# Construction and Analysis of Urban Motor Vehicle Drivers’ Traffic Literacy Evaluation Model Based on Zhengzhou City’s Survey Data

Authors: Liu Shengyang; Wang Yanrong; Tian Kang; Hu Fangzheng
Journal: Journal of Mathematics
 (2022)

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## Abstract

This paper summarizes the relevant literature through the content analysis method and combines expert advice. The company built a four-level indicator including traffic knowledge and skills, and 13 pilot-level traffic literacy evaluation indicators system including traffic rules and mechanical common sense. The Analytic Hierarchy Process (AHP) analysis method is used to determine the weight of each indicator of urban driver traffic literacy evaluation, and conduct pilot survey and evaluation of motor vehicle drivers in Zhengzhou. The results show that the evaluation value of motor vehicle driver traffic literacy in Zhengzhou is 72.07, including a traffic knowledge score of 77.09, traffic awareness score of 73.95, traffic skill score of 78.12, and traffic behavior score of up to 84.3. It shows that the respondents have relatively more active and responsible traffic behaviors and have a certain degree of understanding of traffic skills and traffic knowledge. However, they are relatively low in traffic awareness.


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## Body

## 1. Introduction

With the rapid development of the country’s economy, road congestion is becoming more and more serious; traffic accidents occur frequently, and road traffic laws and regulations are violated in an endless stream, which seriously affects urban development and a resident’s quality of life in transportation [1]. Traditional transportation concepts can no longer adapt to this rapid development era. People must establish a new type of modern transportation awareness to solve a series of transportation problems caused by this. However, the practice has proved that only relying on the construction of large-scale transportation facilities cannot fundamentally alleviate the urban transportation problems [2]. During the implementation of traffic management, we should be people-oriented and combine the awareness of traffic participants and traffic managers to deal with Traffic problems jointly.At present, some domestic scholars have researched related issues of transportation literacy. For example, Chen and Chen [3] investigated the traffic literacy of Hefei citizens on the spot and pointed out that the main problems are pedestrians and vehicles not observing traffic lights, citizens’ driving violations from time to time, citizens occupying roads, and parking. It also proposed that the promotion and education of civilized traffic laws and regulations should be strengthened, and three educational networks of families, schools, and society should be established; also, the level of traffic management should be improved through the construction of law enforcement teams, infrastructure planning, and design, and the introduction of market mechanisms. Strengthening people’s comfort can genuinely realize the purpose of convenient transportation; it is necessary to improve public transportation literacy and rationally deal with “Chinese-style of crossing the road.” Yan [4] discussed traffic quality from drivers’ perspective, pointed out that the civilized traffic quality of drivers is the leading factor affecting modern traffic, and put forward relevant suggestions. Xiao [5] pointed out that the civilized literacy of drivers in the country has been continuously improved based on the comparison of data research from 2004 to 2017. Tracing back to the source, the current lack of driver’s traffic literacy is the root cause of frequent traffic problems. However, everyone’s learning and understanding of traffic safety awareness are different. The behavior and habits are mainly based on acquired propaganda and education, which triggers discussion on driver’s traffic literacy, pays attention to the research of driver’s traffic literacy, and establishes a good personality at the personal level.Traffic literacy awareness aims to fundamentally improve drivers’ awareness of road responsibilities and develop good road travel habits, thereby preventing road traffic accidents and ensuring safe driving. Some domestic scholars have also researched carbon transportation literacy. For example, Hu [6] analyzed the low-carbon awareness, low-carbon knowledge, and low-carbon behaviors of Zhengzhou, Luoyang, and Kaifeng residents. The status quo of residents’ low-carbon transportation literacy in transportation shows that urban residents’ educational level and income level have a clear positive correlation with the degree of concern about low-carbon transportation. Li [7] analyzed the problems of low-carbon transportation construction in Zhengzhou City through data collection, investigation, and analysis, and proposed to improve road construction regulations, divert vehicles and pedestrians on congested roads in urban areas, and increase the public transportation network system, that is, address three aspects to solve the existing problems.The above studies focus on exploratory studies on the status and reasons for traffic literacy, and few studies have focused on the factors that affect drivers’ traffic literacy. Based on the connotation and composition of urban driver’s traffic literacy, this paper analyzes and summarizes the relevant literature on the influencing factors, formation mechanism, evaluation purpose, and index selection principles of the traffic system and constructs an evaluation index system for urban driver’s traffic literacy. We use the analytic hierarchy process to optimize the urban driver’s traffic literacy evaluation index system and conduct a pilot survey and evaluation of Zhengzhou motor vehicle drivers, intending to assess urban drivers further. The traffic literacy evaluation lays a theoretical foundation. It provides specific policy suggestions for improving urban traffic. In Section2, the distinguishing factors of Urban motor vehicle drivers’ traffic literacy are analyzed. Section 3 of this paper constructed the weight model of traffic literacy based on the Analytic Hierarchy Process (AHP). Section 4 evaluates the traffic literacy of motor vehicle drivers in Zhengzhou. In section 5, the conclusion to the current study is presented.


## 2. Analysis of Characteristic Factors of Urban Motor Vehicle Drivers’ Traffic Literacy

This section analyzes the characteristic factors of traffic literacy of urban motor vehicle drivers. First, we define the concept of driver’s traffic literacy. Then, we discuss the basic idea of extraction of characteristics of urban motor vehicle drivers’ traffic literacy. Moreover, the preliminary construction of the traffic literacy evaluation index system is discussed.


