# Evaluation Method of Municipal Road Construction Quality Based on Carbon Emissions using Genetic Algorithm

Authors: Bing Hou; Chunyang Mao; Liang Xu; Botao Sun; Jie Zhang
Journal: Mathematical Problems in Engineering
 (2022)

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## Abstract

With the rapid development of the world economy, the infrastructure of the nations is improving day by day. The transportation system is a backbone of infrastructure of any country. Transportation plays a vital role in environmental issues as well. For a country like China, municipal road plays an important role in the transportation system but the construction should be environmental friendly. The municipal road construction should be free from carbon emissions and the road should be of good quality to increase the efficiency of road transportation. The construction quality of the road is affected by the temperature, type of material, eco-friendly material, and material quality which makes the construction quality uncertain. The environmental issues are alarming. The natural resources are exploited in order to strengthen the infrastructure of any country. There is a need to find the ways to use eco-friendly material for infrastructure in all the developing nations. The traditional quality evaluation methods do not preprocess the construction quality data to keep track of the composition of environmental friendly material in the overall material. The collected dynamic monitoring data of municipal road construction quality are sparse and the key data is not accurate to evaluate the material and its consequences on the environment. Now is the time to pay attention to the environmental issues before any economic and social progress. The evaluation method of municipal road construction quality based on an improved genetic algorithm (GA) is proposed in this paper by considering carbon emissions to keep the environment free from pollution. In the process of quality evaluation of load, a spanning tree constraint method is also introduced to form a related constraint relationship. The improved GA is used to calculate municipal road construction flow parameters to ensure the optimal evaluation results. Experimental results show that the evaluation method is accurate and reliable and meets the requirement of the current era where environment issues are at priority.


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## Body

## 1. Introduction

Municipal roads refer to the roads that connect with roads outside the city, lead to various city areas, and provide transportation in the town [1]. These roads use the functions for pedestrians and provide external transportation for all type of vehicles [2]. As a vital part of urban planning, municipal roads can be divided into trunk roads, subtrunk roads, expressways, and feeder roads [3]. The construction of roads involves different kinds of materials and nowadays research is going on to protect the environment by using eco-friendly material or waste plastic based material to reduce carbon emissions [4]. Therefore, the eco-friendly material based high-quality municipal roads can beautify the city and meet the normal operation of urban traffic needs by preserving the environment [5]. Many authors have presented their research ideas where plastic waste or other materials can be used for the construction of roads where carbon emissions can be reduced and natural resources can also be preserved.In [6], authors have proposed the scheduling of urban road projects based on the multiattribute based approaches such as DEA and TOPSIS. By using these methods, the roads in urban area can construct on or before time and many other factors such as usage of material and environmental factors are also considered during decision making of constructions of roads. These statistical methods such as DEA and TOPSIS have proved to be the best methods for deciding the factors influencing the constructions of the roads. In [7], authors have proposed the monitoring process of street and road network using artificial intelligence (AI). This AI based mechanism monitors the road quality and also keeps track of the material used for the construction of roads and if the material is contributing to increasing the carbon emissions then this method provides the alert. This method can be effectively used to monitor the road quality after completing the project.While constructing the roads, there are many security problems which can affect the quality and risk of the constructors including environmental factors. In [8], authors have proposed smart cone based system for providing timely alerts and warning to the people involved in the construction of roads. This system not only keeps eye on the quality of the construction but also takes care of safety issues related to the constructions of the roads for preserving the green environment. In [9], the authors have proposed a method to construct the road based on the traffic. The authors have used the shortest path with capacity limitation algorithm. This method again allows protection of environment to guide the channelization of traffic. In [10], authors investigate and analyze the factors influencing the rural area road development. The factors are analyzed from multiple perspectives such as reliability, safety, environmental issues, and traffic needs. In [11], authors have proposed a bidding conditions and bidding documents method which is useful in village road construction. However, this paper does not focus on environmental issues; it is only considering the cost affective factors to construct roads in rural areas.With the improvement of transportation infrastructure and the development of intelligent transportation systems, the evaluation of municipal road construction quality has become a hot topic in the field of transportation [12]. In [13], the authors put forward an evaluation method for selecting the best repair process for road machinery and pointed out the high efficiency repairing model for road construction machinery by reducing the carbon emissions. The operation characteristics of reliable and high-precision equipment in road and construction engineering require a high cost to maintain the machine’s maneuverability. The replacement cost of functional components is very high due to the primary use of foreign manufacturing equipment and replacement issues. In order to ensure the reliable and safe operation of road construction machinery, it is necessary to solve these problems systematically [14]. By establishing the original model of energy-saving technology optimization, the solution of the system is determined which is aiming at the highest quality of repaired parts.In [15], the authors have presented the evaluation method of construction effect of dredged surface soil cement on the road and set up cement soil on the base of highway subgrade. The basis of theoretical research on the economic benefits of using modified soils is selecting methods for evaluating this material’s economic benefits and their subsequent description. The calculation includes determining the interests of road users, the current period, and the one-time cost of using various pavement constructions during the charging period. The environmental issues are also considered. The results show the relationship between economic efficiency and traffic intensity of various structures. The use of water-repellent surface cement soil will reduce the financial cost of road construction, protect the environment, improve the quality, and increase federal and regional road overhaul time. In addition, the construction technology and supervision level of municipal road projects have improved, and the quality of municipal road projects has also made a significant leap [16].As one of the many aspects included in road construction, municipal road projects have many particularities different from those of other road construction projects because these projects are aiming to ease the lives of people, protecting the environment, and minimizing the infrastructure cost and safety of the users. In addition, municipal road construction shall be synchronized with the construction of public facilities and transportation facilities in the city [14]. These are the particular problems that do not exist in other road construction, which increases the difficulty and complexity of municipal road construction because there are often some special quality problems in municipal road construction. There are still some unqualified projects in the construction of municipal roads which are not considering environmental factors while planning the design of roads. This paper is focusing on all these problems and presenting an evaluation method to analyze whether the construction of roads has considered all the necessary factors for safety of users including environmental factors. An evaluation method of municipal road construction quality evaluation is put forward to avoid the above defects. The improved GA is used to evaluate the flow parameters of municipal roads. The highlights are given below.(i)
The evaluation method based on a soft computing technique is introduced in this paper. The evolutionary capability of genetic algorithm (GA) is used for evaluating the parameters of municipal road construction quality(ii)
An improved GA is proposed in this paper for the evaluation process and many factors are considered including environmental factors for the evaluation process(iii)
In the process of quality evaluation of load, a spanning tree constraint method is also utilized in this article to form a related constraint relationship(iv)
The improved GA evaluates the municipal road construction flow parameters to ensure the optimal evaluation results(v)
The empirical results show that the evaluation method is accurate and reliable and meets the requirement of the current era where environmental problems are given priorityThe next section discusses the improved GA for evaluation process. The third and fourth sections also explained the subparts of the proposed work. Fifth section elaborated results and sixth section concludes the paper work.


