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Modern - Modelling demand for railway networks

Grant number: 19/07428-2
Support type:Regular Research Grants
Duration: July 01, 2020 - December 31, 2021
Field of knowledge:Engineering - Transportation Engineering - Transportation Planning
Cooperation agreement: University of Birmingham
Principal Investigator:Cassiano Augusto Isler
Grantee:Cassiano Augusto Isler
Principal investigator abroad: Clive Roberts
Institution abroad: University of Birmingham, England
Home Institution: Escola Politécnica (EP). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Assoc. researchers: Marcelo Blumenfeld Mendonca

Abstract

The problem addressed in this project is the mode choice estimation of intercity trips in Brazil if railway passenger services were to compete with existing transport choices. This study carries particular relevance in that it provides evidence of the potential demand under scenarios where different train services run between cities over a specific region of the country using different sets of technologies. This problem is important to be studied from the academic since applying different mode choice modelling approaches to better understand their hypotheses and incurring results can improve estimations on travel behavior and choice. In practical terms, providing adequate estimations on travel behavior is important to the government, which is usually involved in co-financing large and complex infrastructure projects, and private companies, which eventually are involved either in the construction and/or the operation of such transportation systems. In order to achieve these goals we consider applying the Random Utility Model (RUM) and Random Regret Model (RRM) approaches to estimate the mode choice of potential users of hypothetical intercity railway services in the Southeastern Region of Brazil considering a database of answers from a Stated Preference Survey previously conducted. After assessing the results of these models in terms of adherence to the answers of the survey; we will estimate the mode choice from both approaches under different values for the considered attributes (travel time, cost, frequency, etc.) and, finally, compare the hypothesis and modeling results from both approaches and assess the replicability of the models from international databases. Thus, the scientific contribution of this project is the investigation of alternatives methods to specify utility functions based on the Random Utility Maximization Approach, as well providing good estimations of mode choices based on different assumptions to these models. Moreover, the outcomes of this project will contribute to better understand the assumptions and modeling approaches for discrete choice modeling based on the Regret Theory, and will also provide insights on its differences with the utility approach which will be useful to the research community. Research findings from the project will contribute to the establishment of a baseline framework for demand forecast modelling to be used in future project appraisals in Brazil and possibly elsewhere. Similarly, model calibration from different contexts will expand the model applicability in cost-benefit calculations for the planning of future railway services. As an immediate output and performance indicators of the success of the project, the researchers foresee the publication of at least two research papers and/or potential conference presentations on the findings and recommendations. Besides the research publication, we expect that the grant provided by the FAPESP and University of Birmingham grant will enhance the relations between the institutions and the wider community. Thus, the results of the project will also be measured through the engagement achieved with academics, government, and industry in both countries. More specifically, success will be assessed through attendances to dissemination events using metrics of individuals and organizations represented. (AU)