Identification of Factors Influencing the Operational Effect of the Green Wave on Urban Arterial Roads Based on Association Analysis

Round 1

Reviewer 1 Report

Express novelty in abstract and conclusion.

Remove typo and revise English 

Revision of Grammer is important 

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Identification of Factors Influencing the Operational Effect of the Green Wave on Urban Arterial Roads Based on Association Analysis By Zijun Liang, Xuejuan Zhan, Ruihan Wang, Yuqi Li, Yun Xiao

Abstract

Green wave control technology is widely recognized as an effective approach to mitigate traffic congestion on urban arterial roads by optimizing traffic signal coordination. However, previous research predominantly focused on optimizing green wave control schemes without adequately considering the influence of behavioral factors associated with traffic and travel on its operational effectiveness. To address this gap, this study investigates the impact of various behavioral factors on arterial roads, using representative evaluation indicators such as the number of stops, travel time, and delay. Employing a combination of sensitivity analysis and grey relational analysis, the study ranks influential factors based on their correlation degree, identifying design speed, signal timing, lateral interference, and heavy vehicle travel as the most significant factors. To validate the proposed methodology, a case study is conducted utilizing traffic data from Eshan Road in Wuhu City, China. Simulation results in VISSIM reveal that lateral interference and heavy vehicle travel exert the greatest influence on the operational effectiveness of the green wave. Moreover, the study highlights that implementing traffic management measures has a more pronounced impact on improving the effectiveness of the green wave compared to solely optimizing the control scheme. Additionally, it emphasizes the substantial enhancement in operational effectiveness achieved by simultaneously optimizing green wave control schemes and implementing traffic management measures.

  Reviewer Report. Green wave control is an important technology to control traffic signals and improve the efficiency of traffic on urban arterial roads. Prevalent research in the area has focused on optimizing and evaluating schemes of green wave control. However, the operational effect of the green wave is easily affected by a variety of behavioral factors associated with traffic and travel. This makes it important to study methods to identify the behavioral factors influencing the operational effect of the green wave on arterial roads. In this study, we use the number of stops, travel time, and delay as representative evaluation indicators to assess the effects of the green wave, and use them to identify four representative factors influencing it: the design speed, signal timing, lateral interference, and heavy vehicle travel. A method of association analysis that combines sensitivity analysis with grey relational analysis is used to obtain the ranking of influential factors in terms of degree of correlation. This is leveraged in turn to propose a method to identify the factors influencing the effects of the green wave. A case study was conducted based on data on traffic on Eshan Road in Wuhu City of China to verify the proposed method. The results of simulations in VISSIM showed that lateral interference and heavy vehicle travel were the most important factors influencing the operational effect of the green wave. Moreover, implementing measures related to traffic management can help improve the effect of the green wave to a greater extent than optimizing the scheme used to realize green wave control, and optimizing schemes for green wave control under the premise of implementing measures of traffic management can significantly improve the operational effect of the green wave.   This paper aims to provide innovative contributions in the identification of factors that influence the operational effectiveness of the green wave on urban arterial roads. Firstly, a novel approach is proposed by combining sensitivity analysis and grey relational analysis to identify the most influential factors affecting the green wave's operational effectiveness. Additionally, a method for identifying these factors is presented. Secondly, the paper collects, cleans, and matches traffic-related data, including information on multiple intersections along arterial roads, to validate the effectiveness of the proposed method using real-world cases. The analysis indicates that measures related to traffic management may yield greater improvements in the green wave's operational effectiveness compared to optimizing the control scheme.   1. All cited references are pertinent to the research topic, ensuring the paper's thoroughness. 2. The paper's structure and design should be meticulously planned. 3. The sentences need to be presented in conjunction with the corresponding formulas. 4. Substantial editing is necessary to enhance the English language usage and style. 5. It is recommended that the authors diligently review the attached paper, step by step.

With major revisions, the paper has the potential to be published in the Applied Sciences journal.

 

Comments for author File: Comments.pdf

Identification of Factors Influencing the Operational Effect of the Green Wave on Urban Arterial Roads Based on Association Analysis By Zijun Liang, Xuejuan Zhan, Ruihan Wang, Yuqi Li, Yun Xiao

Abstract

Green wave control technology is widely recognized as an effective approach to mitigate traffic congestion on urban arterial roads by optimizing traffic signal coordination. However, previous research predominantly focused on optimizing green wave control schemes without adequately considering the influence of behavioral factors associated with traffic and travel on its operational effectiveness. To address this gap, this study investigates the impact of various behavioral factors on arterial roads, using representative evaluation indicators such as the number of stops, travel time, and delay. Employing a combination of sensitivity analysis and grey relational analysis, the study ranks influential factors based on their correlation degree, identifying design speed, signal timing, lateral interference, and heavy vehicle travel as the most significant factors. To validate the proposed methodology, a case study is conducted utilizing traffic data from Eshan Road in Wuhu City, China. Simulation results in VISSIM reveal that lateral interference and heavy vehicle travel exert the greatest influence on the operational effectiveness of the green wave. Moreover, the study highlights that implementing traffic management measures has a more pronounced impact on improving the effectiveness of the green wave compared to solely optimizing the control scheme. Additionally, it emphasizes the substantial enhancement in operational effectiveness achieved by simultaneously optimizing green wave control schemes and implementing traffic management measures.