### 2.1. Definition of Driver’s Traffic Literacy Concept

Through the analysis and combing of the literature and learning from previous research experience, we believe that the concept of literacy can be introduced into the actual driving process of drivers, and the solution to traffic problems is regarded as a “human action.” Traffic literacy is a kind of professional literacy with practical significance. It refers to the traffic behavior or tendency that traffic participants gradually develop during long-term driving activities and are not easy to change for a while and the knowledge, attitude, and control of driving activities. Ability is gradually summarized from people’s actions and mainly refers to people’s awareness of traffic, the relationship between people and the traffic environment, and humans’ treatment of traffic conditions that are gradually accumulated in response to various road traffic conditions [8]. Comprehensive quality consists of specific knowledge and experience, reasonable methods and skills, and people-oriented green awareness. The formation of traffic literacy starts with the personal mastery of traffic knowledge, cultivates and forms a healthy traffic awareness, then turns traffic knowledge into a skill, establishes a good traffic safety awareness, and uses it to guide actions.


### 2.2. Basic Idea of Extracting Characteristic Factors of Traffic Literacy of Urban Motor Vehicle Drivers

The construction of the urban driver’s traffic literacy evaluation system is a multi-index, multi-level comprehensive evaluation problem. It contains more content and involves a wide range. Therefore, it is necessary to set up a quantitative evaluation and transform qualitative problems into quantitative problems for analysis. An evaluation index system is established according to the index level and the defined size relationship. The traffic literacy of different cities is evaluated to lay a solid foundation for improving the overall traffic literacy and enhancing national traffic safety awareness.


### 2.3. Preliminary Construction of the Evaluation Index System of Traffic Literacy

Determining traffic literacy evaluation indicators is a complicated issue. Since harmonious traffic involves many issues, the corresponding influencing factors can be divided into dozens or hundreds of categories. To facilitate the research and the operability of the evaluation model, combine the influencing factors, formation mechanism, evaluation purpose, and index selection principles of the transportation system [3–5, 9–12], and after analysis and summarization, a subjective index system of traffic literacy is constructed. Specifically, it includes 13 subjective indicators such as traffic rules, general knowledge of machinery, knowledge of laws and regulations, safety awareness, treatment of others, facility safety, situation prediction, vehicle control, preventive measures, emergency measures, self-management behaviors, driving control behaviors, safe and civilized behaviors, etc. After analysis and classification, 13 indicators are combined into 4 main evaluation factors: traffic knowledge, traffic awareness, traffic skills, and traffic behavior, as shown in Table 1.Table 1
Structure of traffic literacy evaluation indicators.
Evaluation goalEvaluation factorEvaluation indexTraffic literacyXTraffic knowledgeX1Traffic rulesX11Mechanical knowledgeX12Knowledge of laws and regulationsX13Traffic awarenessX2Safety consciousnessX21Treat others wellX22Facility safetyX23Situation foreseeingX24Traffic skillsX3Vehicle controlX31PrecautionX32Emergency measuresX33Traffic behaviorX4Self-management behaviorX41Driving control behaviorX42Safe and civilized behaviorX43


## 2.1. Definition of Driver’s Traffic Literacy Concept

Through the analysis and combing of the literature and learning from previous research experience, we believe that the concept of literacy can be introduced into the actual driving process of drivers, and the solution to traffic problems is regarded as a “human action.” Traffic literacy is a kind of professional literacy with practical significance. It refers to the traffic behavior or tendency that traffic participants gradually develop during long-term driving activities and are not easy to change for a while and the knowledge, attitude, and control of driving activities. Ability is gradually summarized from people’s actions and mainly refers to people’s awareness of traffic, the relationship between people and the traffic environment, and humans’ treatment of traffic conditions that are gradually accumulated in response to various road traffic conditions [8]. Comprehensive quality consists of specific knowledge and experience, reasonable methods and skills, and people-oriented green awareness. The formation of traffic literacy starts with the personal mastery of traffic knowledge, cultivates and forms a healthy traffic awareness, then turns traffic knowledge into a skill, establishes a good traffic safety awareness, and uses it to guide actions.


## 2.2. Basic Idea of Extracting Characteristic Factors of Traffic Literacy of Urban Motor Vehicle Drivers

The construction of the urban driver’s traffic literacy evaluation system is a multi-index, multi-level comprehensive evaluation problem. It contains more content and involves a wide range. Therefore, it is necessary to set up a quantitative evaluation and transform qualitative problems into quantitative problems for analysis. An evaluation index system is established according to the index level and the defined size relationship. The traffic literacy of different cities is evaluated to lay a solid foundation for improving the overall traffic literacy and enhancing national traffic safety awareness.


## 2.3. Preliminary Construction of the Evaluation Index System of Traffic Literacy

Determining traffic literacy evaluation indicators is a complicated issue. Since harmonious traffic involves many issues, the corresponding influencing factors can be divided into dozens or hundreds of categories. To facilitate the research and the operability of the evaluation model, combine the influencing factors, formation mechanism, evaluation purpose, and index selection principles of the transportation system [3–5, 9–12], and after analysis and summarization, a subjective index system of traffic literacy is constructed. Specifically, it includes 13 subjective indicators such as traffic rules, general knowledge of machinery, knowledge of laws and regulations, safety awareness, treatment of others, facility safety, situation prediction, vehicle control, preventive measures, emergency measures, self-management behaviors, driving control behaviors, safe and civilized behaviors, etc. After analysis and classification, 13 indicators are combined into 4 main evaluation factors: traffic knowledge, traffic awareness, traffic skills, and traffic behavior, as shown in Table 1.Table 1
Structure of traffic literacy evaluation indicators.
Evaluation goalEvaluation factorEvaluation indexTraffic literacyXTraffic knowledgeX1Traffic rulesX11Mechanical knowledgeX12Knowledge of laws and regulationsX13Traffic awarenessX2Safety consciousnessX21Treat others wellX22Facility safetyX23Situation foreseeingX24Traffic skillsX3Vehicle controlX31PrecautionX32Emergency measuresX33Traffic behaviorX4Self-management behaviorX41Driving control behaviorX42Safe and civilized behaviorX43


## 3. Construction of the Weight Model of Traffic Literacy Based on the Analytic Hierarchy Process

Since each evaluation index needs to set up corresponding weights, all the indexes in this paper use the combination of the Delphi method and analytic hierarchy process to determine the evaluation index weights. The analytic hierarchy process is a multi-target group’s decision-making ideas and methods. In the application of group decision-making, there are two different ways to deal with the pairwise judgments of the group matrix. One of them is to first determine the individual weights according to the individual judgment matrix and then combine them. The second method is to synthesize the individual judgment matrix and then determine the group weight. The evaluator first decomposes the complex problem into many constituent elements and forms these elements into an orderly hierarchical structure according to the dominance relationship. The total evaluation value is determined, and the decision is made. The advantage is that the thinking process of analysts can be systematized, mathematicized, and modeled, and many impact indicators can be classified and processed so that the corresponding importance of each indicator can be determined.


