CN114582121A - Road network level full-life maintenance optimization method considering carbon emission - Google Patents

Road network level full-life maintenance optimization method considering carbon emission Download PDF

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CN114582121A
CN114582121A CN202210139768.1A CN202210139768A CN114582121A CN 114582121 A CN114582121 A CN 114582121A CN 202210139768 A CN202210139768 A CN 202210139768A CN 114582121 A CN114582121 A CN 114582121A
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CN114582121B (en
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刘成龙
杜豫川
吴荻非
潘宁
高倩
翁梓航
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Abstract

The invention relates to a road network level full-life maintenance optimization method considering carbon emission, which mainly describes the maintenance optimization process of a full life cycle through a double-layer optimization model, and describes the influence of maintenance decision on the road network driving quality and the carbon emission in an upper layer model; the influence of maintenance operation on the traffic flow and the congestion state of the road network is described in the lower layer model, and the optimal maintenance scheme is obtained by solving the upper layer model and the lower layer model. Compared with the prior art, the method has the advantages of good road optimization effect, reduction of carbon emission and the like.

Description

Road network level full-life maintenance optimization method considering carbon emission
Technical Field
The invention relates to the technical field of pavement maintenance, in particular to a road network level full-life maintenance optimization method considering carbon emission.
Background
The driving quality of the road is an important parameter affecting the fuel efficiency and carbon emission of the vehicle. The research results of world banks show that: fuel consumption can be reduced by about 6% for each unit of increase in road flatness index. The traditional road maintenance decision method mainly aims at improving the road surface quality and the fund utilization rate, neglects the influence of maintenance work on the carbon emission of vehicles, has short maintenance decision time period, and fails to optimize the maintenance scheme from the perspective of the whole life cycle, thereby causing unnecessary resource waste.
The maintenance decision means of the road network level are mainly divided into three categories: poor road first-repair method, threshold control method and optimization control method. The first kind of bad road first repair method engineering is most widely applied, and mainly in the current maintenance period, the road with the worst quality in all roads is selected according to the capital condition for repair, the lower the quality, the higher the priority of road repair, the way can quickly complement the performance short board of the road network, but because the influence of road decay and traffic flow is not considered in the process, the problem of frequent repair and frequency damage of the road can be caused, even because the maintenance and road sealing time is too long, the problem of quick quality decay of the adjacent road can be caused; the second type of threshold control method is to set a road surface quality threshold, and repair is carried out when the road decays to a value below the threshold, the method is suitable for newly repairing the road, the overall quality of a road network can be generally improved, but the threshold control method causes insufficient maintenance funds in the later decay period, so that the method is difficult to popularize and use in a large range; the third type of optimization control method is to calculate and analyze the benefits obtained by different maintenance schemes under the limited capital constraint from the system perspective, so as to optimize the maintenance method and the maintenance time. The traditional optimization control method is mainly oriented to maintenance operation, the influence of maintenance activities on road network traffic flow is not considered, and the maintenance benefits under a long time period are difficult to analyze, so that the benefits of the method are difficult to realize.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a road network level full-life maintenance optimization method considering carbon emission.
The purpose of the invention can be realized by the following technical scheme:
a road network level full-life maintenance optimization method considering carbon emission comprises the following steps:
s1: confirming a maintenance period of the road network to be optimized, acquiring driving quality parameters of each road section of the road network to be optimized, and constructing a road surface performance decay model of each road section of the road network to be optimized;
s2: establishing a carbon emission estimation model, and calibrating parameters of the carbon emission model;
s3: establishing an objective function of a carbon emission estimation model;
s4: establishing an upper layer model of an optimization method, wherein the constraint conditions of the upper layer model comprise fund constraint, maintenance means uniqueness constraint, decay and maintenance state constraint;
s5: confirming a maintenance mode according to the running quality of the road surface;
s6: establishing a lower layer model of the optimization method, wherein the lower layer model is a user balance model;
s7: and solving the upper layer model and the lower layer model to obtain an optimal maintenance scheme.
