satisfy:

[0070] S > max(0, T3 + F3 + W - T2 - F2);

[0071] Step 3.1.2.2) Conduct a survey of the improved and expanded road, the flow road and the regional social and economic situation, and assign values to the payment matrix;

[0072] Step 3.1.2.3) Establish a replicator dynamic equation as follows:

[0073]

[0074] wherein:

[0075] U A = x(T1+F1+S) + (1-x)(T2+F2+S);

[0076] U R = x(T3+F3+W) + (1-x)(T4+F4+W);

[0077]

[0078] Step 3.1.2.4) Let the dynamic equation equal to 0, and solve the possible equilibrium points of the system as x = 0, x = 1, x = N / M, wherein:

[0079] N = T4+F4+W-T2-F2-S;

[0080] M = T1+F1+T4+F4-T2-F2-T3-F3;

[0081] Step 3.1.2.5) Analysis of equilibrium stability, the system tends to be stable only when g(x) = <0 and g'(x) <0. The system may appear as follows:

[0082] ① Evolution tends to be stable at x = 0, which induces the failure of diversion, and the diversion scheme should be redesigned;

[0083] ② Evolution tends to be stable at x = N / M, according to the payment matrix assignment in S3.1.2.2), N / M is estimated, and the product of N / M and the current highway traffic volume is the traffic volume loss of the expanded highway under the induced diversion condition;

[0084] Step 3.2) Estimate the loss of operating income of the expanded highway during the construction period according to the loss of traffic volume, as shown in the following formula:

[0085]

[0086] wherein: S Q represents the operating loss of the highway expansion project during the construction period; L i represents the length of the i-th construction section of the highway expansion project during the construction period; Q si represents the traffic volume loss of the i-th construction section of the highway expansion project during the construction period, under the condition of forced diversion, Q si is the product of the diversion vehicle ratio and the current highway traffic volume in the same time period, under the condition of induced diversion, Q si is the product of N / M and the current highway traffic volume in the same time period; d represents the highway toll collection standard; k represents the number of construction sections of the highway expansion channel.

[0087] Step 4) Estimation of the operating income during the operating period of the expressway.

[0088] Step 4.1) Division of traffic zones for the project influence area, OD investigation and 24-hour traffic volume observation and analysis on the relevant roads.

[0089] Step 4.2) Trend-type traffic volume distribution prediction.

[0090] Step 4.2.1) Prediction of the future economic development and the elasticity coefficient of each period according to the social and economic data of the project influence area;

[0091] Step 4.2.2) Calculation of the growth rate of the automobile traffic volume of each traffic zone by the elasticity coefficient method, as shown in the following formula:

[0092] r i = T i × E i ;

[0093] wherein r i represents the growth rate of the traffic volume of each influence area in the future year (%); T i represents the elasticity coefficient of the traffic volume of each influence area to the economic index in the future year; and E i represents the growth speed of the gross domestic product of each influence area in the future year (%).

[0094] Step 4.2.3) Prediction of the occurrence and attraction traffic volume of each zone in the future year according to the occurrence and attraction traffic volume of each OD zone in the observation year, according to the following formula.

[0095] Q i = P i × (1 + r i ) t

[0096] wherein Q i represents the occurrence and attraction traffic volume of zone i in the characteristic year; P i represents the occurrence and attraction traffic volume of zone i in the base year; r i represents the average annual growth rate of the traffic volume of zone i (%); and t represents the prediction year.

[0097] Step 4.2.4) Calculation of the trend-type OD distribution matrix of each traffic zone in the future by the Fratar model, as shown in the following formula:

[0098]

[0099] wherein Q ij represents the traffic distribution volume from zone i to zone j in the future prediction characteristic year; Q 0ij represents the present OD volume from zone i to zone j in the base year; and Gj is the growth multiple of traffic attraction of zone j; F i is the growth multiple of traffic generation of zone i; n is the total number of traffic zones in the study area; Q aj is the traffic attraction of zone j in the characteristic year; Q 0aj is the traffic attraction of zone j in the base year; Q pi is the traffic generation of zone i in the characteristic year; Q 0pi is the traffic generation of zone i in the base year; L i is the average location coefficient of zone i; L j is the average location coefficient of zone j.

[0100] Step 4.3) Induced traffic volume distribution prediction.