## 2. Improved Genetic Algorithm (GA) Based Analysis

### 2.1. Principles of Genetic Algorithms

Through natural selection and genetic theory as a basic condition, they are combined with chromosome arbitrary information exchange mechanism and the rule of survival of the fittest in the process of biological evolution. Detailed algorithmic process is shown in Figure1.Figure 1
Genetic method flowchart.


### 2.2. Improved Genetic Method

However, in the later stage of evolution, a large number of individuals try to achieve the optimal position in the solution space; it is easy to trap into local optima during evolution. It may lead to inbreeding, resulting into lesser diversity in individuals. Usually, the test cases generated by obtaining the best local solution cannot achieve satisfactory coverage. So, some mechanisms are to be used to improve the situation. Therefore, this paper adds Tabu search and uses the strong memory ability of this method to replace the inferior individuals with the superior ones within the prescribed range. Genetic approaches have the local super search ability of Tabu search method, and it enhances the probability of generating the best solution. The specific procedures are as follows:(1)
Initialization parameters; population Pop, length of Tabu listL, population size Pop Size(2)
Selecting individuals within the operating population(3)
Manipulating individuals within the population using adaptive mutations and adaptive crossovers(4)
Transferring the eliminated individuals by replacing the eliminated individuals with new ones(5)
Generating a new generation of populations and then transfer to step 2