  Reviewer Report. Green wave control is an important technology to control traffic signals and improve the efficiency of traffic on urban arterial roads. Prevalent research in the area has focused on optimizing and evaluating schemes of green wave control. However, the operational effect of the green wave is easily affected by a variety of behavioral factors associated with traffic and travel. This makes it important to study methods to identify the behavioral factors influencing the operational effect of the green wave on arterial roads. In this study, we use the number of stops, travel time, and delay as representative evaluation indicators to assess the effects of the green wave, and use them to identify four representative factors influencing it: the design speed, signal timing, lateral interference, and heavy vehicle travel. A method of association analysis that combines sensitivity analysis with grey relational analysis is used to obtain the ranking of influential factors in terms of degree of correlation. This is leveraged in turn to propose a method to identify the factors influencing the effects of the green wave. A case study was conducted based on data on traffic on Eshan Road in Wuhu City of China to verify the proposed method. The results of simulations in VISSIM showed that lateral interference and heavy vehicle travel were the most important factors influencing the operational effect of the green wave. Moreover, implementing measures related to traffic management can help improve the effect of the green wave to a greater extent than optimizing the scheme used to realize green wave control, and optimizing schemes for green wave control under the premise of implementing measures of traffic management can significantly improve the operational effect of the green wave.   This paper aims to provide innovative contributions in the identification of factors that influence the operational effectiveness of the green wave on urban arterial roads. Firstly, a novel approach is proposed by combining sensitivity analysis and grey relational analysis to identify the most influential factors affecting the green wave's operational effectiveness. Additionally, a method for identifying these factors is presented. Secondly, the paper collects, cleans, and matches traffic-related data, including information on multiple intersections along arterial roads, to validate the effectiveness of the proposed method using real-world cases. The analysis indicates that measures related to traffic management may yield greater improvements in the green wave's operational effectiveness compared to optimizing the control scheme.   1. All cited references are pertinent to the research topic, ensuring the paper's thoroughness. 2. The paper's structure and design should be meticulously planned. 3. The sentences need to be presented in conjunction with the corresponding formulas. 4. Substantial editing is necessary to enhance the English language usage and style. 5. It is recommended that the authors diligently review the attached paper, step by step.

With major revisions, the paper has the potential to be published in the Applied Sciences journal.

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 3 Report

The last line of abstract was not clear.

The title of section 2.3.1 is too long

The title of section 4.2 is too long.

In the abstract it as not clear, which behavioural factors were intended to be assessed?

In the abstract, it was not clear what do you mean by lateral interference?

“Analyzing the association between the indicators of evaluation of and factors influencing the green wave can help identify the most important factors influencing the operational effect of the green wave.” Please revise this sentence.

“he main objective of this paper is to reveal the interrelationship between influential factors and the operational effect of the green wave, and evaluate the degree of influence of influential factors on the operational effect of the green wave. Therefore, this paper selects the representative evaluation indicators and influential factors of the operational effect of the green wave through literature review: You have repeated the same thing in this sentence and in the introduction.

In section 2.1 it is expected to introduce the influential factors, more.

What was the reason for selecting these influential factors? Why there is not any factor in relation to geometric design of intersection?

Signal timing is a complicated factor. It is hard to decide about it based on this case study.

The last line of abstract was not clear.

The title of section 2.3.1 is too long

The title of section 4.2 is too long.

In the abstract it as not clear, which behavioural factors were intended to be assessed?

In the abstract, it was not clear what do you mean by lateral interference?

“Analyzing the association between the indicators of evaluation of and factors influencing the green wave can help identify the most important factors influencing the operational effect of the green wave.” Please revise this sentence.

“he main objective of this paper is to reveal the interrelationship between influential factors and the operational effect of the green wave, and evaluate the degree of influence of influential factors on the operational effect of the green wave. Therefore, this paper selects the representative evaluation indicators and influential factors of the operational effect of the green wave through literature review: You have repeated the same thing in this sentence and in the introduction.

In section 2.1 it is expected to introduce the influential factors, more.

What was the reason for selecting these influential factors? Why there is not any factor in relation to geometric design of intersection?

Signal timing is a complicated factor. It is hard to decide about it based on this case study.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 4 Report

Taking up the topic is important from the point of view of heavy traffic in large cities. Caused by a large number of people and cars. The green urban wave smoothes the movement of vehicles, as long as it is not disturbed by pedestrian crossings or the movement of heavy vehicles. The results say: "We used data on traffic on the road on a working day (September 21, 2020) during the peak cycle (8:30-9:30) for calculation and analysis" and in table 1 there are slightly different data , namely other dates and times. Check it please. What are the ranges for value of influence? Is 0.5 - 0.7 a high or medium range? State what they are low, medium and high.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The paper has the potential to be accepted for publication in the Applied Sciences journal within this form.