Fuzzy PROMETHEE model for public transport mode choice analysis

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.