Simulation Evaluation of a Current Limiting Scheme in an Urban Rail Transit Network
Round 1
Reviewer 1 Report
Minor revision is required. A few grammatical errors are detected. Detailed comments are in the attached file.
Comments for author File: 
Comments.pdf
Author Response
Dear Reviewer,
Thank you for your comments on the revision of my article. After carefully reading your review comments, I have finished revising your comments.
As a result of your suggestions, the revised articles are better. Thanks again to your help.
Kind regards,
Author
Author Response File: 
Author Response.docx
Reviewer 2 Report
Overall the paper is well written and is very interesting. The topic is also very important considering the problems being faced by the rail transit systems in scheduling, accommodating passenger flow, reducing delay and others. Following are some of the comments:
1) Please provide a reference to "2020 subway peak
hour passenger flow statistics provided by Dalian Metro Group Co., Ltd." on Page 2, line 55.
2) Line 58 of Page 2, says "the validity
and practicability of the model were verified based on specific examples". Can you please provide some examples here.
3) As each train station is different and time to transfer from one station to other differs depending on various factors such as size of the station, passenger volume and other. How the simulation models considers the time variation in transferring from one station to other.
4) How dynamic is this model? Has this model been tested for different conditions.
5) The paper shows the mathematical model but does this runs an Algorithm which is not mentioned in the paper.
Author Response
Response to Reviewer 2
Point 1: Please provide a reference to "2020 subway peak hour passenger flow statistics provided by Dalian Metro Group Co., Ltd." on Page 2, line 55.
Response 1: Since this project belongs to Dalian Metro Group Co., Ltd., the relevant data is still in the confidential stage, please forgive me for not being able to provide it at present
Point 2: Line 58 of Page 2, says "the validityand practicability of the model were verified based on specific examples". Can you please provide some examples here.
Response 2: In Figure 7, the process of modeling, input, output, and verification of the simulation research work is explained. In the fourth chapter (Results) of the paper, the experiment of model verification was done. For this model, the main thing that has a direct impact on the experiment is the accuracy of the passenger flow input in the model. Therefore, this paper studies whether the model can reflect the passenger flow changes in the real scene according to the two errors of the passenger flow experimental value and the observed value in the test results.
Point 3: As each train station is different and time to transfer from one station to other differs depending on various factors such as size of the station, passenger volume and other. How the simulation models considers the time variation in transferring from one station to other.
Response 3: In Section 3.2, this paper clarifies the information communication methods of passengers, stations, and train agents. The model checks the train speed and train timetable, so that the passengers' on-board time and transfer time can be calculated.
Point 4: How dynamic is this model? Has this model been tested for different conditions.
Response 4: In order to demonstrate the effect of the current limiting scheme obtained under the multi-objective programming model, three groups of experiments are carried out on the basis of the above background in the fourth chapter. The first group does not take current limiting measures, in addition to being used for comparison with the latter two groups of experiments, it is also used as the basis for validating the model; The second group, on the basis of the first group of experimental results, conducts flow limitation at the same level according to experience for several stations with large passenger flow or the front stations in the section with high passenger flow density; The third group performs current limiting according to the optimized current limiting scheme. By comparing the results of the second and third groups of experiments, the evaluation and suggestions of the optimized current limiting scheme are given.
Point 5: The paper shows the mathematical model but does this runs an Algorithm which is not mentioned in the paper.
Response 5: The algorithms involved in this model belong to the previous research results of the research group and have not yet been published. Therefore, it cannot be cited in the paper.
Author Response File: Author Response.docx
Reviewer 3 Report
A simulation-based tool is studied for the scheduling principle of the current limiting scheme. A meso-scale simulation model is proposed based on AnyLogic to evaluate the current limiting scheme. This study has some contribution to the world knowledge system.However, the author should improve the paper from the following aspects.
1. Please clarify the contribution with the literature review. What is the scope of this study, station-, line- or network-level?
2. What is the definition and necessity of a mesoscopic simulation?
3. Please clarify the legend of Figure 1.
4. Line 189: tm represents the number but previous ti indicates the time. Please change the designation of either one. X in Figure 2 are vague. What is bi?
5. Please eliminate the Chinese in Eq.1.
6. Please add a problem statement section to integrate all background and definitions of this study. It is confusing to mix model setting and explanations together.
7. Please clarify the feasibility and verifiability of such model in 3.2.1 with Figure 3 about the principle of exchanging data.
8. According to Conclusion 2, What is it mean by “The model is especially suitable for evaluating the current limiting scheme under the multi-objective planning model”
Author Response
Response to Reviewer 3
Point 1: Please clarify the contribution with the literature review. What is the scope of this study, station-, line- or network-level?
Response 1: According to your comments, we have modified lines 126 to 135 in the paper. Illustrates the contribution and establishes the scope of the study to be at the network level.
Point 2: What is the definition and necessity of a mesoscopic simulation?
Response 2: According to your comments, the definition and necessity of mesoscopic simulation are explained in lines 60-68 of the text.
Point 3: Please clarify the legend of Figure 1.
Response 3: Added related notes at 174-175 of the paper.
Point 4: Line 189: tm represents the number but previous ti indicates the time. Please change the designation of either one. X in Figure 2 are vague. What is bi?
Response 4: The definition of tm has been corrected(209-210). Figure 2 has also been processed. The definition of bi is in line 207 of the paper.
Point 5: Please eliminate the Chinese in Eq.1.
Response 5: The Chinese part has been deleted.
Point 6: Please add a problem statement section to integrate all background and definitions of this study. It is confusing to mix model setting and explanations together.
Response 6: Newly added section 3.2.1 as part of the problem statement.
Point 7: Please clarify the feasibility and verifiability of such model in 3.2.1 with Figure 3 about the principle of exchanging data.
Response 7: Section 3.2 is the model design part. The first set of experiments mentioned in lines 454 to 455 of the article analyzed the feasibility of the model.
Point 8: According to Conclusion 2, What is it mean by “The model is especially suitable for evaluating the current limiting scheme under the multi-objective planning model”
Response 8: Because most multi-objective programming models will consider the comprehensive impact of a series of indicators such as fairness, benefit type, and delay on the evaluation scheme, it can be seen from section four in this paper that the simulation evaluation model studied can be evaluated for different indicators.
