Non-Shortest Paths Route Choice Model Based on Fuzzy Preference Relations

Authors

  • M. Ridwan RWTH Aachen

Abstract

This paper presents a new methodology for route based on fuzzy preference relations. The core of the model is FiPV (fuzzy-individualle Praeferenzen von Verkehrstilnehmern or fuzzy traveler preferences) , that is an adjustment of Orlovsky's fuzzy choice function for travel decisions. The proposed model is the first application of fuzzy individual (preference-based) choice in travel demand modeling and also the first in this class to consider spatial knowledge of individual travelers in route choice. It is argued that travelers do not or cannot always follow perfect maximization principle. We formulate therefore a model that also takes into account the travelers with non-perfect maximizing behavior. Although the model is not yet supported by empirical evidence, it shows a more transparent structure than those of/he Conventional dynamic route Choice models.

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References

Bisdorff, R. 2000. Logical foundation of fuzzy preferential systems with application to the electre decision aid methods. Computers & Operations Research, 27(7-8), 673-687.

Buchanan, J.T., E.J. Henig and M.I. Henig. 1998. Objectivity and subjectivity in the decision making process. Annals of Operations Research, 80, 333-345.

Cascetta, E. 2001. Transportation Systems Engineering: Theory and Methods. Dordrecht: Kluwer Academic Publishers.

Conlisk, J. 1996. Why Bounded Rationality? Journal of Economic Literature, XXXIV (June), 669-700.

Fodor, J., S. Orlovsky, P. Perny, and M. Roubens. 1998. The Use of Fuzzy Preference Models in Multiple Criteria Choice, Ranking and Sorting. In Fuzzy sets in decision analysis, operation research, and statistics (pp. 69-101), ed. R. Slowinski. Boston: Kluwer Academic Publishers.

Gilboa, I. and D. Schmeidler. 1999. A Theory of Case-Based Decisions. (Preliminary Draft - February ed.). Tel Aviv: The Foerder Institute for Economic Research, Tel-Aviv University.

Golledge, R. 1997a. Dynamics and ITS: Behavioral Responses to Information Available from ATIS (Resource Paper). Paper presented at the IATBR 8th meeting: Challenges and Opportunities in Travel Behavior Research and Application, The University of Texas at Austin, September 21-25.

Golledge, R. G. 1997b. Defining the criteria used in path selection. In Activity-based approach to travel analysys (pp.151-169), eds. D. Ettema and H.J.P. Timmermans. Oxford, UK: Pergamon.

Harsanyi, J.C. 1996. Utilities, preferences, and substantive goods. Paper presented at the third meeting of the Society for Social Choice and Welfare, Maastricht, June 22.

Henn, V. 2000. Fuzzy route model for traffic assignment. Fuzzy sets and systems, 116(1), 77-101.

Henn, V. 2002. What is the meaning of Fuzzy Costs in Fuzzy Traffic Assignment Models? Paper presented at the 13th Mini-EURO Conference Handling Uncertainty in the Analysis of Traffic and Transportation Systems. Bari, Italy, 10 - 12 June.

Hoogendoorn, S.P., G. Copinga, and U. Kaymak. 1998. Perspectives of Fuzzy Logic in Traffic Engineering: Reviews and Annotated Bilbiography. Research Report. Delft: TRAIL Research School.

Jan, O., A.J. Horowitz, and Z.R. Peng. 2000. Using GPS Data to Understand Variations in Path Choice. Paper presented at the TRB 79th Annual Meeting, Washington, DC., January 9-13.

Mahmassani, H.S. and R.C. Jou. 1998. Bounded Rationality in Commuter Decision Dynamics: Incorporating Trip Chaining in Departure Time and Route Swithcing Decions. In Theoretical Foundations of Travel Choice Modeling (pp 201-229, eds. T. Gaerling, T. Laitila and K. Westin. New York: Elsevier

Nakayama, S., R. Kitamura and S. Fujii. 2000. Drivers' route choice heuristics and network behaviour: a simulation study using generic algorithms. Paper presented at the 9th IABTR Conference, Sheraton Mirage Gold Coast, Queensland, Australia.

Orlovsky, S. A. 1978. Decision-making a fuzzy preference relation. Fuzzy Sets and Systems 1, 155-167

Peeta, S. and A.K. Ziliaskopoulos. 2001.Foundations of Dynamic Traffic Assignment: The Past, the Present and the Future. Networks and Spatial Economics, 1(3/4) 233-265

Ramming, M.S. 2002. Network Knowledge and Route Choice. Unpublished PhD Dissertation (forthcoming). Cambridge, MA: MIT

Ran, B. and D. E. Boyce. 1996. Modeling dynamic transportation networks: an intelligent transportation system oriented (ITS) approach, 2nd rev. ed. Berlin: Springer-Verlag.

Ridwan, M. 2000. Ranking and choice algorithm with fuzzy preference model (first draft version). Unpublished Manuscript (in German). Aachen: RWTH

Ridwan, M. 2002. Fuzzy Preference Based Traffic Assignment Problem. Paper accepted for presentation in the ISTTT15 Workshop on Intelligent Transport Systems: Emerging technologies and methods in transportation and traffic. Adelaide, 19 July 2002 and will appear in a special issue of Transportation Research Part C: Emerging Technologies (guest editor: Michael A. P. Taylor).

Sheffi, Y. 1985. Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods. Englewood Cliffs: Prentice-Hall.

Simon, H.A. 1955. A behavioral model of rational choice. Quarterly Journal of Economics, 69, 99-118.

Teodorovis, D. 1999. Fuzzy logic systems for transportation engineering: the state of the art. Transportation Research Part A: Policy and Practice, 33(5), 337-364.

Watling, D. 1999. Stability of the stochastic equilibrium assignment problem: a dynamical systems approach. Transportation Research Part B: Methodological, (33)4, 281-312.

Zadeh, L.A. 1965. Fuzzy sets. Information and Control, 8, 338-353

Zimmerman, H.J. 1987. Fuzzy Sets, Decision Making, and Expert Systems. Boston: Kluwer Academic Publishers.

Zimmerman, H.J. 1996. Fuzzy set theory and its applications. (3rd ed). Boston: Kluwer Academic Publishers.

Zimmerman, H.J. 1999. Intelligente Technologien un data Mining zur Unterstutzung des Verkehrsmanagemetns. Paper presented at the Heureka '99, Optomierung in Verkehr und Transport. Tagungsbericht, Karlsruhe: M. Boltze, H. Keller & et. al. (eds), Maret 3-4, FGSV Verlag.

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How to Cite

Ridwan, M. (2017). Non-Shortest Paths Route Choice Model Based on Fuzzy Preference Relations. Journal of Regional and City Planning, 14(2), 69-81. Retrieved from https://journals.itb.ac.id/index.php/jpwk/article/view/4299

Issue

Vol. 14 No. 2 (2003)

Section

Research Articles

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