### 2.3. Module Design of Tabu Search

The similarity between two individuals is represented byS, and the specific formula is given in the following equation:(1)S=∑1mai−aj2.In equation (1), ai is the best value in Tabu search and aj is the reference value in Tabu search. Take any point as the center sphere, and then call any point in the sphere which is not the center point its neighbor. Adding Tabu search to the genetic approach allows individuals to use the Tabu test for the deletion of genes with poor fitness. Those individuals are targeted whose fitness value is poorer than the parents. In addition, individuals with efficient genes but poor fitness have more opportunities to participate in mutation and crossover to avoid or delay convergence and improve the search power of GA [15].(1)
The selection method and the size of the neighborhood solution set have a great impact on the parameter performance of the algorithm. At present, the best choice will be made in the solution field. If the choice is too large, the amount of calculation will be relatively large. On the contrary, if the choice is too small, the probability of high-quality solution will be reduced. Therefore, the main way to generate a domain is to take the current solutionx as the center and then use R as the radius to generate neighborhood given in the following equation:(2)FF=x′−x.In equation (2), x′ represents the discretized neighborhood solution arbitrarily generated by the current solution x.(2)
In the evolution process of genetic methods, after each iteration, the generation of new population is formed which may be superior or inferior to the present population [16], the individuals below γ level are eliminated, and these eliminated individuals are set as aiai,a2,…,an. The Tabu search method is used to complete the alternative search and then search in the neighborhood. The steps are as follows:Step 1: Preprocess the data of a solutionFFnow=ai and Tabu listStep 2: Select the best individualBest in β, and when fBest>FFnow and S>ε at the same time, FFnow=Best and Best will be added to L; otherwise, if Best∉L and FFnow=Best, L will be modifiedStep 3: If the condition is met, the search will be terminated; otherwise, it needs to be transferred to step 2


### 2.4. Genetic Module Design

The concrete improvement in genetic method is based on three basic operators as follows.


#### 2.4.1. Operator Selection

The survival rule of the fittest is selected to ensure the distribution of individuals in the population. The fitness value of each individual is subtracted from the worst fitness value of the individual in the group, and this value is used as the criterion for selecting the individual. This method is superior to the traditional roulette method. After the best individual is selected, the probability of mutation and crossover is increased significantly. The worst individual will lose the genetic opportunity, and the overall convergence speed will increase rapidly. The specific method for calculating the selection of the probability is given in the following equation:(3)Pi=FF∑i=1fi−fworst.In equation (3), fi represents the fitness of the selected individual, and fworst represents the fitness of the worst individual.


#### 2.4.2. Crossover and Variation

The crossover rate and mutation rate of the GA are fixed, mainly as a random search. There is specific blindness which is likely to lead to the existence of relatively high fitness individuals damaged. Therefore, it is necessary to repair the damaged individuals, use adaptive operators, adjust individual dynamics, check whether the crossover probability of mutation is effective, and overcome the existing defects. There are the global optimal solutions, efficiency, and better robustness. The specific crossover ratePc and mutation rate Pm are given in the following equation:(4)Pc=Pc1Pc1−Pc2fmax−favgf′−favg,favg≤f′<fma,Pc1,f′<favg.In equation (4), fmax represents the maximum fitness within the population, favg represents the average fitness of all populations, f′ represents the larger fitness within the individuals requiring crossover, and f represents the fitness value of individuals requiring variation.


#### 2.4.3. Preservation of Elites

The best individuals within a population are replicated into the next generation of the population to become the next generation of new individuals [17].


## 2.1. Principles of Genetic Algorithms

Through natural selection and genetic theory as a basic condition, they are combined with chromosome arbitrary information exchange mechanism and the rule of survival of the fittest in the process of biological evolution. Detailed algorithmic process is shown in Figure1.Figure 1
Genetic method flowchart.


## 2.2. Improved Genetic Method

However, in the later stage of evolution, a large number of individuals try to achieve the optimal position in the solution space; it is easy to trap into local optima during evolution. It may lead to inbreeding, resulting into lesser diversity in individuals. Usually, the test cases generated by obtaining the best local solution cannot achieve satisfactory coverage. So, some mechanisms are to be used to improve the situation. Therefore, this paper adds Tabu search and uses the strong memory ability of this method to replace the inferior individuals with the superior ones within the prescribed range. Genetic approaches have the local super search ability of Tabu search method, and it enhances the probability of generating the best solution. The specific procedures are as follows:(1)
Initialization parameters; population Pop, length of Tabu listL, population size Pop Size(2)
Selecting individuals within the operating population(3)
Manipulating individuals within the population using adaptive mutations and adaptive crossovers(4)
Transferring the eliminated individuals by replacing the eliminated individuals with new ones(5)
Generating a new generation of populations and then transfer to step 2


