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Article
Peer-Review Record

Adaptive Cruise Control for Intelligent City Bus Based on Vehicle Mass and Road Slope Estimation

Appl. Sci. 2021, 11(24), 12137; https://doi.org/10.3390/app112412137
by Fei-Xue Wang, Qian Peng, Xin-Liang Zang * and Qi-Fan Xue
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Appl. Sci. 2021, 11(24), 12137; https://doi.org/10.3390/app112412137
Submission received: 29 October 2021 / Revised: 3 December 2021 / Accepted: 10 December 2021 / Published: 20 December 2021
(This article belongs to the Special Issue Statistical Learning: Technologies and Industrial Applications)

Round 1

Reviewer 1 Report

This paper proposed an adaptive cruise control for intelligent buses considering vehicle mass and road grade dynamics. The MPC framework is standard and the road geometrics have also been studied in ACC models, but the consideration of passenger weight is new. The organization is clear and the method is solid. I enjoyed reading it and have only minor comments regarding the writing. 

 

1. The paper lacks a clear statement of research gap. The literature review is a simple list of related studies. The research gaps in this area were not clearly identified, and thus it makes readers keep wondering what is the additional contribution of this work. Please add one paragraph explicitly pointing out what the research gaps are and how they are addressed in this paper. 

 

2. Since you have already a notation list, why not include all variables and parameters in it?

 

3. What does s denote in Eq. 1?

 

4. Line 116, looked table or lookup table?

 

5. Line 276, should be Fig. 7. 

 

6. Fig. 7, where is the trajectory from? Is it a naturalistic trajectory? Same questions for Fig. 8. 

 

7. There are a few typos. Please check carefully in the revision. 

 

Author Response

Please see the attachment

Author Response File: Author Response.docx

Reviewer 2 Report

In the mass and road estimation approach, you did not cite approaches based on ML approaches like for instance some approach base on random forrest. Maybe you can add some references to those works.
In your model, you don't take any sliding into account, which may impact the converge of the mass and grade estimate? May be you may comment on it?
For the optimization, you find a balance between different optimization objectives, some are mandatory (like the minimal distance) and are secondary objectives, like the jerk. There is very little information about the priorisation of the objectives. 
When presenting the results, you show the evolution of the distance between the current bus and the preceeding bus. However, it would have been interesting to compare also with the current bus that does not implement the road grade and mass estimation. A comparison with another ACC implementation would also give a good estimate on the performance.

Author Response

Please see the attachment

Author Response File: Author Response.docx

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