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Fuzzy PROMETHEE model for public transport mode choice analysis.

Laila Oubahman1, Szabolcs Duleba1,2

  • 1Department of Transport Technology and Economics, Faculty of Transportation and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem rkp. 3., Budapest, 1111 Hungary.

Evolving Systems
|April 16, 2024
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Summary

This study introduces an integrated model for public transportation mode choice, combining subjective and objective measures. The new method enhances accuracy by incorporating fuzzy logic and group preference ranges, supporting better transit decisions.

Keywords:
FuzzyGAIA planeMCDAMode choicePROMETHEEPublic transport

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Area of Science:

  • Transportation Science
  • Decision Science
  • Operations Research

Background:

  • Public transportation service quality is crucial for understanding passenger preferences.
  • Existing methods often rely solely on subjective scoring, limiting accuracy.
  • There's a need for models integrating objective and subjective measures for mode choice analysis.

Purpose of the Study:

  • To develop an integrated model for public transportation mode choice.
  • To combine subjective passenger preferences with objective measures like distance and time.
  • To refine group consideration in mode choice analysis by including preference ranges.

Main Methods:

  • Utilized Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE) for tangible and intangible criteria evaluation.
  • Integrated fuzzy theory to handle vague responses and reduce scoring uncertainty.
  • Employed Graphical Analysis for Interactive Aid (GAIA) for attribute interaction visualization and sensitivity analysis.

Main Results:

  • Developed an integrative method that is less subjective than traditional models.
  • Incorporated group preference ranges alongside the mean for refined analysis.
  • Demonstrated the model's efficiency through a case study in Budapest, supporting underground service quality.

Conclusions:

  • The proposed model offers a more robust and less subjective approach to public transportation mode choice.
  • The integration of fuzzy logic and group preference ranges enhances the analysis of passenger behavior.
  • The methodology provides a strong foundation for fuzzy inference systems to aid passenger mode choice in dynamic environments.