## 2.3. Module Design of Tabu Search

The similarity between two individuals is represented byS, and the specific formula is given in the following equation:(1)S=∑1mai−aj2.In equation (1), ai is the best value in Tabu search and aj is the reference value in Tabu search. Take any point as the center sphere, and then call any point in the sphere which is not the center point its neighbor. Adding Tabu search to the genetic approach allows individuals to use the Tabu test for the deletion of genes with poor fitness. Those individuals are targeted whose fitness value is poorer than the parents. In addition, individuals with efficient genes but poor fitness have more opportunities to participate in mutation and crossover to avoid or delay convergence and improve the search power of GA [15].(1)
The selection method and the size of the neighborhood solution set have a great impact on the parameter performance of the algorithm. At present, the best choice will be made in the solution field. If the choice is too large, the amount of calculation will be relatively large. On the contrary, if the choice is too small, the probability of high-quality solution will be reduced. Therefore, the main way to generate a domain is to take the current solutionx as the center and then use R as the radius to generate neighborhood given in the following equation:(2)FF=x′−x.In equation (2), x′ represents the discretized neighborhood solution arbitrarily generated by the current solution x.(2)
In the evolution process of genetic methods, after each iteration, the generation of new population is formed which may be superior or inferior to the present population [16], the individuals below γ level are eliminated, and these eliminated individuals are set as aiai,a2,…,an. The Tabu search method is used to complete the alternative search and then search in the neighborhood. The steps are as follows:Step 1: Preprocess the data of a solutionFFnow=ai and Tabu listStep 2: Select the best individualBest in β, and when fBest>FFnow and S>ε at the same time, FFnow=Best and Best will be added to L; otherwise, if Best∉L and FFnow=Best, L will be modifiedStep 3: If the condition is met, the search will be terminated; otherwise, it needs to be transferred to step 2


## 2.4. Genetic Module Design

The concrete improvement in genetic method is based on three basic operators as follows.


### 2.4.1. Operator Selection

The survival rule of the fittest is selected to ensure the distribution of individuals in the population. The fitness value of each individual is subtracted from the worst fitness value of the individual in the group, and this value is used as the criterion for selecting the individual. This method is superior to the traditional roulette method. After the best individual is selected, the probability of mutation and crossover is increased significantly. The worst individual will lose the genetic opportunity, and the overall convergence speed will increase rapidly. The specific method for calculating the selection of the probability is given in the following equation:(3)Pi=FF∑i=1fi−fworst.In equation (3), fi represents the fitness of the selected individual, and fworst represents the fitness of the worst individual.


### 2.4.2. Crossover and Variation

The crossover rate and mutation rate of the GA are fixed, mainly as a random search. There is specific blindness which is likely to lead to the existence of relatively high fitness individuals damaged. Therefore, it is necessary to repair the damaged individuals, use adaptive operators, adjust individual dynamics, check whether the crossover probability of mutation is effective, and overcome the existing defects. There are the global optimal solutions, efficiency, and better robustness. The specific crossover ratePc and mutation rate Pm are given in the following equation:(4)Pc=Pc1Pc1−Pc2fmax−favgf′−favg,favg≤f′<fma,Pc1,f′<favg.In equation (4), fmax represents the maximum fitness within the population, favg represents the average fitness of all populations, f′ represents the larger fitness within the individuals requiring crossover, and f represents the fitness value of individuals requiring variation.


### 2.4.3. Preservation of Elites

The best individuals within a population are replicated into the next generation of the population to become the next generation of new individuals [17].


## 2.4.1. Operator Selection

The survival rule of the fittest is selected to ensure the distribution of individuals in the population. The fitness value of each individual is subtracted from the worst fitness value of the individual in the group, and this value is used as the criterion for selecting the individual. This method is superior to the traditional roulette method. After the best individual is selected, the probability of mutation and crossover is increased significantly. The worst individual will lose the genetic opportunity, and the overall convergence speed will increase rapidly. The specific method for calculating the selection of the probability is given in the following equation:(3)Pi=FF∑i=1fi−fworst.In equation (3), fi represents the fitness of the selected individual, and fworst represents the fitness of the worst individual.


## 2.4.2. Crossover and Variation

The crossover rate and mutation rate of the GA are fixed, mainly as a random search. There is specific blindness which is likely to lead to the existence of relatively high fitness individuals damaged. Therefore, it is necessary to repair the damaged individuals, use adaptive operators, adjust individual dynamics, check whether the crossover probability of mutation is effective, and overcome the existing defects. There are the global optimal solutions, efficiency, and better robustness. The specific crossover ratePc and mutation rate Pm are given in the following equation:(4)Pc=Pc1Pc1−Pc2fmax−favgf′−favg,favg≤f′<fma,Pc1,f′<favg.In equation (4), fmax represents the maximum fitness within the population, favg represents the average fitness of all populations, f′ represents the larger fitness within the individuals requiring crossover, and f represents the fitness value of individuals requiring variation.


## 2.4.3. Preservation of Elites

The best individuals within a population are replicated into the next generation of the population to become the next generation of new individuals [17].