[0101] Step 4.3.1) When the current inter-zone traffic volume is not zero, the induced traffic volume calculation formula is as follows:

[0102]

[0103] wherein T ij represents the induced traffic volume from zone i to zone j; D ij represents the generalized cost from zone i to zone j without this item; D ij ' represents the generalized cost from zone i to zone j with this item; Q ij represents the trend traffic volume from zone i to zone j; and r is the gravity model parameter.

[0104] Step 4.3.2) When the current inter-zone traffic volume is zero, the induced traffic volume calculation formula is as follows:

[0105]

[0106] wherein P i represents the traffic generation of zone i; A j represents the traffic generation of zone j; and K, a, b, g represent the gravity model parameters, which are calibrated according to the OD survey results and regression analysis.

[0107] Step 4.4) The sum of the trend-type OD matrix and the induced-type OD matrix of each zone is calculated, as shown in the following formula:

[0108] QZ ij = Q ij + T ij

[0109] wherein QZ ij represents the sum of the trend-type traffic distribution and the induced-type traffic distribution from zone i to zone j in a certain predicted characteristic year in the future.

[0110] Step 4.5) The shortest path iterative assignment method considering capacity limitation is used to distribute the traffic volume QZ ijThe distribution is made, and the annual traffic volume of the project route is obtained

[0111] Step 4.5.1) Divide QZ ij into n parts, and according to the route impedance, find the shortest path from i area to j area, and distribute one part of the traffic volume to the shortest path. Wherein: the calculation method of route impedance is as follows:

[0112]

[0113] Wherein: t a (x a ) represents the route a impedance; represents the vehicle travel time of route a in free flow state; C a refers to the route capacity; V represents the time value; k a represents the route fixed fee; l a represents the route length; d represents the highway toll standard;

[0114] Step 4.5.2) After the last distribution is completed, according to the distribution result, the route impedance is recalculated in combination with the section capacity, and the next part of traffic volume is distributed to the new shortest path;

[0115] Step 4.5.3) Repeat the above operation until the traffic volume distribution is completed. The traffic volume distributed to the project route is converted into the annual total traffic volume Q k ;

[0116] Step 4.6) According to the route annual traffic volume obtained in step 4.5), the operating income of the project in the operating period is calculated as follows:

[0117]

[0118] Wherein: Y Q represents the operating income of the highway expansion in the operating period; L represents the length of the project road; Q k total traffic volume of the route in the kth year after the completion of the highway expansion; d represents the highway toll standard; g represents the calculation period.

[0119] Step 5) Estimate the operating cost of the highway in the operating period.

[0120] Step 5.1) According to the engineering experience of existing highway expansion projects, estimate the management cost and annual maintenance cost required after the completion of the project.

[0121] Step 5.2) Estimate the increase of management cost according to the number of personnel.

[0122] S pm =pm1×a×g+pm1×b×g;

[0123] Wherein: S pm represents the highway operating period management cost; pm1 represents the number of highway toll station management personnel; pm2 represents the number of highway management branch and monitoring center personnel; a represents the annual per capita cost standard of toll station management personnel; b represents the annual per capita cost standard of management branch and monitoring center personnel; g represents the calculation period.

[0124] Step 5.3) Estimate the maintenance cost.

[0125]

[0126] Wherein: S rdz represents the highway operating period maintenance cost; S rdj represents the highway expansion operating period maintenance cost in the jth year, including daily maintenance cost and major repair cost; g represents the calculation period.

[0127] Step 5.4) The highway operating period operating cost is the sum of the management cost and the maintenance cost.

[0128] S y = S pm + S rdz ;

[0129] Wherein: S y represents the highway operating period operating cost.

[0130] Step 6) Propose an estimation method of highway expansion period and operating period carbon emission cost.

[0131] Step 6.1) According to the expected service level of highway expansion period and operating period, the running speed of different vehicle types is speculated;

[0132] Step 6.2) Estimate the vehicle fuel consumption per 100 kilometers according to the running speed;

[0133] Fuel consumption per 100 kilometers of small passenger car:

[0134] N1 = -0.21637v1 + 0.0013055v1 2 + 0.24808IRI + 13.36580;

[0135] In the formula: N1 is the fuel consumption per 100 kilometers of small passenger car, L / 100km; v1 is the running speed of small passenger car, km / h; IRI is the international smoothness index, m / km;

[0136] Fuel consumption per 100 kilometers of medium passenger car:

[0137] N2 = -0.45341v2 + 0.0032984v2 2 + 0.42424IRI + 25.31578;