### 3.1. Hierarchical Analysis Model Construction

The questionnaire survey form is adopted for this model to facilitate the analysis of various indicators, and the corresponding AHP model is established, as shown in Figure1. The comparative judgment matrix uses the Delphi method to invite relevant experts to make corresponding decisions. It uses questionnaires for statistical analysis, summarizes the comparative judgment matrix between indicators at various levels, and calculates the weight of each indicator based on the judgment matrix.Figure 1
Specific traffic literacy model.First, select the evaluation index system, select experts according to the range of knowledge required for the traffic literacy evaluation problem, ask all experts to make decisions and related requirements, and attach all relevant background materials. At the same time, ask the experts to suggest what other materials are needed and supplemented. After the experts receive the materials, they compare the importance of the evaluation indicators according to a scale of 1–9. After normalizing the comparison matrix, the relative weight of each indicator at the same level is obtained. Generally speaking, after returning the questionnaire, the expert’s judgment matrix should be checked for consistency. Specific steps are as follows:If the activity relative activity has a score value, the activity relative activity score is reciprocal. The initial pairwise comparison matrixR can be expressed as follows:(1)R=1a12⋯a1na211⋯a2n⋮⋮⋮⋮an1an2⋯1.In equation (1), aij=1/aji,aij>0. The calculation of the weight of each level index, that is, the calculation of the root mean squares of all elements in each row of the judgment matrix; the formula is as follows:(2)Cij=n∏j=1naij,i=1,2,…,n.Generally speaking, the comparison matrix is not necessarily a consistent matrix, the characteristic root of the n-order consistent matrix is n, and the characteristic root of the n-order reciprocal matrix is λ, whereλ≥n. And, λ=n when the matrix is uniform, since λ continuously depends on aij, λ can be more than n, the inconsistency of the matrix will be more serious, so the value of λ−n is used to measure the degree of inconsistency. The formula is as follows: CI=λ−n/n−1Among them, in order to determine the allowable range of matrix inconsistency, a random consistency index is also introducedRI, when CR=CI/RI (If it is 0.1, it can be considered that the inconsistency of the matrix is within the allowable range, and the matrix that cannot pass is modified accordingly), Then, normalize the matrix to obtain the relative weight of the index layer.(3)Cij=aij∑i=1naij,Wij=∑j=1nCijn,∑i=1nWi=1.This study adopts software combined with a questionnaire survey based on experts to compare the importance of indicators at various levels and calculate the weights. Finally, the geometric average of all statistical experts’ data is used as the relative weight.


### 3.2. Determining the Weights of All Levels of Traffic Literacy Evaluation

According to the results of questionnaire analysis and expert decision-making, this part realizes the weight calculation of the first-level index and the second-level index through the operation of the software. All judgment matrices and calculation results are shown in Tables2 to 6.Table 2
Judgment matrix of traffic literacy evaluation system and weight.
The assembled judgment matrix--the evaluation system of traffic literacyConcordance ratio CR = 0.0173Traffic literacy evaluation systemTraffic knowledgeTraffic awarenessTraffic skillsTraffic behaviorwiTraffic knowledge1.00002.40823.39350.31960.2397Traffic awareness0.41521.00001.49630.21440.1127Traffic skills0.29470.66831.00000.18280.0819Traffic behavior3.12914.66325.47071.00000.5657Table 3
Discrimination matrix of traffic knowledge secondary indicators and weight.
The assembled judgment matrix-traffic knowledgeConcordance ratio CR = 0.0000Traffic knowledgeTraffic rulesMechanical knowledgeKnowledge of laws and regulationswiTraffic rules1.00003.93631.82060.4163Mechanical knowledge0.25401.00000.38390.2251Knowledge of laws and regulations0.54932.60521.00000.3586Table 4
Discrimination matrix of traffic awareness level indicators and weight.
The assembled judgment matrix-traffic awarenessConcordance ratio CR = 0.0514Traffic awarenessSafety consciousnessTreat others wellFacility safetySituation foreseeingwiSafety consciousness1.00004.07606.11854.16940.6950Treat others well0.24531.00003.00001.24570.2148Facility safety0.16340.33331.00001.52810.0903Situation foreseeing0.23980.80270.65441.00000.1269Table 5
Discrimination matrix of traffic skill secondary indicators and weight.
The assembled judgment matrix-transportation skillsConcordance ratio CR = 0.0167Traffic skillsVehicle controlPrecautionEmergency measureswiVehicle control1.00005.30463.62970.6759Precaution0.18851.00000.46110.1117Emergency measures0.27552.16891.00000.2124Table 6
Discriminant matrix of traffic behavior secondary indicators and weight.
The assembled judgment matrix-traffic behaviorConcordance ratio CR = 0.0000Traffic behaviorSelf-management behaviorDriving control behaviorSafe and civilized behaviorwiSelf-management behavior1.00004.35973.39350.5266Driving control behavior0.22941.00000.65980.2103Safe and civilized behavior0.29471.51571.00000.2631Based on the above research and calculation results, it can be seen that the analytic hierarchy process is used to solve the weight of each indicator, and the detailed calculation process of each indicator is realized with the aid of the analysis software “yaahp.” The detailed summary information of the weight of each level is shown in Table7.Table 7
Driver’s traffic literacy system indicators comprehensive weighted weight assignment.
Secondary indicator layerWeightsThree-level indicator layerWeightsDriver’s traffic literacyTraffic knowledge0.2397Traffic rules0.4163Mechanical knowledge0.2251Knowledge of laws and regulations0.3586Traffic awareness0.1127Safety consciousness0.6950Treat others well0.2148Facility safety0.0903Situation foreseeing0.1269Traffic skills0.0819Vehicle control0.6759Precaution0.1117Emergency measures0.2124Traffic behavior0.5657Self-management behavior0.5266Driving control behavior0.2103Safe and civilized behavior0.2631When the total weight is obtained, the consistency test index of the total arrangement is calculated, namely, CR = 0.0173, and the total index can pass the consistency test when the test is passed.