## 3. Evaluation Method for Construction Quality of Municipal Roads

### 3.1. Characteristic Analysis of Municipal Road Construction

Engineering quality refers to the engineering safety, environmental safety, engineering economic practicality, and aesthetic degree required by national laws, regulations, technical standards, and design documents [18]. This phenomenon is including three levels of construction quality, work quality, and working procedure quality to consider while designing an evaluation system [19]. Relevant construction should be in accordance with the quality requirements and environment friendly standards for safeguarding the natural resources and human beings. The construction entities comprehensively consider the technical possibility and economic applicability of the construction and also consider the balance between the conditions permitted by social production and the actual development of the projects. The motive is to reduce the project cost, to reduce the carbon footprints generated by the construction, and to improve the project quality through the most economical construction methods [20].The term “work quality” refers to the level and degree of perfection of the work related to project quality undertaken by the engineering constructor which is embodied in the whole process of technical engineering activities and is comprehensively embodied through the preservation of natural resources, reduction in carbon footprints, quality of construction, and economic efficiency of the project [21]. Each link and each aspect of the project in the forming process will comprehensively reflect the project’s quality. In order to guarantee the project quality, all the project participants should improve their work quality and strictly control all the influencing factors of the construction project to improve the project quality level without hampering the environment [22]. The process quality becomes an important factor in the construction process operations where other factors such as environment, operation process, machinery, labor force, and the eco-friendly material significantly appraise the quality. The judgment of construction quality of municipal roads refers to the judgment of quality status according to the connectivity reliability parameters of municipal roads in a specified time period [18]. The construction model based on environment is characterized as follows:(a)
The nonlinear transformation characteristics of municipal road construction quality reliability parameters are analyzed. The selected municipal roads include intersections, transport roads, and related roads. Equation (5) can be used to calculate the road reliability c parameter.(5)wcl+1=gwi,wtr,wrr,Q,l.In equation (5), l represents the time period for calculating the connectivity reliability of municipal roads, and Wcl+1 represents the connectivity reliability parameters of municipal roads in the next time period. According to equation (5), many factors affect the connectivity reliability of municipal roads, which a simple mathematical model cannot describe, so the nonlinear transformation relationship of g function cannot be obtained [19].(b)
The environmental characteristics of municipal road are based on two parameters, i.e., and minimal consumption of natural resources and maximum utilization of eco-friendly material. The equation of state for municipal roads can be described by the following equation:(6)EF=min∑i=0nCnr+max∑i=0nUem.Based on equation (6), it can be concluded that the variation of the quality also depends upon the parameters of environment, the natural resources should be utilized optimally, and eco-friendly materials should be utilized to the maximum to reduce the carbon footprints and to enhance the quality of municipal roads.


### 3.2. Calculation of Construction Quality of Municipal Roads

The calculation results of municipal road construction quality are closely related to the traffic flow, historical data, the quality of construction, and environment friendly perspective. It is necessary to establish a reasonable mathematical model to describe this relationship. Equation (7) can be used to describe the quality of the specified municipal road as it depends upon environment factor, reliability of the roads, safety of the roads, cost effectiveness, and channelization of the traffic as mentioned below.(7)CQ=maxEF+maxwcl+1+maxsafety+mincost+optimaltraffic.According to the above municipal road connectivity quality analysis, there are many factors influencing the construction quality of the roads but environmental factor is at priority due to global warming and ozone layer issues. The traditional algorithm for municipal road construction quality calculation cannot accurately describe the real situation of the load model, resulting in the deviation of the calculation results.