[0138] In the formula: N2 is the fuel consumption of a medium-sized bus per 100 kilometers, L / 100km; v2 is the operating speed of the medium-sized bus, km / h; IRI is the International Roughness Index, m / km;

[0139] Fuel consumption per 100 kilometers for large buses:

[0140] N3 = -1.07275v3 + 0.0084534v3 2 +1.12121IRI+53.00515;

[0141] Where: N3 is the fuel consumption of the large bus per 100 kilometers, L / 100km; v3 is the operating speed of the large bus, km / h; IRI is the International Roughness Index, m / km;

[0142] Fuel consumption per 100 kilometers for small trucks:

[0143] N4 = -0.56612v4 + 0.004014v4 2 +0.56222IRI+25.29872;

[0144] In the formula: N4 is the fuel consumption of a small truck per 100 kilometers, L / 100km; v4 is the operating speed of the small truck, km / h; IRI is the International Roughness Index, m / km;

[0145] Fuel consumption per 100 kilometers for medium-sized trucks:

[0146] N5 = -0.77007v5 + 0.0061404v5 2 +1.45051IRI+34.50465;

[0147] In the formula: N5 is the fuel consumption of a medium-sized truck per 100 kilometers, L / 100km; v5 is the operating speed of a medium-sized truck, km / h; IRI is the International Roughness Index, m / km;

[0148] Fuel consumption per 100 kilometers for large trucks:

[0149] N6 = -1.64706v6 + 0.014388v6 2 +1.58990IRI+62.90253;

[0150] In the formula: N6 is the fuel consumption of a large truck per 100 kilometers, liters / 100km; v6 is the operating speed of the large truck, km / h; IRI is the International Roughness Index, m / km;

[0151] Step 6.3) Calculate the total fuel consumption during the highway expansion and operation periods based on the vehicle's fuel consumption per 100 kilometers:

[0152]

[0153] CR = ∑(i=1 to n) (q i * L * CR i) ; where CR is the total fuel consumption of vehicles on the expressway during the construction and operation period, L is the length of the route, km, q i is the cumulative traffic volume of the i th vehicle type during the construction period, and CR i is the fuel consumption per 100 km of the i th vehicle type during the construction period. ki yi q i is the cumulative traffic volume of the i th vehicle type during the operation period, and CR i is the fuel consumption per 100 km of the i th vehicle type during the operation period. ki yi CR i is the fuel consumption per 100 km of the i th vehicle type during the operation period.

[0154] Step 6.4) Estimate the carbon dioxide emissions based on the total fuel consumption of vehicles on the expressway during the construction and operation period:

[0155] e3 = CR * δ; where e3 is the total carbon emissions of vehicles on the expressway during the construction and operation period, and δ is the fuel carbon emission factor.

[0156] where e3 is the total carbon emissions of vehicles on the expressway during the construction and operation period, and δ is the fuel carbon emission factor.

[0157] Step 6.5) Convert the carbon emission estimate into carbon emission cost S QC as follows:

[0158] S QC = VC * e3; where S QC is the total carbon emission cost of vehicles on the expressway during the construction and operation period, e3 is the total carbon emissions of vehicles on the expressway during the construction and operation period, and VC is the average unit price of carbon emission cost.

[0159] Step 7) Based on the conclusions of Steps 1) to 6), use the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to evaluate and analyze the expressway expansion scheme based on the life cycle cost-benefit, including the following steps:

[0160] Step 7.1) The life cycle cost of the expressway expansion project mainly includes the construction cost during the expansion period, the carbon emission cost during the expansion period, the loss of operation benefits during the expansion period, the operation cost after the expansion is completed, and the carbon emission cost during the operation period. It is a minimum type index and is processed in a positive direction by taking the reciprocal method.

[0161] Step 7.2) Life cycle benefit analysis of expressway expansion project mainly includes operation benefits during the operation period, which is a maximum type index.

[0162] ​​Step 7.3) Standardize the min-sized indicators after the positive direction processing and the max-sized indicators without processing to eliminate the influence of dimension;

[0163] Step 7.4) Calculate the positive ideal solution and the negative ideal solution according to the cost-benefit composition. The positive ideal solution refers to the virtual solution composed of the maximum values of each data after the processing of step 7.3), and the negative ideal solution refers to the virtual solution composed of the minimum values on each attribute;

[0164] Step 7.5) Score different highway expansion schemes using the TOPSIS method, and select the one with the highest score as the final decision scheme, as shown in the following formula:

[0165]

[0166] In the formula: S i represents the comprehensive evaluation score of the i th expansion scheme; D i + and D i - respectively represent the Euclidean distance between the i th expansion scheme and the positive ideal solution and the negative ideal solution.