Preferably, the road surface property decay model of each road section is a negative exponential decay model:
R＝R0{1-exp[-(A/t)B]}B
wherein R is the driving quality of the road section, R0The quality of the whole road section is shown, A is a life factor, B is a form factor, and t is the year.
Preferably, the carbon emission estimation model is
Figure BDA0003506215240000021
Wherein O is road carbon emission considering road surface running quality, a and b are carbon emission model parameters, AR、 BRThe model fixed parameters are estimated for carbon emissions, R is the travel mass of the road segment, and v is the flow.
Preferably, the carbon emission model parameters are calibrated by a least square method.
Preferably, in step S3, an objective function is set by using a trapezoidal area method, and the objective is that the sum of carbon emissions generated by all roads in the road network within the full life cycle is the lowest:
Figure BDA0003506215240000022
wherein Obj is an objective function, N is the total number of road sections, T is the full life cycle maintenance time, i is the road section number, T is the year, vi、Oi、τiFlow, carbon emission and time of flight, t, respectively, on the ith road+In the beginning of the tth year, (t +1)-At the end of the t +1 year.
Preferably, the capital constraints are:
Figure BDA0003506215240000031
wherein L isiThe maintenance length of the ith road is represented by p, which is the mark of the maintenance means, the poplar means is preventive maintenance when p is 1, the maintenance means is daily maintenance when p is 2, the maintenance means is major repair when p is 3, y is major repair when p is 3i,p(t) is a parameter indicating that the p-th maintenance measure is adopted on the ith road in the t year, and yi,pWhen (t) is 0, y is not usedi,pWhen (t) is 1, c isp(t) the price of the p-th curing means, r the discount rate, BgTotal maintenance costs for the full life cycle;
the unique constraint of the maintenance means is as follows:
Figure BDA0003506215240000032
the decay and maintenance state constraints are as follows:
Figure BDA0003506215240000033
Figure BDA0003506215240000034
wherein R isi(t+) The driving quality of the ith road at the beginning of the t year, A is a life factor, B is a form factor, Ri(t-) For the driving quality of the ith road at the end of the t year, Delta R (p, t) is the benefit of adopting the p planting section in the t year, vi(t) is the traffic volume of the ith road segment in the t year.
Preferably, the maintenance mode confirmation formula is:
yi,2(t)＝0,yi,3(t)＝0,if R(t-)∈(M1,5]
yi,3(t)＝0,if R(t-)∈(M2,M1]
yi,p(t)·(1-yi,p(t))＝0
wherein M is1Quality of travel parameter for major and minor repairs, M2The running quality parameters are used for daily maintenance.
Preferably, the user balance model is:
Figure BDA0003506215240000035
wherein v isi(t) is the traffic of the ith road section in the t year, tc (v)i(t)) is a road segment generalized cost, representing the sum of the time cost and comfort cost incurred by a user traveling the road segment,
Figure BDA0003506215240000041
wherein, tcoiFree flow time for section i, CiFor the traffic capacity of section i
Figure BDA0003506215240000042
Wherein, γ and
Figure BDA0003506215240000043
the value parameters of the road section driving comfort and the passing time are obtained.
Preferably, in step S7, an active set semi-heuristic algorithm is used to solve the upper and lower layer models.
Preferably, in step S1, the topology structure diagram of the road network to be optimized is obtained, and the road information of the road network to be optimized is obtained according to the topology structure diagram.
Compared with the prior art, the method fully considers the influence of road decay and traffic flow in the road-network level roads, combines the influence of maintenance fund and maintenance activity on the road-network traffic flow, and can directly calculate the recommended maintenance means for each road section in each year in a long T period, thereby reducing the carbon emission generated by the road network while ensuring the driving quality of the road section, solving the problems of poor global property and low fund utilization rate of the traditional maintenance means, having high calculation precision and good accuracy, effectively providing optimization decision for the optimization of the roads, and improving the ecological benefit and ensuring the overall road quality.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a topological graph of a road network according to an embodiment of the present invention;
FIG. 3 is a graph illustrating the relationship between maintenance funds and the variation of road network carbon emissions in an embodiment of the present invention;
fig. 4 is a relationship between maintenance funds and the average traveling quality of the road network according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and the specific embodiments. Note that the following description of the embodiments is merely a substantial example, and the present invention is not intended to be limited to the application or the use thereof, and is not limited to the following embodiments.