## 3.1. Hierarchical Analysis Model Construction

The questionnaire survey form is adopted for this model to facilitate the analysis of various indicators, and the corresponding AHP model is established, as shown in Figure1. The comparative judgment matrix uses the Delphi method to invite relevant experts to make corresponding decisions. It uses questionnaires for statistical analysis, summarizes the comparative judgment matrix between indicators at various levels, and calculates the weight of each indicator based on the judgment matrix.Figure 1
Specific traffic literacy model.First, select the evaluation index system, select experts according to the range of knowledge required for the traffic literacy evaluation problem, ask all experts to make decisions and related requirements, and attach all relevant background materials. At the same time, ask the experts to suggest what other materials are needed and supplemented. After the experts receive the materials, they compare the importance of the evaluation indicators according to a scale of 1–9. After normalizing the comparison matrix, the relative weight of each indicator at the same level is obtained. Generally speaking, after returning the questionnaire, the expert’s judgment matrix should be checked for consistency. Specific steps are as follows:If the activity relative activity has a score value, the activity relative activity score is reciprocal. The initial pairwise comparison matrixR can be expressed as follows:(1)R=1a12⋯a1na211⋯a2n⋮⋮⋮⋮an1an2⋯1.In equation (1), aij=1/aji,aij>0. The calculation of the weight of each level index, that is, the calculation of the root mean squares of all elements in each row of the judgment matrix; the formula is as follows:(2)Cij=n∏j=1naij,i=1,2,…,n.Generally speaking, the comparison matrix is not necessarily a consistent matrix, the characteristic root of the n-order consistent matrix is n, and the characteristic root of the n-order reciprocal matrix is λ, whereλ≥n. And, λ=n when the matrix is uniform, since λ continuously depends on aij, λ can be more than n, the inconsistency of the matrix will be more serious, so the value of λ−n is used to measure the degree of inconsistency. The formula is as follows: CI=λ−n/n−1Among them, in order to determine the allowable range of matrix inconsistency, a random consistency index is also introducedRI, when CR=CI/RI (If it is 0.1, it can be considered that the inconsistency of the matrix is within the allowable range, and the matrix that cannot pass is modified accordingly), Then, normalize the matrix to obtain the relative weight of the index layer.(3)Cij=aij∑i=1naij,Wij=∑j=1nCijn,∑i=1nWi=1.This study adopts software combined with a questionnaire survey based on experts to compare the importance of indicators at various levels and calculate the weights. Finally, the geometric average of all statistical experts’ data is used as the relative weight.


## 3.2. Determining the Weights of All Levels of Traffic Literacy Evaluation

According to the results of questionnaire analysis and expert decision-making, this part realizes the weight calculation of the first-level index and the second-level index through the operation of the software. All judgment matrices and calculation results are shown in Tables2 to 6.Table 2
Judgment matrix of traffic literacy evaluation system and weight.
The assembled judgment matrix--the evaluation system of traffic literacyConcordance ratio CR = 0.0173Traffic literacy evaluation systemTraffic knowledgeTraffic awarenessTraffic skillsTraffic behaviorwiTraffic knowledge1.00002.40823.39350.31960.2397Traffic awareness0.41521.00001.49630.21440.1127Traffic skills0.29470.66831.00000.18280.0819Traffic behavior3.12914.66325.47071.00000.5657Table 3
Discrimination matrix of traffic knowledge secondary indicators and weight.
The assembled judgment matrix-traffic knowledgeConcordance ratio CR = 0.0000Traffic knowledgeTraffic rulesMechanical knowledgeKnowledge of laws and regulationswiTraffic rules1.00003.93631.82060.4163Mechanical knowledge0.25401.00000.38390.2251Knowledge of laws and regulations0.54932.60521.00000.3586Table 4
Discrimination matrix of traffic awareness level indicators and weight.
The assembled judgment matrix-traffic awarenessConcordance ratio CR = 0.0514Traffic awarenessSafety consciousnessTreat others wellFacility safetySituation foreseeingwiSafety consciousness1.00004.07606.11854.16940.6950Treat others well0.24531.00003.00001.24570.2148Facility safety0.16340.33331.00001.52810.0903Situation foreseeing0.23980.80270.65441.00000.1269Table 5
Discrimination matrix of traffic skill secondary indicators and weight.
The assembled judgment matrix-transportation skillsConcordance ratio CR = 0.0167Traffic skillsVehicle controlPrecautionEmergency measureswiVehicle control1.00005.30463.62970.6759Precaution0.18851.00000.46110.1117Emergency measures0.27552.16891.00000.2124Table 6
Discriminant matrix of traffic behavior secondary indicators and weight.
The assembled judgment matrix-traffic behaviorConcordance ratio CR = 0.0000Traffic behaviorSelf-management behaviorDriving control behaviorSafe and civilized behaviorwiSelf-management behavior1.00004.35973.39350.5266Driving control behavior0.22941.00000.65980.2103Safe and civilized behavior0.29471.51571.00000.2631Based on the above research and calculation results, it can be seen that the analytic hierarchy process is used to solve the weight of each indicator, and the detailed calculation process of each indicator is realized with the aid of the analysis software “yaahp.” The detailed summary information of the weight of each level is shown in Table7.Table 7
Driver’s traffic literacy system indicators comprehensive weighted weight assignment.
Secondary indicator layerWeightsThree-level indicator layerWeightsDriver’s traffic literacyTraffic knowledge0.2397Traffic rules0.4163Mechanical knowledge0.2251Knowledge of laws and regulations0.3586Traffic awareness0.1127Safety consciousness0.6950Treat others well0.2148Facility safety0.0903Situation foreseeing0.1269Traffic skills0.0819Vehicle control0.6759Precaution0.1117Emergency measures0.2124Traffic behavior0.5657Self-management behavior0.5266Driving control behavior0.2103Safe and civilized behavior0.2631When the total weight is obtained, the consistency test index of the total arrangement is calculated, namely, CR = 0.0173, and the total index can pass the consistency test when the test is passed.


