Modelling parking choice behaviour using possibility theory

Transportation Planning and Technology

Volumn 34, Issue 7, 2011, Pages 647-667

  Ottomanelli, Michele ^a   Dell'Orco, Mauro ^a   Sassanelli, Domenico ^a  

^a POLITECNICO DI BARI   (Italy)

Author keywords

Approximate reasoning; Fuzzy logic; Parking policy; Possibility Theory; Uncertainty; User behaviour

Indexed keywords

APPROXIMATE REASONING; PARKING POLICY; POSSIBILITY THEORY; UNCERTAINTY; USER BEHAVIOUR;

ADVANCED TRAVELER INFORMATION SYSTEMS; DECISION MAKING; FUZZY LOGIC; INFORMATION SYSTEMS; PARKING; SOFT COMPUTING; TRANSPORTATION;

BEHAVIORAL RESEARCH;

DISCRETE CHOICE ANALYSIS; FUZZY MATHEMATICS; INFORMATION SYSTEM; PARKING; TRANSPORTATION SYSTEM; UNCERTAINTY ANALYSIS;

EID: 80051896323     PISSN: 03081060     EISSN: 10290354     Source Type: Journal    
DOI: 10.1080/03081060.2011.602846     Document Type: Article

References (44)

1. Akiyama, T. and Kawahara, T., 1997. Traffic assignment model with fuzzy travel time information. In: Proceedings of the 9th Mini-EURO conference "Fuzzy sets in Traffic and Transport Systems". 17-19 September, Budva, Yugoslavia.
2. Avineri, E., 2005. Soft computing applications in traffic and transportation systems: a review. In: Soft computing: methodologies and applications. Berlin: Springer-Verlag, 17-25.
3. Bates, J.J. and Bradley, M.A., 1986. The CLAMP parking policy analysis model. Traffic Engineering and Control, 27, 410-411.
4. Ben Akiva, M. and Lerman, S., 1985. Discrete choice analysis. Cambridge, MA: MIT Press.
5. Bifulco, G.N., 1993. A stochastic user equilibrium assignment model for the evaluation of parking policies. European Journal of Operational Research, 71, 269-287.
6. Cascetta, E., 2001. Transportation systems engineering: theory and methods. Dordrecht: Kluwer Academic Publisher.
7. Dubois, D., et al., 1996. Aggregation of decomposable measures with application to utility theory. Theory and Decision, 41, 59-95.
8. Dubois, D. and Prade, H., 1983. Ranking fuzzy numbers in the setting of possibility theory. Information Sciences, 30 (2), 183-224.
9. Dubois, D. and Prade, H., 1997. The three semantics of fuzzy sets. Fuzzy Sets and Systems, 90, 141-150.
10. Dubois, D. and Prade, H., 1988. Possibility theory. New York: Plenum Press.
11. Geer, J.F. and Klir, G.J., 1992. A mathematical analysis of information-preserving transformations between probabilistic and possibilistic formulations of uncertainty. International Journal of General Systems, 20, 143-176.
12. Henn, V., 2000. Fuzzy route choice model for traffic assignment. Fuzzy Set and Systems, 116, 77-101.
13. Henn, V., 2005. What is the meaning of fuzzy costs in fuzzy traffic assignment models? Transportation Research Part C, 13, 107-119.
14. Henn, V. and Ottomanelli, M., 2006. Handling uncertainty in route choice models: from probabilistic to possibilistic approaches. European Journal of Operational Research, 175, 1526-1538.
15. Hensher, D.A. and King, J., 2001. Parking demand and responsiveness to supply, pricing and location in the Sydney central business district. Transportation Research Part A, 35, 177-196.
16. Hess, S. and Polak, J., 2004. Mixed Logit estimation of parking type choice. In: Proceedings of the 83rd annual meeting of the Transportation Research Board. 11-15 January, Washington DC.
17. Kikuchi, S. and Chakroborty, P., 2006. Place of possibility theory in transportation analysis. Transportation Research Part B, 40, 595-615.
18. Klir, G.J., 1990. A principle of uncertainty and information invariance. International Journal of General Systems, 17, 249-275.
