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Article
Peer-Review Record

Investigation of Factors Associated with Heavy Vehicle Crashes in Iran (Tehran–Qazvin Freeway)

Sustainability 2023, 15(13), 10497; https://doi.org/10.3390/su151310497
by Ali Tavakoli Kashani 1,2,*, Kamran Zandi 1,3 and Atsuyuki Okabe 4
Reviewer 1: Anonymous
Reviewer 2:
Reviewer 3:
Sustainability 2023, 15(13), 10497; https://doi.org/10.3390/su151310497
Submission received: 10 April 2023 / Revised: 17 May 2023 / Accepted: 30 May 2023 / Published: 4 July 2023
(This article belongs to the Section Sustainable Transportation)

Round 1

Reviewer 1 Report

The work in this paper is very meaningful to investigate the contribution of heavy vehicles in freeway crashes and uncover other causal factors. The method is novel. Specifically, a binary logit model was estimated from the data to determine if there was a significant correlation between recognized factors and the likelihood of the crash. The logit modeling results clearly illustrate important relationships between various risk factors and occupant injury in which heavy vehicles were recognized as one of the most important factors in this study. The whole paper is well organized and the investigation procedure is rigorous. Thus, I agree to accept this paper in a revised version. Below are my comments:

-Please highlight the contributions of the work. In its current form, the contributions are not pointed out explicitly;

-The speed of the truck is a key factor that might be correlated to the crash. However, except for this variable, the sideslip angle is a vital variable in the electronic stability control system of the vehicle. Although it is hard to obtain, readers would be willing to see the discussion on the excessive steering causing the crash as well. In that regard, please consider the sideslip angle as a variable and have some discussion of its importance to the safety of the crash. Some related works can be found in: autonomous vehicle kinematics and dynamics synthesis for sideslip angle estimation based on consensus kalman filter; estimation on imu yaw misalignment by fusing information of automotive onboard sensors; automated vehicle sideslip angle estimation considering signal measurement characteristic; imu-based automated vehicle body sideslip angle and attitude estimation aided by gnss using parallel adaptive kalman filters; improved vehicle localization using on-board sensors and vehicle lateral velocity. Please discuss these works either in the introduction or the results discussion section to mention that the lateral motion will also cause crash issues.

-Will the autonomous driving system benefit heavy vehicles or contribute to reducing crashes? Please incorporate the autonomous driving system into the discussion section as well. Some related works should be considered: automated driving systems data acquisition and processing platform; yolov5-tassel: detecting tassels in rgb uav imagery with improved yolov5 based on transfer learning.

-The format of the table is not consistent within the paper. Please unify the format of the tables in the paper.

Author Response

Please read the attached file.

Author Response File: Author Response.pdf

Reviewer 2 Report

 This paper proposed a binary logit model to estimate if there is a significant correlation between recognized factors and the likelihood of a crash. The model method of assessing various risk factors and occupant injury is reasonable and well-supported. comments are below:

1. Literature takes up too much room in the whole paper. The summary table is helpful, but not all the papers are relevant to heavy vehicle accidents. 

2. Descriptive statistics of study variables didn't mention the data volume, data quality and data processing

3. conclusion is weak, why the model is important and better than many others and any limitations?

 

 

Moderate editing of English language

Author Response

Please read the attached file.

Author Response File: Author Response.docx

Reviewer 3 Report

Dear authors!

The occurrence of traffic accidents is the result of random variables that may depend on weather conditions, days of the week, vehicle class. The systematization of these factors and the development of a prediction accidents model is an urgent task. Therefore, I recommend paying more attention to the proposed prediction accidents model.

I recommend adding to fig. units of measure and correct the number Main Cause of Crash Regarding the Time.

And also, Fig 2. – 4 and their descriptive material should be placed in Inferential statistics. In Conclusion, pay attention to general conclusions, model comparison results, and future research.

Author Response

Please read the attached file.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

My comments were well addressed and thank you for the revision.

proofreading on grammar

Author Response

Dear sir/madam,

Thank you for the reviewing the article "Investigation of Factors Associated with Heavy Vehicle Crash in Iran ‎‎(Tehran-Qazvin Freeway)‎" submitted to your journal. We would like to thank the reviewers for their careful reading and thoughtful and kind comments on the submitted draft. As the required minor revision, we have carefully taken their comments into consideration and have revised our paper accordingly.

We hope our work will be accepted for the publication in your esteemed journal.

your sicerelly

Ali Tavakoli Kashani

Author Response File: Author Response.pdf

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