## 3.1. Characteristic Analysis of Municipal Road Construction

Engineering quality refers to the engineering safety, environmental safety, engineering economic practicality, and aesthetic degree required by national laws, regulations, technical standards, and design documents [18]. This phenomenon is including three levels of construction quality, work quality, and working procedure quality to consider while designing an evaluation system [19]. Relevant construction should be in accordance with the quality requirements and environment friendly standards for safeguarding the natural resources and human beings. The construction entities comprehensively consider the technical possibility and economic applicability of the construction and also consider the balance between the conditions permitted by social production and the actual development of the projects. The motive is to reduce the project cost, to reduce the carbon footprints generated by the construction, and to improve the project quality through the most economical construction methods [20].The term “work quality” refers to the level and degree of perfection of the work related to project quality undertaken by the engineering constructor which is embodied in the whole process of technical engineering activities and is comprehensively embodied through the preservation of natural resources, reduction in carbon footprints, quality of construction, and economic efficiency of the project [21]. Each link and each aspect of the project in the forming process will comprehensively reflect the project’s quality. In order to guarantee the project quality, all the project participants should improve their work quality and strictly control all the influencing factors of the construction project to improve the project quality level without hampering the environment [22]. The process quality becomes an important factor in the construction process operations where other factors such as environment, operation process, machinery, labor force, and the eco-friendly material significantly appraise the quality. The judgment of construction quality of municipal roads refers to the judgment of quality status according to the connectivity reliability parameters of municipal roads in a specified time period [18]. The construction model based on environment is characterized as follows:(a)
The nonlinear transformation characteristics of municipal road construction quality reliability parameters are analyzed. The selected municipal roads include intersections, transport roads, and related roads. Equation (5) can be used to calculate the road reliability c parameter.(5)wcl+1=gwi,wtr,wrr,Q,l.In equation (5), l represents the time period for calculating the connectivity reliability of municipal roads, and Wcl+1 represents the connectivity reliability parameters of municipal roads in the next time period. According to equation (5), many factors affect the connectivity reliability of municipal roads, which a simple mathematical model cannot describe, so the nonlinear transformation relationship of g function cannot be obtained [19].(b)
The environmental characteristics of municipal road are based on two parameters, i.e., and minimal consumption of natural resources and maximum utilization of eco-friendly material. The equation of state for municipal roads can be described by the following equation:(6)EF=min∑i=0nCnr+max∑i=0nUem.Based on equation (6), it can be concluded that the variation of the quality also depends upon the parameters of environment, the natural resources should be utilized optimally, and eco-friendly materials should be utilized to the maximum to reduce the carbon footprints and to enhance the quality of municipal roads.


## 3.2. Calculation of Construction Quality of Municipal Roads

The calculation results of municipal road construction quality are closely related to the traffic flow, historical data, the quality of construction, and environment friendly perspective. It is necessary to establish a reasonable mathematical model to describe this relationship. Equation (7) can be used to describe the quality of the specified municipal road as it depends upon environment factor, reliability of the roads, safety of the roads, cost effectiveness, and channelization of the traffic as mentioned below.(7)CQ=maxEF+maxwcl+1+maxsafety+mincost+optimaltraffic.According to the above municipal road connectivity quality analysis, there are many factors influencing the construction quality of the roads but environmental factor is at priority due to global warming and ozone layer issues. The traditional algorithm for municipal road construction quality calculation cannot accurately describe the real situation of the load model, resulting in the deviation of the calculation results.


## 4. Optimization Calculation Method for Quality Judgment of Municipal Road Construction

Using the traditional algorithm to calculate the connectivity reliability of municipal roads cannot avoid the defect; the algorithm cannot accurately describe the real situation of the load model due to the random variation of the load state of different time sections, which leads to the deviation of the calculation results of the connectivity reliability of municipal roads.


### 4.1. Realization of Road Reliability Calculation

The physical value of the construction quality monitoring information node is fused with the improved GA to obtain the similarity between the quality monitoring information competitive layer neuron and its input mode weight vector. The dimension of the input vector is reduced and mapped to the two-dimensional plane to effectively complete the visualized dynamic monitoring of the municipal road construction quality. In the municipal network, the number of roads frombj to bk is t, which can be described by m1,m2,…,mj,…,mt, and the connectivity reliability of municipal road mj can be described by smj. Assuming that smj is composed of municipal road fj1,fj2,…,fjn in series, the connectivity reliability of fjn can be described by sfjn, and l=1,2,…,u, and the composition function of municipal road reliability can be described by the following equation:(8)smj=sfjn×λ.Assuming that there arep roads in municipal road from node bj to node bk, and all transport roads are paralleled, the connectivity reliability composition function between these two points can be described by the following equation:(9)Sbj,bk=1−smj×p.The topological relationship of municipal roads is shown in Figure2.Figure 2
Topological relationship of municipal road.There are two different paths from the starting pointT to the municipal road intersection B, that is, through the curve F1 to the end point U or through the curve F2 to the end point U. The equivalent topology transformation of the above structure can obtain a new topology diagram, as shown in Figure 3.Figure 3
Equivalent transformation of topological relations.The calculation method of connectivity reliability fromB1 to B2 is as follows:Step 1: Calculate the topological network corresponding to the municipal road, and set the municipal road to be described by B and F, respectively, given in the following equation:(10)B=B1,B2,…,Bj,…,Bp,F=F1,F2,…,Fj,…,Fn.Step 2: Initialize the municipal road parameters and set the tree root node asBi=B1.Step 3: In the municipal road without calculation, search the node connected to the root node and never searched. Assuming that there is no node meeting the above conditions, the next step is to calculate; otherwise, anyBj node is selected.Step 4: Search the first branch node of the above root node as a new branch node, introduceP into the municipal road, and calculate the selected branch node as the branch node of the target road.Step 5: Assume that the data set of the unselected municipal path is a nonempty data set, then select any point, and return to step (3) to continue the operation.Step 6: Calculate the disjoint road data set according to the municipal road branch node.Step 7: According to equations (9) and (10), calculate the connectivity reliability of municipal roads.According to the method described above, the spanning tree method can be used to calculate road connectivity reliability.