Examples
A road network level full-life maintenance optimization method considering carbon emission is characterized in that a double-layer optimization algorithm is established for road network vehicle carbon emission by utilizing a road surface performance decay model and a carbon emission estimation algorithm based on current driving quality parameters of road sections in a road network, service quality is guaranteed, and meanwhile road network full-life carbon emission is reduced, so that the problems of unreasonable road network maintenance time and excessive carbon emission caused by improper maintenance means are solved.
The method describes the influence of maintenance decisions (when, what road section and what way) made by a manager on the road network driving quality and carbon emission in an upper layer model; the influence of the maintenance work on the traffic flow and the traffic jam state of the road network is described in the lower model. As shown in fig. 1, the method mainly includes the following steps in the implementation process:
(1) obtaining road network information of a road network to be optimized, drawing a topological graph of the road network to be optimized, specifically, confirming that the maintenance period of the road network to be optimized is T years, and obtaining a driving quality parameter R of each road section of the road network to be optimized0And constructing a road surface performance decay model of each road section of the road network to be optimized.
In the invention, the maintenance period is not less than 5 years, and the whole life cycle is not more than 30 years in order to avoid overlarge calculation amount of solution.
The road surface performance decay model of each road section is a negative exponential decay model:
R＝R0{1-exp[-(A/t)B]}B
wherein R is the driving quality of the road section, R0In order to ensure the driving quality of the whole road section, wherein A is a life factor, B is a form factor, t is the year, the life factor A and the form factor B are related to parameters such as traffic flow, pavement materials, paving process, structure thickness and the like, in the embodiment, an empirical formula is selected:
Figure BDA0003506215240000051
wherein v is the road section flow and ol is the initial deflection of the road section.
Further, in the step (1), a topological structure is drawn according to the road network condition to be optimized, wherein a node set is Q, a road section set formed by the nodes is G, and different sequences of the two nodes respectively represent two driving directionsFor example, node 1-2 forms link 1, node 2-1 forms link 2, and links 1 and 2 are each in different directions of the same road. Collecting current driving quality set R of all road sections in road section set0The user demand matrix of the road network is OD, and the current R is used as the basis0And the condition and the road network OD, calculating a flow set V of each road section under the initial condition, acquiring a traffic capacity set C of each road section of the road network, then determining decay factor sets A and B of each road section of the road network according to the flow of each road section, and estimating the performance decay condition of each road section in the road network G in the time T under the condition of not carrying out maintenance according to the road surface performance decay model. Making clear the investment of the whole life maintenance planning period BgThe capital discount rate r of the current region should be referenced to the current discount rate of the design year and the price C of different maintenance meanspRoad section running quality threshold value M required for carrying out different maintenance means1,M2Calculating the value parameters gamma and gamma of the driving comfort and the passing time of the road section by using the local oil charge and the average user time cost
Figure BDA0003506215240000052
(2) Establishing a carbon emission estimation model:
Figure BDA0003506215240000053
wherein O is road carbon emission considering road surface running quality, a and b are carbon emission model parameters, AR、 BREstimating model fixed parameters for carbon emission, wherein R is the driving quality of a road section, and v is the flow;
and calibrating the carbon emission model parameters. Specifically, road sections of different road surfaces are selected from a road network to be optimized, the running quality R, the flow v and the carbon emission O of the road sections are collected, and model parameters a and b are calibrated through a least square method. In this example, R ∈ [0,5 ]]Wherein 5 is the best running quality, and 0 is the worst running quality, AR＝6.122，BR1.963. In this embodiment, the road network of not less than 10 road segments is determined to perform parameter calibration.
