Research for Nonlinear Model Predictive Controls to Laterally Control Unmanned Vehicle Trajectory Tracking

Round 1

Reviewer 1 Report

Lines 25-26: The statement is not supported by the content.

Line 49: What do the authors mean by a “changing road”?

Figure 2: The angles theta and delta are practically the same. Therefore, the third relation in Equation (3) is not correct. Please correct the figure, represent the vehicle speed on it and correct the equation.

There is a conflict in notations: x is the abscissa of the center of the rear axle of the vehicle, y is the ordinate of the center of the rear axle of the vehicle in Equation (3), but the same notations are used for system input and state in Equations (1), (2), (4), etc.

Please explain the quantity noted by “n” in Equation 5.

It is not clear for which position(s) of the car the mean squared error was calculated and represented in Figure 4. Furthermore, Figure 4 seems to be a repartition of the relative frequency of the mean squared error. Consequently, please give it in percentage.

Figure 8: As it can be seen, the frequency of the lateral deviation decreases as the vehicle speed increases. How can the author explain this? Please insert a figure for high speed as well.

Line 173 and Figure 9: At certain speeds (namely 45, 70, 80 and 90 km/h) the maximum lateral deviation is around 0.5 m, which can be critical and does not guarantee the driving safety as the authors state. It would be useful to compare the precision of the developed model with the precision of other models from the special literature.

Section 4.4 is too brief and the last part of Conclusions is not supported by the text. Could the authors provide further details regarding the precision during the experiment?

Other observations:

Section titles 4.2 and 4.3: Please use capital letters for “Hil”.

It is unusual to start a sentence with citation [x].

In this paper there is a single Algorithm, so it is not necessary to be numbered.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

The paper shows a trajectory tracking control methodology for autonomous driving. The topic is ver up-to date, the introduction of the paper is shows the importance of the topic, however, some more literatures and methodologies can be cited. From line 77, the paper criticize the usage of sequential quadratic programming, because these methodologies were not deals with the calculation time of this methodology. This critic is a bit strange for me, because quadratic programming can be solved by interior poinst methodology based solvers, which are very fast and proves and converges to the global optimum. The problem of these methodologies are usually that their formalism is quite restictive: Boyd, Stephen, Stephen P. Boyd, and Lieven Vandenberghe. Convex optimization. Cambridge university press, 2004.
The methodology and the novelty of the paper should be mentioned in the introduction more clearly and the advantage shuold be highlighted better in 1-2 sentences.
The applied methodology is described, well, maybe instead of using a simple monte carlo methodology, a more advanced methodology from design of experiments would be interesting for sampling. The applicability of the proposed methodology is validated by real experiment. The results should be discussed in more details in the results and discussion section.

In Line 315, instead of using some shortcomings, which very hardly devaluates your work, it would be better to use some explicit advice, what should be improved, so the future research directions. For example, a dedicated robust design optimization tool will be used, which can handle large number of parameters and some more advanced method from the field of design of experiments, which can handle the uncertainties more accurately. I would like to recommend the following robust design optimizer project (http://www.agros2d.org/artap/), which integrates all of the above mentioned missing methods in a systematic way:
Pánek, David,et al ” Ārtap: robust design optimization framework for engineering applications.” arXiv preprint arXiv:1912.11550 (2019).

This is my same advice for the next sentence, as well, which says higher speeds were not testd is not lucky, please do not judge yourself. Better to use more neutral and objective sentences with the advantages and the limitations, but please avoid from this good and bad. The beginning of the conclsion and the abstract is good and clearly says the motivation. I think it will be an interesting and good paper, but please ask your colleague to make a proofread in this paper to improve these kind of sentences, which judge yourself negatively, these indices the feeling that this paper is not good.

Author Response

Please see the attachment.

Author Response File: Author Response.docx