## 4.1. Realization of Road Reliability Calculation

The physical value of the construction quality monitoring information node is fused with the improved GA to obtain the similarity between the quality monitoring information competitive layer neuron and its input mode weight vector. The dimension of the input vector is reduced and mapped to the two-dimensional plane to effectively complete the visualized dynamic monitoring of the municipal road construction quality. In the municipal network, the number of roads frombj to bk is t, which can be described by m1,m2,…,mj,…,mt, and the connectivity reliability of municipal road mj can be described by smj. Assuming that smj is composed of municipal road fj1,fj2,…,fjn in series, the connectivity reliability of fjn can be described by sfjn, and l=1,2,…,u, and the composition function of municipal road reliability can be described by the following equation:(8)smj=sfjn×λ.Assuming that there arep roads in municipal road from node bj to node bk, and all transport roads are paralleled, the connectivity reliability composition function between these two points can be described by the following equation:(9)Sbj,bk=1−smj×p.The topological relationship of municipal roads is shown in Figure2.Figure 2
Topological relationship of municipal road.There are two different paths from the starting pointT to the municipal road intersection B, that is, through the curve F1 to the end point U or through the curve F2 to the end point U. The equivalent topology transformation of the above structure can obtain a new topology diagram, as shown in Figure 3.Figure 3
Equivalent transformation of topological relations.The calculation method of connectivity reliability fromB1 to B2 is as follows:Step 1: Calculate the topological network corresponding to the municipal road, and set the municipal road to be described by B and F, respectively, given in the following equation:(10)B=B1,B2,…,Bj,…,Bp,F=F1,F2,…,Fj,…,Fn.Step 2: Initialize the municipal road parameters and set the tree root node asBi=B1.Step 3: In the municipal road without calculation, search the node connected to the root node and never searched. Assuming that there is no node meeting the above conditions, the next step is to calculate; otherwise, anyBj node is selected.Step 4: Search the first branch node of the above root node as a new branch node, introduceP into the municipal road, and calculate the selected branch node as the branch node of the target road.Step 5: Assume that the data set of the unselected municipal path is a nonempty data set, then select any point, and return to step (3) to continue the operation.Step 6: Calculate the disjoint road data set according to the municipal road branch node.Step 7: According to equations (9) and (10), calculate the connectivity reliability of municipal roads.According to the method described above, the spanning tree method can be used to calculate road connectivity reliability.


## 5. Experimental Results

In order to verify the effectiveness of the municipal road construction quality evaluation method based on the GA, we need to carry out an experimental study in a simulated environment. The experiment is based on MATLAB 7 simulation tool, using Visual Studio 2010 to build a visual simulation platform for municipal road quality evaluation, and Simulink tool to read road visual landscape image. The gray histogram of urban roadside landscape image is set asHm  = 0.12, the joint template matching coefficient is 0.25, and the template size of 3D color distribution is Ms  = 12, in x, y, z direction, the edge pixel set is (20, 27, 42), the pixel size of image sampling is 200∗400, the pixel level intensity as shown in Figure 4 is 12 dB, the interference intensity is 24 dB, and the center position Cp is (0.25, 0.46). According to the above simulation environment and parameter setting, the simulation of municipal road construction quality evaluation method is carried out.Figure 4
Carbon footprint releases by various methods for 1 km.Two days of municipal road related data need to be collected as sample data in the experiment process. The traffic state in the specified time period is recorded every 10 minutes. A total of 288 samples are collected, and the first 200 data are used as training sample data. The flow in the municipal road is described in Figure5.Figure 5
Experimental vehicle flow data.The municipal roads are shown in Figure6 in a simulated environment.Figure 6
Municipal roads in a map view.The first parameter for evaluation is carbon footprints by the proposed and existing methods.Table1 reveals the carbon footprints released by various methods within 1 km for different number of iterations. It can be concluded from the above results that carbon footprints released by the proposed method are minimal because this research is mainly focusing on the environmental issue during construction of municipality roads. The second best results are produced by the existing method presented in [4] and the worst carbon footprints release is given by the reference method [3]. However different methods can be used to evaluate the carbon footprints; we have used global hectare unit for the measurement of carbon footprints.Table 1
The carbon footprints produced by various methods for 1 km.
Number of samplesProposed method (g)Method of literature [3] (g)Method of literature [4]100255768567g200376889672g300498935844g4004961054100150069912941125gThe next parameter considered for the study is overall evaluation of the quality of the road which is based on the multiobjective fitness function of the proposed GA where different weights are given to the parameters influencing the construction of municipality roads but the maximum weightage is given to environmental factor. The weightage of 100% is divided (40% to environment + 20% to safety + 20% to consideration of traffic needs + 20% connectivity to other roads) in various parameters which influence the quality of municipality roads. The percentage-wise comparison of various techniques in presented in Table2 and Figure 7. It can be seen from Figure 7 that the proposed GA based evaluation method outperforms other methods as it has the highest percentage of reliability for evaluating the construction system considering all the influencing parameters.Table 2
Overall comparison of various methods in percentage on the reliability matrix.
Number of samplesProposed methodMethod of literature [3]Method of literature [4]2000.950.840.894000.940.820.866000.920.800.8468000.910.790.80110000.860.740.765Figure 7
Overall comparison of various methods in percentage on the reliability matrix.The proposed method can be applied to the actual road construction projects in future urban development for evaluating the construction model.