[0167] In another embodiment, the present application provides a highway expansion system based on life cycle cost-benefit calculation, which comprises:

[0168] The acquisition module is used to collect the existing highway expansion project estimation, budget, budget, data, expansion period material and energy consumption data, regional social and economic development, predicted traffic volume and traffic distribution, vehicle running speed, and data of each step target operation node into the system;

[0169] The data module is used to establish a gray system model, a carbon emission cost estimation model, an expansion period operation benefit loss estimation model, an operation period operation cost estimation model, an operation period operation benefit estimation model, etc., and establish a data operation process;

[0170] The data component module is used to store table data, and form a visual classification of the front end through the table data, and form a DAG graph, and construct a logical graph of the stored table data;

[0171] The decision module uses the TOPSIS method to evaluate and decide different expansion schemes. In another embodiment, the present application provides a computer readable storage medium having a computer program stored thereon, which, when executed by a processor, realizes the functions of the method embodiments or other corresponding system embodiments, which will not be repeated here.

[0172] In another embodiment, the present application provides a computer device, comprising a processor, a memory, and a computer program stored on the memory and executable on the processor, wherein the processor implements the functions of the method embodiments or other corresponding system embodiments described in combination when the computer program is executed, which will not be described here again.

[0173] Finally, it should be noted that: the above only for the preferred embodiments of the present application, and not for limiting the present application, although in reference to the foregoing embodiments of the present application has been described in detail, for those skilled in the art, it still can be modified, or part of the technical features of the equivalent replacement of the technical solutions recorded in the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A decision-making method for highway expansion based on life-cycle cost-benefit analysis, characterized in that, Includes the following steps: S1. Cost estimation for highway expansion: Collect estimated, preliminary, budgeted and final account data of existing highway expansion projects, estimate the construction cost of highway expansion based on the GM(1,1) grey system model, and obtain the predicted construction cost under different expansion methods; S2. Estimation of carbon emission costs during highway expansion: Based on the experience of existing highway expansion projects, estimate the material and energy consumption under different expansion methods; establish a method for estimating carbon emission costs during highway expansion based on different expansion methods and material and energy consumption. S3. Estimation of operational revenue loss during highway expansion, distinguishing between forced diversion and induced diversion, and estimating the operational revenue loss during highway expansion based on the lost traffic volume; S3 also includes: S3.1) Estimate the traffic loss during the highway expansion period; S3.1.1) Under mandatory diversion conditions, estimate the lost traffic volume according to the mandatory diversion ratio; S3.1.2) Under the induced diversion condition, the lost traffic volume is estimated based on evolutionary game theory; S3.1.2.1) Establish an evolutionary game model G={N, S, U}, where N, S, and U represent the players, strategy set, and payoff matrix in the evolutionary game, respectively: N = {Participant 1, Participant 2}; S = {Accept inducement, reject inducement}; The payment matrix is ​​as follows: Where: T1 and F1 represent the time cost and fuel cost when the participant simultaneously chooses to accept the guidance strategy; T4 and F4 represent the time cost and fuel cost when the participant simultaneously chooses to reject the guidance strategy; when the participant chooses different strategies, T2 and F2 represent the time cost and fuel cost when the participant chooses to accept the guidance strategy, and T3 and F3 represent the time cost and fuel cost when the participant chooses to reject the guidance strategy; W represents the toll incurred when the participant chooses to reject the guidance strategy and travels on the upgraded highway; S represents other payments incurred by the participant when traveling on the receiving road, such as payments caused by decreased traffic conditions and increased traffic interference when drivers switch to national or provincial highways. Before the upgrade, drivers tended to choose highways, so other payments on the receiving road should satisfy: ; S3.1.2.2) Conduct research on the reconstruction and expansion of roads, the roads receiving traffic, and the socio-economic conditions of the region, and assign values ​​to the payment matrix; S3.1.2.3) The replication dynamic equations are established as follows: ; in: ; ； ； S3.1.2.4) Set the replicated dynamic equation to 0, and solve for the possible equilibrium points of the system as x=0, x=1, x=N / M, where: ; ； S3.1.2.5) Analyze the stability of the equilibrium point if and only if and At this point, the system tends to stabilize; the