Estimation of Travel Demand Models with Limited Information: Floating Car Data for Parameters’ Calibration

Round 1

Reviewer 1 Report

Please include “Big Data” in the Keywords.

Please note that reference [32] appears before [31]. More specifically, [32] appears on page 8, line 302, and [31] appears on page 13, line 558.

Please note that Reference [37] is missing from the manuscript although it appears in the Reference List at the end of the paper.

Please include the source for the geographical background of Figures 4, 5 and 9.

Although Figure 1 is a very comprehensive Figure, I would like to ask the authors to consider the idea to clarify schematically the conditions under which the arrow from “observed data” is directed to “ITS” and the conditions under which the arrow from “observed data” is directed to “transport planning”.

Page 8, lines 305-306, “…may be combined with traditional zoning techniques…”: My suggestion is to provide within the manuscript some more details concerning the so-called “traditional zoning techniques”.

Page 8, line 310-311, “…providing statistics on historical…”: Which is the time horizon for the so-called “historical data” for the purposes of your research (e.g., min. number of years). Please include your answer within your manuscript.

Page 14, line 593, “The reference period of analysis h is 24 hours of a workday:…”: Please define “workday” for the purposes of your research. For example, Saturday often presents the traffic characteristics of a typical workday (Monday to Friday). Please justify why you exclude Saturday.

Page 14, lines 597-599, “The number of users who use public transport is negligible in the study area. Therefore, it is acceptable that the private car mode is the only available motorized mode for trips inside the study area.”: What about other motorized modes like motorcycles, mopeds? (Please refer to the limitations of your work, as they are included in the Section of Conclusions).

Page 17, Figure 7: Please note that the sum of all the percentages is 100.01% which is different from 100.00%.

Page 17, Figure 8: Please change “hours” to “Hours” in the title of x-axis.

Page 18, Figure 9: Please note that according to the label of the specific Figure, the same number appears in successive scales (e.g., 0-500, 500-1000, 1000-2000 etc.). My suggestion is to change the scales to: 0-500, 501-1000, 1001-2000 etc.).

Page 21, “…that today, several vehicles have embedded GPS…”: My suggestion is to provide an estimate, if possible, concerning the existing percentage of vehicles which have embedded GPS and the future trends.

Section 5. Conclusions: My suggestion is to extent the part of the conclusions which concerns your recommendations and to address it to specific stakeholders who will benefit from your findings (e.g., Public Administration Authorities, Local Authorities, Urban Traffic Systems Operators, Users etc.).

 

Author Response

The authors would like to thank the reviewers for the constructive comments and the possibility of improving the quality of their paper. The authors greatly appreciate the kind advices.

The authors incorporated the feedbacks in the revised manuscript accordingly. For each comment, the authors provided a response as follows.

Author Response File: Author Response.pdf

Reviewer 2 Report

This research work models transport demand systems and predicts mobility patterns through the integrated use of traditional data and floating car data.

Although these models have been studied in the literature, a new approach based on big data and CDF incorporation is proposed.

The manuscript is well structured and written in general, with exceptions proposed below and a simple revision of the English.

The experimentation and the proposed example with real-world data perfectly exemplify and justify the contributions.

Some suggestions for improvement:

Since this work will be published in sustainability, it is advisable to refer to a related aspect or relate its contents, objectives, and contributions.

Certain parts of the manuscript, such as the conclusions, the introduction and state of the art, are repetitive. Definitions and explanations of objectives, contributions and achievements are repeated, are excessive and do not facilitate clarity of reading.

I do not understand the reasons for including contributions in state-of-the-art. That is subsection 2.3 into section 2.  In this subsection, no previous reference is analysed, and it can go perfectly in the introduction, simplifying and avoiding repetitions.

Review in line 710 (subsection 4.3) the reference to direct estimation section 4.1.

References in 4.3.2 (lines 738 and 744) to section 4 must be specified.

References [26] to the parameters in 4.3.1 are not understood. To facilitate reading and understanding, most of the explanations must be self-included

Finally, it would be of interest to point out that in the experimentation, computer tools or applications have been used for data processing or, where appropriate, that it has been developed for it. Also, make the data used available for future research and thus facilitate experimentation and subsequent comparison.

Author Response

The authors would like to thank the reviewers for the constructive comments and the possibility of improving the quality of their paper. The authors greatly appreciate the kind advices.

The authors incorporated the feedbacks in the revised manuscript accordingly. For each comment, the authors provided a response as follows.

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors proposed the combined use of emerging big data, conventional statistics and travel demand models for reciprocity. Although the topic is interesting and timely, there are a number of aspects that should be improved to make the paper publishable.

 

• The theoretical contribution is not clearly summarised in the introduction and conclusions sections. How do the findings specifically contribute to the existing literature, particularly in the research domains of sustainability?

 

• The research gap should be identified in a more precise way. There are a number of previous works that investigated the combined uses of multi-source travel data in a conventional transport model (suggest reading, for instance, doi.org/10.1016/j.tbs.2021.04.012, doi.org/10.3390/ijgi8040187 and doi.org/10.1177/2399808320924433). However, the authors failed to make the linkage and clarify the contribution of this particular study to the literature.

 

• In the conclusions or results section, the authors should highlight whether/how the biases by using FCD to infer travel patterns can be mitigated in the proposed method.

 

• There are some minor corrections to note: (a) scale bars should be added to all the maps in the manuscript, and (b) Table 5 should be moved to section 4.3.2.

 

 

Author Response

The authors would like to thank the reviewers for the constructive comments and the possibility of improving the quality of their paper. The authors greatly appreciate the kind advices.

The authors incorporated the feedbacks in the revised manuscript accordingly. For each comment, the authors provided a response as follows.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

The revised version looks much better, and there are no more comments from my side.