### 5.1. Discussion

The city road construction quality evaluation method is based on the improved GA proposed in this paper which has the better automatic matching ability to evaluate urban road related construction landscape color characteristics. The construction quality evaluation method of municipal roads is adopted to evaluate the parameters influencing the environment, effectively avoid visual stimulation, and improve the reliability of color characteristics evaluation. The environment is also given importance by eliminating carbon emissions by suggesting eco-friendly materials. The reliability of the method is good because it is considering multiple parameters for evaluating the construction quality of municipality roads. The proposed GA based method is compared with other existing methods to find out the evaluation score in percentage and carbon footprints released by various methods. It can be summarized from the results that carbon footprints released by the proposed method are minimal as compared to the other methods, as this method is mainly focusing on the environmental issue during construction of municipality roads. In result section, it can also be observed from Figure7 that the proposed GA based evaluation method outperforms other existing methods as it has achieved the highest percentage of reliability for evaluating the road construction system considering all the influencing parameters in construction of municipality roads.


## 5.1. Discussion

The city road construction quality evaluation method is based on the improved GA proposed in this paper which has the better automatic matching ability to evaluate urban road related construction landscape color characteristics. The construction quality evaluation method of municipal roads is adopted to evaluate the parameters influencing the environment, effectively avoid visual stimulation, and improve the reliability of color characteristics evaluation. The environment is also given importance by eliminating carbon emissions by suggesting eco-friendly materials. The reliability of the method is good because it is considering multiple parameters for evaluating the construction quality of municipality roads. The proposed GA based method is compared with other existing methods to find out the evaluation score in percentage and carbon footprints released by various methods. It can be summarized from the results that carbon footprints released by the proposed method are minimal as compared to the other methods, as this method is mainly focusing on the environmental issue during construction of municipality roads. In result section, it can also be observed from Figure7 that the proposed GA based evaluation method outperforms other existing methods as it has achieved the highest percentage of reliability for evaluating the road construction system considering all the influencing parameters in construction of municipality roads.


## 6. Conclusion

The environmental changes around the globe are alarming. The development of infrastructure is a threat to environment. It is the need of the hour to consider environmental issues during the development of the infrastructure. There is a need to locate the ways to make use of eco-friendly material for infrastructure in all the developing nations. The conventional quality evaluation methods do not consider the environmental and other important factors such as safety, reliability, and traffic needs. Now is the time to pay attention to the global environmental issues before the development of infrastructure. The evaluation method of municipal road construction quality based on an improved GA is proposed in this article by considering carbon footprints. The proposed GA based evaluation method is compared with other existing methods to determine the evaluation score in percentage and carbon footprints released by the proposed and other existing methods. The carbon footprints released by the proposed method are minimal as compared to the other state-of-the-art methods. It is also observed that the proposed GA based evaluation method achieves the highest percentage of reliability for evaluating the road construction system by considering all the parameters which are impacting the construction of municipality roads. In future, more parameters will be studied to consider environmental factor for the development of infrastructure such as municipality roads, bridges, and flyovers.



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*Source: 3434683-2022-05-21.xml*