## 4. Evaluation of Traffic Literacy of Motor Vehicle Drivers in Zhengzhou City

This section intends to evaluate the traffic literacy of motor vehicle drivers in Zhengzhou city. Henceforth, the design of the questionnaire and scoring rules are defined. Furthermore, an overview of sample and data acquisition is also explained. In addition, the results are analyzed and evaluated. Finally, an overall evaluation of traffic literacy of motor vehicle drivers in Zhengzhou is given.


### 4.1. Questionnaire Design and Scoring Rules

To obtain adequate data and ensure the scientificity and standardization of the evaluation, the design of the questionnaire follows the principles of matching, conciseness, and completeness. The confidentiality commitment is made in the questionnaire instruction section, and the research purpose is explained [10]. A survey questionnaire for traffic literacy evaluation of motor vehicle drivers in Zhengzhou is designed. The questionnaire is composed of three parts: the headline, the basic situation of the surveyed person, and the main body of the questionnaire. The basic information of the surveyed person includes seven demographic indicators of gender, age, education, occupation, place of residence, annual family income, and driving age of the surveyed person. The main body of the questionnaire contains four topics: traffic knowledge, traffic awareness, traffic skills, and traffic behavior. Questions are set according to the weights of 13 three-level indicators, with a lower weight setting of 1-2 questions, and a higher weight setting of 2-3 questions per problem. A total of 19 questions are set.When designing each questionnaire item, we learned from the relatively mature scale paradigm and used the Likert scale to measure traffic knowledge, awareness, skills, and behavior. This study’s answer is designed into five measurement levels, corresponding to the five points of “5, 4, 3, 2, and 1.” According to different questions, different combinations of statement languages are designed to investigate the respondents, enabling them to make choices more clearly and conveniently so that the attitudes or opinions of the respondents can be more clearly reflected. By consulting experts and teachers in related fields, such as psychology, sociology, and statistics, and drawing on relatively mature scales, such as scientific literacy, environmental literacy, water literacy, etc., the language expression of the questionnaire is refined to form the “Vehicle Driver Traffic Literacy Evaluation Questionnaire.”


### 4.2. Data Acquisition and Sample Overview

The questionnaire of this research selected people with driving experience within the administrative area of Zhengzhou City. The questionnaire is distributed online through electronic questionnaires and face-to-face hard copy questionnaires. Considering that the online questionnaire still has certain limitations, filling is done in the paper questionnaire face to face to supplement. The paper questionnaire is distributed to select locations such as a vehicle management office in Zhengzhou, a comprehensive service hall of a traffic police brigade, and a vehicle repair shop to make the data obtained more comprehensive. A total of 980 questionnaires were distributed in this study, and 693 valid questionnaires were obtained after excluding unqualified questionnaires (for example, the online questionnaire has a short answer time, more than 80% of the questions are answered in a certain order, and the paper questionnaire is not completely filled out, etc., all of which will be regarded as unqualified questionnaires). The effective sample rate is 70.71%. The demographic information of the sample is described in five items: gender, age, education level, occupation, and average monthly household income, as shown in Table8.Table 8
Sample demographic characteristics information.
CategoryCategory descriptionNumber of samplesProportion (%)GenderMale53677.34Female15722.66Age16–3513519.4836–4533147.7646–5919227.71Over 60 years old355.05Education levelElementary school and below334.76Junior high school18927.27High school (including secondary school, vocational high school, technical school, etc.)25436.65University (college/undergraduate)14220.49Master's degree and above7510.82ProfessionCorporate personnel13319.19National civil servants (including soldiers, police, etc.)9814.14The public utility staff (such as teachers, doctors, etc.)10815.58Freelancers25536.80Others9914.29Average monthly household income (yuan)Below 4999415.925000–999929342.2810000–1999917625.4020000–4999910415.01Above 500007911.40