possible scenarios are as follows: ① If the evolution tends to stabilize at x=0, then the induced diversion fails and the diversion scheme should be redesigned; ② The evolution tends to stabilize at x=N / M. Based on the payment matrix assignment in S3.1.2.2), N / M is estimated. The product of N / M and the current highway traffic volume is the traffic loss of the expanded highway under the induced diversion condition. S3.2) Estimate the loss of operating revenue during the highway expansion period based on the lost traffic volume, as shown in the following formula: ; Where: SQ represents the operational loss during the construction period of the expressway expansion project; Li represents the length of the i-th construction section during the construction period of the expressway expansion project; Qsi represents the traffic volume loss during the construction period of the i-th construction section of the expressway expansion project. Under the condition of forced diversion, Qsi is the product of the proportion of diverted vehicle types and the traffic volume of the existing expressway in the same time period. Under the condition of induced diversion, Qsi is the product of N / M and the traffic volume of the existing expressway in the same time period; d represents the expressway toll standard; k represents the number of construction sections in the expressway expansion corridor. S4. Estimation of operating revenue during the operation period of the expressway: OD survey, 24-hour traffic volume observation and socio-economic survey are conducted in the project impact area to predict the future traffic volume increment rate and growth rate. The Fratar model is used to calculate the trend OD distribution matrix of each traffic zone in the future. At the same time, the induced traffic volume is calculated. The user balance allocation model is used to calculate the expressway traffic volume after the expansion, and the operating revenue during the operation period is estimated from this. S5. Estimation of operating costs during the operation period of the expressway: The operating costs during the operation period are estimated based on personnel costs and maintenance expenses. S6. Estimation of carbon emission costs during the expansion and operation phases of highways: Calculate the fuel consumption of different vehicle models based on operating speed, and then calculate the carbon emissions and carbon emission costs during the expansion and operation phases. S7. Combining the conclusions of S1 to S6, using the approximation ideal solution ranking method, i.e., the TOPSIS method, to evaluate and analyze the highway expansion scheme based on the whole life cycle cost-benefit, including the following steps; S7.1) The total life-cycle cost of highway expansion projects mainly includes construction costs during the expansion period, carbon emission costs during the expansion period, loss of operating revenue during the expansion period, operating costs after the expansion is completed, and carbon emission costs during the operating period. It is a very small indicator, and the reciprocal method is used to make it positive. S7.2) Life-cycle revenue analysis of highway expansion projects, mainly including operating revenue during the operation period, is a very large indicator; S7.3) Standardize the extremely small indices after positive transformation and the extremely large indices before transformation to eliminate the influence of dimensions; S7.4) Based on the above cost-benefit composition, calculate the positive and negative ideal solutions. The positive ideal solution refers to the virtual solution composed of the maximum values ​​of each data after processing by S7.3, while the negative ideal solution refers to the virtual solution composed of the minimum values ​​of each attribute. S7.5) Use the TOPSIS method to score different highway expansion schemes and select the one with the highest score as the final decision scheme.

2. The highway expansion method decision-making method based on life-cycle cost-benefit analysis according to claim 1, characterized in that, The S2 process also includes: S2.1) Estimate the carbon emissions generated by the physicochemical properties of materials during the highway expansion period using the following formula: ; Where: e1 is the carbon emissions generated by the material's physical and chemical processes; i is the type of material; Mi is the consumption of material i; γi is the carbon emission coefficient of material i; S2.2) Estimate the carbon emissions generated by mechanical construction during the highway expansion period using the following formula; ； ； Where: e2 is the carbon emissions generated by mechanical construction; j is the type of energy; Rj is the activity data of energy j; βj is the carbon dioxide emission factor of energy j; NCVj is the lower heating value of energy j; FCj is the consumption of energy j; CCj is the carbon content per unit calorific value of energy j; OFj is the carbon oxidation rate of energy j. S2.3) Estimate the carbon emission cost of the highway expansion project based on the carbon emissions generated by the material physicochemical processes and the carbon emissions generated by mechanical construction during the expansion period, according to the following formula; ； ； Where: Scj is the total carbon emission cost of the highway expansion construction period; e is the total carbon emission generated during the highway expansion construction; and VC is the average unit price of carbon emission cost.

