ITSS: An Intelligent Traffic Signaling System Based on an IoT Infrastructure

Round 1

Reviewer 1 Report

This paper is focused on ITSS: An Intelligent Traffic Signaling System based on CloudIoT Infrastructure. The subject matter of this manuscript fits the journal's scope, and the information included in the manuscript seems not to have been published in any other publication so far. However, it seems difficult to adequately evaluate the value of this study because the explanation of the significance of the study, the description of the interpretation and usefulness of the results obtained by the analysis, and the explanation of the model are insufficient. I would like to ask the authors to consider responding to the following comments:

(1)    Authors need to re-write the abstract, because some statement are not linked each other. Such as Inter-communication in the control unit sets the timer of the traffic light synchronized with
the traffic density in real-time. Integrating a pre-emption mechanism ensures prioritizing emergency vehicles over other vehicles in the same lane through infrared sensors. The consideration of traffic density determines the timer of the light post in real-time, thus enhancing the smooth flow of vehicles with reduced delay for travelers.

(2)    Would you explicitly specify the novelty of your work? What progress against the most recent state-of-the-art similar studies was made?

(3)    The Introduction section should be improved. It should be dedicated to presenting a critical analysis of state-of-the-art related work to justify the study's objective. In addition, critical comments should be made on the results of the cited works.

(4)    The main objective of the work must be written in a more precise and concise way at the end of the introduction section. Please carefully check recent literature and discuss/cite as you see fit, and update your reference list. Implementing the Maximum Likelihood Method for Critical Gap Estimation under Heterogeneous Traffic Conditions. Modeling of machine learning with SHAP approach for electric vehicle charging station choice behavior prediction.

(5)    A summative Table 1 Comparison study of the existing traffic signaling approaches based on various features. Its suggested to remove N with NO, Y with YES for more clarity

(6)    There is a room to improve the research methodology for publishing in an international journal. Furthermore, the numerical experiments were insufficient.

(7)    The reviewer think some figures related to the computation results should be presented to improve the quality of this paper.

(8)    The conclusion section provides a lack of contributions to this manuscript. Provide the key features, merits, and limitations of the proposed approach to clarify the precise boundary of the algorithms. The implication of the proposed method is also required.

(9)    This paper is generally well written, but I found multiple typographic and editorial errors over the entire manuscript, including the equations. The authors need to proofread again carefully.

Author Response

Please see attached file

Author Response File: Author Response.pdf

Reviewer 2 Report

This paper proposes an Internet of Things-based real-time Intelligent Traffic Signal System (ITSS) for optimizing traffic lights in response to varying traffic demand (density). Overall, the paper is well-written and has some merit; however, there are several major flaws that should be clarified/addressed before it can be accepted for publishing.

1.      In the introduction, the authors should reflect on traffic congestion and delay at an intersection in urban areas as a global socioeconomic concern. It is recommended to review and include the following studies in this regard: https://doi.org/10.3390/s20030685; doi.org/10.1080/15568318.2021.1885085; https://doi.org/10.3390/su12020646; https://doi.org/10.1016/j.tra.2020.02.019

2.      The proposed problem seems like a typical signal control/timing optimization problem, and tens and hundreds of studies have been conducted recently on the same subject. So what is added value or specific innovation points of the present work?

3.      In the literature, while authors have highlighted several methods for solving the signal timing optimization issues, they fail to mention the use of metaheuristics-based traffic signal control strategies, which have been increasingly used lately in the subject domain. It is suggested to review and cite the following important references in this regard:  https://doi.org/10.1016/j.swevo.2021.100865;  https://doi.org/10.3390/su12187394; https://doi.org/10.1177/168781401984249; DOI: 10.5772/intechopen.99395; https://doi.org/10.3390/su12051896

4.      A major concern of the study proposed is the lack of validation using field data. The analysis is purely based on simulation, and the traffic dynamics, driver behavior, and complexity of traffic can hardly be handled precisely using such simulation software. Further, the default parameter for the simulation tool should be calibrated and validated to the local conditions (for example, see: https://doi.org/10.3390/su11113018;  doi.org/10.1177/03611981051934001;  ) before making conclusions based on the model output. 

5.      Why only density was selected as the performance metric for the proposed IOT-based traffic signal controller. What about other performance metrics such as queues, average vehicle delay, etc.

6.      What is range(assumed ranged) assumed for vehicles density detections as the accurate estimate of traffic density is important for reliable for signal controller. Similarly the mounted height of the detector in place as well as its performance under heterogenous, non-lane disciplined and adverse weather conditions, should be discussed. If few of these points are not covered, it can be added as study limitations.

7.      Authors should discuss in detail the pros and cons of the proposed methods compared to other state-of-the-art traffic signal control technologies.

8.      VISSIM is the most widely used and recognized traffic simulation tool for various applications, including the problem at hand. Why SUMO was preferred over VISSIM. Is it possible to compare the SUMO results with VISSIM?

9.      Study limitations and prospects for future research works should be included/refined.

10.   The paper also requires a careful proofreading to remove typos and other occasional grammar mistakes.

Author Response

Please see attached file

Author Response File: Author Response.pdf

Reviewer 3 Report

The signal control system presented in this paper, including the use of “inductive loops” and signal control based on the vehicles’ actuation, is similar to the “state-of-practice” signal control systems that have been implemented in the field for about 50 years. Therefore, I do not believe that the paper has any contributions.

Author Response

Please see attached file

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

The revised version is substantially improved. Author (s) have addressed all queries positively. Therefore recommended for publication

Reviewer 2 Report

Authors have provided satisfactory responses to my previous comments. Accordingly thorough modifications were made in the revised draft. Therefore, I recommend it for publishing after a careful language audit.