### 4.3. Result Analysis and Evaluation

Statistical analysis of the traffic literacy questionnaire survey of motor vehicle drivers in Zhengzhou City shows each evaluation factor score (the score is between 1 and 5, the higher the score, the better the evaluation), as shown in Table9.Table 9
Zhengzhou city motor vehicle driver traffic literacy evaluation factor score.
First level indicatorSecondary indicatorsQuestion numberSummary of observation pointsScoreTraffic knowledgeTraffic rules1Understanding of traffic rules4.002Attitudes toward learning traffic rules4.20Mechanical knowledge3Understanding of motor vehicle components3.15Knowledge of laws and regulations4Traffic-related laws and regulations3.63Traffic awarenessSafety consciousness5Have a strong sense of safety4.286Cultivation of safety awareness4.26Treat others well7How the passengers feel4.42Facility safety8Safety of motor vehicle parts4.08Situation foreseeing9Foresight4.09Traffic skillsVehicle control10Driving vehicle control4.1411Learning the intention of vehicle control3.92Precaution12Preventive measures for emergencies3.70Emergency measures13Understanding of relevant emergency measures3.64Traffic behaviorSelf-management behavior14Self-management4.2915Self-management awareness4.19Driving control behavior16Driving control4.15Safe and civilized behavior17Safe and civilized4.21Judging from the traffic literacy evaluation factor scores of motor vehicle drivers in Zhengzhou, the highest-scoring question is question 7, “Do you care more about the feelings of passengers and be kind to others during driving?” with a score of 4.42. The corresponding evaluation index is traffic awareness, which shows that the respondents have an obvious subjective idea of being kind to others. In the second place is question 14, “Can you perform better self-management during driving, with a score of 4.29, and its corresponding evaluation index is traffic behavior, which reflects that the respondent’s clear self-management behavior is projected on the performance of traffic behavior. It also shows that the respondents have good self-management habits in daily driving. The question with the lowest score was Question 3, “Do you have a common sense of the various components of the motor vehicle you drive?” which was only 3.15, indicating that most respondents did not have a common sense of the various components of the motor vehicle. In addition, a similar question is question 4, “Do you have a knowledge of traffic-related laws and regulations?” with a score of 3.63, ranking second from the bottom. Question 13 “Do you know relevant emergency measures for traffic emergencies?,” with a score of 3.64, indicating that the respondent does not know much about the emergency measures and is not familiar with the same related laws and regulations.4 questions correspond to traffic knowledge, among which the first question is “Do you understand traffic rules?” and the second question is “Have you studied traffic rules knowledge content?” The scores are relatively close, all-around 4 points. This shows that the respondents have a better knowledge of traffic rules. The third question, “Do you know a common sense of the various components of the motor vehicle you drive?” has a shallow score, only 3.15 points, indicating that some respondents are more aware of motor vehicles but do not know much about the components.In traffic awareness, in addition to the highest score for question 7, questions 5 and 6 have relatively high scores, indicating that motor vehicle drivers have a high level of safety awareness. The scores of questions 8 “Do you often pay attention to the safety of the various parts and facilities of the vehicle you drive?” and 9 “Do you think you can anticipate situations better while driving?” are not very high, which shows that motor vehicle drivers are not too concerned about the safety of auto parts and facilities. They cannot predict the situation very well.The score was 4.14 when asked, “Do you think you can handle a vehicle well?” but only 3.92 when asked “Do you intend to learn vehicle handling skills?”; this result shows that most of the respondents think that they have better vehicle control skills and do not want to carry out new learning. In traffic skills, preventive measures and emergency measures have low scores, and the training of emergency and preventive measures for motor vehicle drivers should be strengthened.Compared with traffic knowledge, traffic awareness, and traffic skills, traffic behavior scores were higher, with an average score of about 4.2. In particular, the self-management behavior score of the respondents was 4.29, and they all had good traffic civilized behaviors. It also shows that the traffic behavior of motor vehicle drivers in Zhengzhou is relatively good.


### 4.4. Overall Evaluation of Traffic Literacy of Motor Vehicle Drivers in Zhengzhou

According to the abovementioned analytic hierarchy process to determine the index weights at all levels, based on the average value of the traffic literacy evaluation factor scores of motor vehicle drivers in Zhengzhou City, the traffic literacy of motor vehicle drivers in Zhengzhou City is evaluated. To show the scores of each factor more intuitively, normalize each factor index and convert it into a percentile system. Taking the traffic literacy evaluation value of motor vehicle drivers in Zhengzhous as an example, the converted traffic literacy evaluation of motor vehicle drivers in Zhengzhou Value s = 4/5 × 100 = 80 uses the same method to process the index scores of each factor and get Table 10.Table 10
Zhengzhou city motor vehicle driver traffic literacy evaluation score.
SEvaluation valueSiEvaluation valueSijEvaluation valueTraffic literacy72.07Traffic knowledge77.09Traffic rules82.01Mechanical knowledge63.05Knowledge of laws and regulations72.57Traffic awareness73.95Safety consciousness85.39Treat others well88.50Facility safety81.53Situation foreseeing81.88Traffic skills78.12Vehicle control80.59Precaution74.05Emergency measures72.88Traffic behavior84.3Self-management behavior84.81Driving control behavior82.90Safe and civilized behavior84.12The traffic literacy evaluation value of motor vehicle drivers in Zhengzhou is 72.07, of which the traffic knowledge score is 77.09, traffic awareness score is 73.95, and traffic skills score is 78.12. The traffic behavior score is 84.3, reflecting that the respondents have a relatively more active and responsible traffic behavior and have a certain degree of understanding of traffic skills and traffic knowledge, but are relatively low in traffic awareness.Among the various scores of traffic knowledge, motor vehicle drivers are more familiar with traffic laws and regulations but do not know much about the car’s components. Most motor vehicle drivers pay more attention to traffic knowledge during driving and do not need to know much about the car’s components, which is also in line with the driver’s daily life status. The highest score in traffic awareness is to be kind to others, indicating that motor vehicle drivers can better put themselves in other’s place and consider them. The attribute with the highest score in traffic skills is vehicle control, indicating that the motor vehicle driver can control well the driving of the vehicle. The highest traffic behavior score indicates that drivers behave well during motor vehicle driving. This is due to the observance of traffic rules and the self-cultivation of drivers. Overall, the traffic literacy score is only 72.07, which is not too high. It may be due to relatively low traffic knowledge, traffic awareness, and traffic skills. Therefore, it is necessary to strengthen the traffic knowledge, traffic awareness, and traffic skills of motor vehicle drivers.