In this embodiment, the carbon emission of each year in the full life cycle T is calculated using a trapezoidal formula.
(3) Setting a target function of the carbon emission estimation model by utilizing a trapezoidal area method, wherein the target is that the sum of carbon emissions generated by all roads in the road network in the whole life cycle is the lowest:
Figure BDA0003506215240000061
wherein Obj is an objective function, N is the total number of road sections, T is the full life cycle maintenance time, i is the road section number, T is the year, vi、Oi、τiFlow, carbon emission and time of flight, t, respectively, on the ith road+In the beginning of the tth year, (t +1)-At the end of the t +1 st year.
(4) And establishing an upper layer model of the optimization method, wherein the upper layer is a decision maker layer, and the constraint conditions comprise capital constraint, maintenance means uniqueness constraint, decay and maintenance state constraint.
The capital constraint is that the sum of all maintenance expenses of the full life cycle T does not exceed the total budget Bg：
Figure BDA0003506215240000062
Wherein L isiThe maintenance length of the ith road is represented by p, the mark is the maintenance means, p is {1,2,3}, the preventive maintenance is carried out by the poplar means when p is 1, the daily maintenance is carried out by the maintenance means when p is 2, the major and middle maintenance is carried out by the maintenance means when p is 3, y is carried out by the maintenance means when p is 3i,p(t) is a parameter indicating that the p-th maintenance measure is adopted on the ith road in the t year, and yi,pWhen (t) is 0, y is not usedi,pWhen (t) is 1, c isp(t) the price of the p-th curing means, r the discount rate, BgTotal maintenance costs for the full life cycle;
the uniqueness constraint of the maintenance means is that one road can only adopt one of three types of maintenance means at the same time:
Figure BDA0003506215240000063
the decay and maintenance state constraint is that the road surface running quality decays according to a road surface performance decay model under the condition of no maintenance; under the maintenance condition, the road surface running quality is recovered to the optimal state:
Figure BDA0003506215240000064
Figure BDA0003506215240000071
wherein R isi(t+) The quality of the ith road at the beginning of the t year, A is a life factor, B is a form factor, Ri(t-) For the driving quality of the ith road at the end of the t year, Delta R (p, t) is the benefit of adopting the p planting section in the t year, vi(t) is the traffic volume of the ith road segment in the t year.
(5) And confirming the maintenance mode according to the running quality of the road surface. The curing means considered in this embodiment are mainly classified into three types: preventive maintenance, daily maintenance and major and middle maintenance, wherein the specific maintenance means is selected according to the current pavement state; the construction time of the maintenance means is calculated according to the construction capacity of the current area, and the confirmation formula of the maintenance mode is as follows:
yi,2(t)＝0,yi,3(t)＝0,if R(t-)∈(M1,5]
yi,3(t)＝0,if R(t-)∈(M2,M1]
yi,p(t)·(1-yi,p(t))＝0
wherein M is1Quality of travel parameter for major and minor repairs, M2The running quality parameters are used for daily maintenance.
(6) Establishing a lower layer model of the optimization method, wherein the lower layer model is a static deterministic user equilibrium model, and a road resistance function is formed by the influence of road surface driving quality and the influence of travel time:
wherein the objective function is
Figure BDA0003506215240000072
Wherein v isi(t) is the traffic of the ith road section in the t year, tc (v)i(t)) is a road segment generalized cost, representing the sum of the time cost and comfort cost incurred by a user traveling the road segment,
the user transit time is estimated as:
Figure BDA0003506215240000073
wherein, tcoiFree flow time for section i, CiFor the traffic capacity of section i
Figure BDA0003506215240000074
Wherein, γ and
Figure BDA0003506215240000075
the unit is unified for the value parameters of the road section driving comfort and the passing time.