3. The highway expansion method decision-making method based on life-cycle cost-benefit analysis according to claim 2, characterized in that, The S6 process specifically includes: S6.1) Based on the expected service levels during the highway expansion and operation periods, estimate the operating speeds of different vehicle types; S6.2) Estimate the vehicle's fuel consumption per 100 kilometers based on its operating speed; Fuel consumption per 100 kilometers for passenger cars: N1=-0.21637v1+0.0013055v12+0.24808IRI+13.36580; Where: N1 is the fuel consumption of the passenger car per 100 kilometers, L / 100km; v1 is the operating speed of the passenger car, km / h; IRI is the International Roughness Index, m / km; Fuel consumption per 100 kilometers for medium-sized buses: N2=-0.45341v2+0.0032984v22+0.42424IRI+25.31578; In the formula: N2 is the fuel consumption of a medium-sized bus per 100 kilometers, L / 100km; v2 is the operating speed of the medium-sized bus, km / h; IRI is the International Roughness Index, m / km; Fuel consumption per 100 kilometers for large buses: N3=-1.07275v3+0.0084534v32+1.12121IRI+53.00515; Where: N3 is the fuel consumption of the large bus per 100 kilometers, L / 100km; v3 is the operating speed of the large bus, km / h; IRI is the International Roughness Index, m / km; Fuel consumption per 100 kilometers for small trucks: N4=-0.56612v4+0.004014v42+0.56222IRI+25.29872; Where: N4 is the fuel consumption of a small truck per 100 kilometers, L / 100km; v4 is the operating speed of the small truck, km / h; IRI is the International Roughness Index, m / km; Fuel consumption per 100 kilometers for medium-sized trucks: N5=-0.77007v5+0.0061404v52+1.45051IRI+34.50465; In the formula: N5 is the fuel consumption of a medium-sized truck per 100 kilometers, L / 100km; v5 is the operating speed of a medium-sized truck, km / h; IRI is the International Roughness Index, m / km; Fuel consumption per 100 kilometers for large trucks: N6=-1.64706v6+0.014388v62+1.58990IRI+62.90253; In the formula: N6 is the fuel consumption of a large truck per 100 kilometers, liters / 100km; v6 is the operating speed of the large truck, km / h; IRI is the International Roughness Index, m / km; S6.3) Calculate the total fuel consumption during the highway expansion and operation periods based on the vehicle's fuel consumption per 100 kilometers: ; In the formula: CR represents the total fuel consumption of vehicles during the highway expansion and operation periods, in liters; L represents the route length, in km; qki represents the cumulative traffic volume of the i-th type of vehicle during the expansion period, in vehicles; qyi represents the cumulative traffic volume of the i-th type of vehicle during the operation period, in vehicles; Nki represents the fuel consumption of the i-th type of vehicle during the expansion period, in liters / 100km; Nyi represents the fuel consumption of the i-th type of vehicle during the operation period, in liters / 100km. S6.4) Estimate carbon dioxide emissions based on the total fuel consumption of vehicles during the highway expansion and operation periods: Where: e3 represents the total carbon emissions from vehicle operation during the highway expansion and operation periods; and represents the fuel carbon emission factor. S6.5) Referring to the method in S2.3), the carbon emission estimation results are converted into carbon emission costs (SQC) as follows: ; Where: SQC is the total carbon emission cost of vehicles operating during the highway expansion and operation periods; e3 is the total carbon emissions generated by vehicles operating during the highway expansion and operation periods; and VC is the average unit price of carbon emission costs.

4. A decision-making system employing the highway expansion scheme method based on life-cycle cost-benefit calculation as described in claim 1, characterized in that, The system includes: Data Acquisition Module: Used to collect data on existing highway expansion projects, including estimates, preliminary estimates, budgets, and final accounts; data on material and energy consumption during the expansion period; regional socio-economic development; predicted traffic volume and distribution; vehicle operating speed; and data from the target calculation nodes of each step into the system. Data module: used to establish gray system models, carbon emission cost estimation models, expansion period operation revenue loss estimation models, operation period operation cost estimation models, operation period operation revenue estimation models, and to establish data processing flow; Data component module: Used to store tabular data and construct a visual classification on the front end using the tabular data, while also forming a DAG graph to build a logical diagram from the stored tabular data; Decision module: Utilizes the TOPSIS method to evaluate and make decisions on different expansion plans.

5. A computer device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1-3 or the functions of the system according to claim 4.

6. A computer-readable storage medium having a computer program stored thereon, said computer program, when executed by a processor, implementing the steps of the method according to any one of claims 1-3 or the function of the system according to claim 4.

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