## 4.1. Questionnaire Design and Scoring Rules

To obtain adequate data and ensure the scientificity and standardization of the evaluation, the design of the questionnaire follows the principles of matching, conciseness, and completeness. The confidentiality commitment is made in the questionnaire instruction section, and the research purpose is explained [10]. A survey questionnaire for traffic literacy evaluation of motor vehicle drivers in Zhengzhou is designed. The questionnaire is composed of three parts: the headline, the basic situation of the surveyed person, and the main body of the questionnaire. The basic information of the surveyed person includes seven demographic indicators of gender, age, education, occupation, place of residence, annual family income, and driving age of the surveyed person. The main body of the questionnaire contains four topics: traffic knowledge, traffic awareness, traffic skills, and traffic behavior. Questions are set according to the weights of 13 three-level indicators, with a lower weight setting of 1-2 questions, and a higher weight setting of 2-3 questions per problem. A total of 19 questions are set.When designing each questionnaire item, we learned from the relatively mature scale paradigm and used the Likert scale to measure traffic knowledge, awareness, skills, and behavior. This study’s answer is designed into five measurement levels, corresponding to the five points of “5, 4, 3, 2, and 1.” According to different questions, different combinations of statement languages are designed to investigate the respondents, enabling them to make choices more clearly and conveniently so that the attitudes or opinions of the respondents can be more clearly reflected. By consulting experts and teachers in related fields, such as psychology, sociology, and statistics, and drawing on relatively mature scales, such as scientific literacy, environmental literacy, water literacy, etc., the language expression of the questionnaire is refined to form the “Vehicle Driver Traffic Literacy Evaluation Questionnaire.”


## 4.2. Data Acquisition and Sample Overview

The questionnaire of this research selected people with driving experience within the administrative area of Zhengzhou City. The questionnaire is distributed online through electronic questionnaires and face-to-face hard copy questionnaires. Considering that the online questionnaire still has certain limitations, filling is done in the paper questionnaire face to face to supplement. The paper questionnaire is distributed to select locations such as a vehicle management office in Zhengzhou, a comprehensive service hall of a traffic police brigade, and a vehicle repair shop to make the data obtained more comprehensive. A total of 980 questionnaires were distributed in this study, and 693 valid questionnaires were obtained after excluding unqualified questionnaires (for example, the online questionnaire has a short answer time, more than 80% of the questions are answered in a certain order, and the paper questionnaire is not completely filled out, etc., all of which will be regarded as unqualified questionnaires). The effective sample rate is 70.71%. The demographic information of the sample is described in five items: gender, age, education level, occupation, and average monthly household income, as shown in Table8.Table 8
Sample demographic characteristics information.
CategoryCategory descriptionNumber of samplesProportion (%)GenderMale53677.34Female15722.66Age16–3513519.4836–4533147.7646–5919227.71Over 60 years old355.05Education levelElementary school and below334.76Junior high school18927.27High school (including secondary school, vocational high school, technical school, etc.)25436.65University (college/undergraduate)14220.49Master's degree and above7510.82ProfessionCorporate personnel13319.19National civil servants (including soldiers, police, etc.)9814.14The public utility staff (such as teachers, doctors, etc.)10815.58Freelancers25536.80Others9914.29Average monthly household income (yuan)Below 4999415.925000–999929342.2810000–1999917625.4020000–4999910415.01Above 500007911.40


## 4.3. Result Analysis and Evaluation

Statistical analysis of the traffic literacy questionnaire survey of motor vehicle drivers in Zhengzhou City shows each evaluation factor score (the score is between 1 and 5, the higher the score, the better the evaluation), as shown in Table9.Table 9
Zhengzhou city motor vehicle driver traffic literacy evaluation factor score.
First level indicatorSecondary indicatorsQuestion numberSummary of observation pointsScoreTraffic knowledgeTraffic rules1Understanding of traffic rules4.002Attitudes toward learning traffic rules4.20Mechanical knowledge3Understanding of motor vehicle components3.15Knowledge of laws and regulations4Traffic-related laws and regulations3.63Traffic awarenessSafety consciousness5Have a strong sense of safety4.286Cultivation of safety awareness4.26Treat others well7How the passengers feel4.42Facility safety8Safety of motor vehicle parts4.08Situation foreseeing9Foresight4.09Traffic skillsVehicle control10Driving vehicle control4.1411Learning the intention of vehicle control3.92Precaution12Preventive measures for emergencies3.70Emergency measures13Understanding of relevant emergency measures3.64Traffic behaviorSelf-management behavior14Self-management4.2915Self-management awareness4.19Driving control behavior16Driving control4.15Safe and civilized behavior17Safe and civilized4.21Judging from the traffic literacy evaluation factor scores of motor vehicle drivers in Zhengzhou, the highest-scoring question is question 7, “Do you care more about the feelings of passengers and be kind to others during driving?” with a score of 4.42. The corresponding evaluation index is traffic awareness, which shows that the respondents have an obvious subjective idea of being kind to others. In the second place is question 14, “Can you perform better self-management during driving, with a score of 4.29, and its corresponding evaluation index is traffic behavior, which reflects that the respondent’s clear self-management behavior is projected on the performance of traffic behavior. It also shows that the respondents have good self-management habits in daily driving. The question with the lowest score was Question 3, “Do you have a common sense of the various components of the motor vehicle you drive?” which was only 3.15, indicating that most respondents did not have a common sense of the various components of the motor vehicle. In addition, a similar question is question 4, “Do you have a knowledge of traffic-related laws and regulations?” with a score of 3.63, ranking second from the bottom. Question 13 “Do you know relevant emergency measures for traffic emergencies?,” with a score of 3.64, indicating that the respondent does not know much about the emergency measures and is not familiar with the same related laws and regulations.4 questions correspond to traffic knowledge, among which the first question is “Do you understand traffic rules?” and the second question is “Have you studied traffic rules knowledge content?” The scores are relatively close, all-around 4 points. This shows that the respondents have a better knowledge of traffic rules. The third question, “Do you know a common sense of the various components of the motor vehicle you drive?” has a shallow score, only 3.15 points, indicating that some respondents are more aware of motor vehicles but do not know much about the components.In traffic awareness, in addition to the highest score for question 7, questions 5 and 6 have relatively high scores, indicating that motor vehicle drivers have a high level of safety awareness. The scores of questions 8 “Do you often pay attention to the safety of the various parts and facilities of the vehicle you drive?” and 9 “Do you think you can anticipate situations better while driving?” are not very high, which shows that motor vehicle drivers are not too concerned about the safety of auto parts and facilities. They cannot predict the situation very well.The score was 4.14 when asked, “Do you think you can handle a vehicle well?” but only 3.92 when asked “Do you intend to learn vehicle handling skills?”; this result shows that most of the respondents think that they have better vehicle control skills and do not want to carry out new learning. In traffic skills, preventive measures and emergency measures have low scores, and the training of emergency and preventive measures for motor vehicle drivers should be strengthened.Compared with traffic knowledge, traffic awareness, and traffic skills, traffic behavior scores were higher, with an average score of about 4.2. In particular, the self-management behavior score of the respondents was 4.29, and they all had good traffic civilized behaviors. It also shows that the traffic behavior of motor vehicle drivers in Zhengzhou is relatively good.