And (4) forming a double-layer optimization model by the upper layer model and the lower layer model in the steps (6), wherein the model aims to ensure that the carbon emission of the road network in the whole life cycle is the lowest, and the optimized independent variable is whether the ith road in the t year in the road network G is maintained in the pth mode. The double-layer optimization model is non-convex non-concave non-linear, a semi-heuristic algorithm can be adopted to convert the independent variable of the model into a binary system, the initial model solution can be set to be zero, the descending direction of the model is determined by calculating the Lagrange multiplier of each group of solutions, the feasible solutions are adjusted until the model has no descending direction, and the optimal solution for the whole life maintenance is obtained. The variable of the lower-layer optimization model is road section flow, and the flow is a calculation parameter of the upper-layer model. In the calculation process, the lower-layer flow condition is determined according to the t-year maintenance scheme, and the upper-layer road surface decay condition is calculated according to the flow condition. In order to consider the influence of construction time, the annual passing time is used for reducing the maintenance road-sealing time, the annual passing time is divided by the annual passing time, the discount coefficient is calculated, and the road section passing capacity is reduced.
(7) And (4) solving the double-layer optimization model described in the steps (4), (5) and (6), and solving the model by adopting an active set semi-heuristic algorithm, so that a certain maintenance mode is adopted for a certain road section in a certain year.
Further specifically, in this embodiment, a planned road network is selected as shown in fig. 2, the traffic capacity of road segments and the user OD are shown in tables 1 and 2, and the road network is a newly-built road RQI0Are all 5, M1,M22.435 and 4.195, price CpThe curing period T is 115000 yuan/km (p is 1), 325000 yuan/km (p is 2), 894000 yuan/km (p is 3), the benefit of the curing means is 5 years (p is 1), 8 years (p is 2), 20 years (p is 3), and 10 years.
Table 1 road network traffic capacity meter
Figure BDA0003506215240000081
TABLE 2 road network demand OD
Figure BDA0003506215240000082
Figure BDA0003506215240000091
The relationship between carbon emission and road surface running quality calibrated by a control variable experiment is as follows:
Figure BDA0003506215240000092
γ and
Figure BDA0003506215240000093
respectively 0.0601 yuan/(RQI. mile) and 15.49 yuan/h, and the discount rate r is 0.08.
(2) Model building and calculation: and putting the calibration information and the road network information into a double-layer model, and solving the model by using an active set semi-heuristic algorithm.
(3) Model accuracy evaluation
The carbon emission of the road network is calculated by comparing the solved model optimization solution with the traditional bad road first repairing method and the threshold control method respectively as shown in fig. 3. It can be clearly seen that with the increase of the expenditure, the carbon emission is gradually reduced, the ecological benefit is gradually improved, and the carbon emission of the method provided by the invention is the lowest under the condition of limited funds. Fig. 4 shows the change of the average driving quality of the road network with the increase of maintenance capital, which indicates that the technical method provided by the invention can ensure the overall road quality while improving the ecological benefit.
The above embodiments are merely examples and do not limit the scope of the present invention. These embodiments may be implemented in other various manners, and various omissions, substitutions, and changes may be made without departing from the technical spirit of the present invention.

Claims (10)

1. A road network level full-life maintenance optimization method considering carbon emission is characterized by comprising the following steps:
s1: confirming a maintenance period of the road network to be optimized, acquiring driving quality parameters of each road section of the road network to be optimized, and constructing a road surface performance decay model of each road section of the road network to be optimized;
s2: establishing a carbon emission estimation model, and calibrating parameters of the carbon emission model;
s3: establishing an objective function of a carbon emission estimation model;
s4: establishing an upper layer model of an optimization method, wherein the constraint conditions of the upper layer model comprise fund constraint, maintenance means uniqueness constraint, decay and maintenance state constraint;
s5: confirming a maintenance mode according to the running quality of the road surface;
s6: establishing a lower layer model of the optimization method, wherein the lower layer model is a user balance model;
s7: and solving the upper layer model and the lower layer model to obtain an optimal maintenance scheme.