## 4.4. Overall Evaluation of Traffic Literacy of Motor Vehicle Drivers in Zhengzhou

According to the abovementioned analytic hierarchy process to determine the index weights at all levels, based on the average value of the traffic literacy evaluation factor scores of motor vehicle drivers in Zhengzhou City, the traffic literacy of motor vehicle drivers in Zhengzhou City is evaluated. To show the scores of each factor more intuitively, normalize each factor index and convert it into a percentile system. Taking the traffic literacy evaluation value of motor vehicle drivers in Zhengzhous as an example, the converted traffic literacy evaluation of motor vehicle drivers in Zhengzhou Value s = 4/5 × 100 = 80 uses the same method to process the index scores of each factor and get Table 10.Table 10
Zhengzhou city motor vehicle driver traffic literacy evaluation score.
SEvaluation valueSiEvaluation valueSijEvaluation valueTraffic literacy72.07Traffic knowledge77.09Traffic rules82.01Mechanical knowledge63.05Knowledge of laws and regulations72.57Traffic awareness73.95Safety consciousness85.39Treat others well88.50Facility safety81.53Situation foreseeing81.88Traffic skills78.12Vehicle control80.59Precaution74.05Emergency measures72.88Traffic behavior84.3Self-management behavior84.81Driving control behavior82.90Safe and civilized behavior84.12The traffic literacy evaluation value of motor vehicle drivers in Zhengzhou is 72.07, of which the traffic knowledge score is 77.09, traffic awareness score is 73.95, and traffic skills score is 78.12. The traffic behavior score is 84.3, reflecting that the respondents have a relatively more active and responsible traffic behavior and have a certain degree of understanding of traffic skills and traffic knowledge, but are relatively low in traffic awareness.Among the various scores of traffic knowledge, motor vehicle drivers are more familiar with traffic laws and regulations but do not know much about the car’s components. Most motor vehicle drivers pay more attention to traffic knowledge during driving and do not need to know much about the car’s components, which is also in line with the driver’s daily life status. The highest score in traffic awareness is to be kind to others, indicating that motor vehicle drivers can better put themselves in other’s place and consider them. The attribute with the highest score in traffic skills is vehicle control, indicating that the motor vehicle driver can control well the driving of the vehicle. The highest traffic behavior score indicates that drivers behave well during motor vehicle driving. This is due to the observance of traffic rules and the self-cultivation of drivers. Overall, the traffic literacy score is only 72.07, which is not too high. It may be due to relatively low traffic knowledge, traffic awareness, and traffic skills. Therefore, it is necessary to strengthen the traffic knowledge, traffic awareness, and traffic skills of motor vehicle drivers.


## 5. Conclusion

Based on the concept of traffic literacy and the elemental composition of traffic literacy, this article combines the analysis of the influencing factors, formation mechanism, evaluation purpose, index selection principles of the traffic system, and after analysis and induction, constructs a subjective index system of traffic literacy. The specific subjective index layer has 13 indicators, namely, traffic rules, machinery knowledge, knowledge of laws and regulations, safety awareness, kindness to others, facility safety, situation prediction, vehicle control, preventive measures, emergency measures, self-management behaviors, driving control behaviors, and safe and civilized behaviors. The 13 indicators are classified and combined into 4 evaluation factors: traffic knowledge, traffic awareness, traffic skills, and traffic behavior. Through the investigation and analysis of the analytic hierarchy process, the weights of the four evaluation factors, traffic knowledge, traffic awareness, traffic skills, and traffic behavior, are respectively: 0.2397, 0.1127, 0.0819, and 0.5657. The results show that the weight of traffic awareness is relatively high in the driver’s traffic literacy evaluation index. The indicators with higher weights of the third-level indicators are traffic rules (0.4163), safety awareness (0.6950), vehicle control (0.6759), and self-management behavior (0.5266). After clarifying the importance of the secondary and tertiary indicators, the total weighted value of the driver’s traffic literacy system indicators is obtained. Based on the evaluation index system of motor vehicle drivers’ traffic literacy, a questionnaire was designed, and a questionnaire survey was conducted in the pilot city of Zhengzhou to analyze the primary status of the traffic literacy of motor vehicle drivers in Zhengzhou and conduct an overall evaluation of the traffic literacy of motor vehicle drivers. It shows that the traffic literacy evaluation value of motor vehicle drivers in Zhengzhou is 72.07, of which the traffic knowledge score is 77.09, the traffic awareness score is 73.95, the traffic skills score is 78.12, and the traffic behavior score is 84.3, reflecting that the respondents are relatively more active and responsible. Traffic behavior also has a certain degree of understanding of traffic skills and knowledge, but is relatively low in traffic awareness.Because of the limitations and subjectivity of the traffic literacy index system constructed in this study and the results based on the questionnaire survey, there are specific differences with the literacy of actual drivers. Respondents had a self-glorifying mentality when answering the questionnaire, which led to discrepancies between actual results and survey results. The survey results are pretty different, so follow-up research work needs to improve the construction of the indicator system further, and according to the current advanced technology in the era of big data, enrich the data basis of motor vehicle drivers’ traffic literacy, and use network data (accident rate, vehicle service life). Such indicators more intuitively reflect the traffic literacy of motor vehicle drivers to lay a solid foundation for further improving the overall traffic literacy of drivers and enhancing the awareness of safe traffic for all.



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*Source: 2366458-2022-02-16.xml*