2. The carbon emission-considered road network level full-life maintenance optimization method according to claim 1, wherein the road surface performance decay model of each road section is a negative exponential decay model:
R＝R0{1-exp[-(A/t)B]}B
wherein R is the driving quality of the road section, R0The quality of the whole road section is shown, A is a life factor, B is a form factor, and t is the year.
3. The method of claim 1, wherein the carbon emission estimation model is a road network-level life-saving maintenance optimization method taking carbon emission into account
Figure FDA0003506215230000011
Wherein O is road carbon emission considering road surface running quality, a and b are carbon emission model parameters, AR、BRThe model fixed parameters are estimated for carbon emissions, R is the travel mass of the road segment, and v is the flow.
4. The road network level full-life maintenance optimization method considering carbon emission according to claim 3, wherein the carbon emission model parameters are calibrated by a least square method.
5. The method for optimizing maintenance of road network level and whole life considering carbon emission according to claim 3, wherein the step S3 is performed by using a trapezoidal area method to set an objective function, wherein the objective function is to minimize the sum of carbon emissions generated by all roads in the road network during the whole life cycle:
Figure FDA0003506215230000021
wherein Obj is an objective function, N is the total number of road sections, T is the full life cycle maintenance time, i is the road section number, T is the year, vi、Oi、τiFlow, carbon emission and time of flight, t, respectively, on the ith road+In the beginning of the tth year, (t +1)-At the end of the t +1 year.
6. The method of claim 5, wherein the capital constraints are:
Figure FDA0003506215230000022
wherein L isiThe maintenance length of the ith road is represented by p, the mark is the maintenance means, p is {1,2,3}, the preventive maintenance is carried out by the poplar means when p is 1, the daily maintenance is carried out by the maintenance means when p is 2, the major and middle maintenance is carried out by the maintenance means when p is 3, y is carried out by the maintenance means when p is 3i,p(t) is a parameter indicating that the p-th maintenance measure is adopted on the ith road in the t year, and yi,pWhen (t) is 0, y is not usedi,pWhen (t) is 1, c isp(t) the price of the p-th curing means, r the discount rate, BgTotal maintenance costs for the full life cycle;
the unique constraint of the maintenance means is as follows:
Figure FDA0003506215230000023
the decay and maintenance state constraint is as follows:
Figure FDA0003506215230000024
Figure FDA0003506215230000025
wherein R isi(t+) The quality of the ith road at the beginning of the t year, A is a life factor, B is a form factor, Ri(t-) For the driving quality of the ith road at the end of the t year, Delta R (p, t) is the benefit of adopting the p planting section in the t year, vi(t) is the traffic volume of the ith road segment in the t year.
7. The road network level full-life maintenance optimization method considering carbon emission according to claim 6, wherein the confirmation formula of the maintenance mode is as follows:
yi,2(t)＝0,yi,3(t)＝0,if R(t-)∈(M1,5]
yi,3(t)＝0,if R(t-)∈(M2,M1]
yi,p(t)·(1-yi,p(t))＝0
wherein, M1Quality of travel parameter for major and minor repairs, M2The running quality parameters are used for daily maintenance.
8. The method of claim 6, wherein the customer balance model is:
Figure FDA0003506215230000031
wherein v isi(t) is the traffic of the ith road section in the t year, tc (v)i(t)) is a road segment generalized cost, representing the sum of the time cost and comfort cost incurred by a user traveling the road segment,
Figure FDA0003506215230000032
wherein, tcoiFree flow time for section i, CiFor the traffic capacity of section i
Figure FDA0003506215230000033
Wherein, γ and
Figure FDA0003506215230000034
is a value parameter of the road section driving comfort and the passing time.
9. The method for road network level full-life maintenance optimization considering carbon emission according to claim 1, wherein in the step S7, an active set semi-heuristic algorithm is adopted to solve the upper and lower layer models.
10. The carbon emission-considered road network-level life-saving maintenance optimization method according to claim 1, wherein in step S1, a topology structure diagram of the road network to be optimized is obtained, and the road information of the road network to be optimized is obtained according to the topology structure diagram.
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