19. Klir, G. J. and Folger, T.A., 1988. Fuzzy sets, uncertainty and information. Englewood Cliffs, NJ: Prentice-Hall.
20. Koutsopoulos, H.N., Lotan, T., and Yang, Q., 1994. A driving simulator an its application for modeling route choice in the presence of information. Transportation Research Part C, 2, 91-107.
21. Lam, W.H.K., et al., 2006. Modeling time-dependent travel choice problems in road networks with multiple user classes and multiple parking facilities. Transportation Research Part B, 40, 368-395.
22. Lam, W.H.K., Tam, M.L., and Bell, M.G.H., 2002. Optimal road tolls and parking charges for balancing the demand and supply of road transport facilities. In: M.A.P. Taylor, ed. Transportation and traffic theory. Oxford: Elsevier, 561-582.
23. Lambe, T.A., 1996. Driver choice of parking in the city. Socio-Economic Planning Systems, 30, 207-219.
24. Liu, H. X., et al., 2003. A formulation and solution algorithm for fuzzy dynamic traffic assignment model. Transportation Research Record: Journal of the Transportation Research Board, 1854, 114-123.
25. Lotan, T., 1992. Modelling route choice behaviour in the presence of information using concepts of fuzzy sets theory and approximate reasoning. Thesis (PhD). MIT, Boston, MA.
26. Lotan, T. and Koutsopoulos, H.N., 1993. Approximate reasoning models for route choice behavior in the presence of information. In: C.F. Daganzo, ed. Transportation and traffic theory. Amsterdam: Elsevier, 71-88.
27. Medasani, S., Kim, J., and Krishnapuram, R., 1998. An overview of membership function generation technique for pattern recognition. International Journal of Approximate Reasoning, 19, 391-417.
28. Nour Eldin, M.S., El-Reedy, T.Y., and Ismail, H.K., 1981. A combined parking and traffic assignment model. Traffic Engineering and Control, 10, 524-530.
29. Pappis, C. and Mamdani, E., 1977. A fuzzy logic controller to a traffic junction. IEEE Transactions Systems Man Cybernet, 7 (10), 707-717.
30. Perincherry, V., 1994. A generalized approach for the analysis of large scale systems under uncertainty: application to transportation planning and engineering. Thesis (PhD). University of Delaware, Delaware.
31. Polak, J. and Vythoulkas, P., 1993. An assessment of the state-of-the-art in the modelling of parking behaviour (p. 752). Oxford: Transp. Res. Lab, Report no. 752.
32. Polak, J., Axhausen, K.W., and Errigton, T., 1990. The application of the CLAMP to the analysis of parking policy in Birmingham city centre. Proceedings of the 18th PTRC summer annual meeting. 10-14 September, University of Sussex, Brighton, England.
33. Raufaste, E., Da Silva Neves, R., and Mariné, C., 2003. Testing the descriptive validity of possibility theory in human judgments of uncertainty. Artificial Intelligence, 148, 197-218.
34. Shannon, C.E. and Weaver, W., 1948. A mathematical theory of communication. Bell System Technical Journal, 27, 379-423.
35. Teodorović, D., 1999. Fuzzy logic systems for transportation engineering: the state of the art. Transportation Research Part A, 33, 337-364.
36. Teodorović, D. and Kikuchi, S., 1990. Transportation route choice model using fuzzy inference technique. Proceedings of the 1st international symposium on uncertainty modeling and analysis. College Park, 1990. USA: IEEE Computer Society Press, 140-145.
37. Teodorović, D. and Lucic, P., 2006. Intelligent parking systems. European Journal of Operational Research, 175, 1666-1681.
38. Teodorović, D. and Dell'Orco, M., 2005. Multi agent systems approach to parking facilities management. In: N.O. Attoh-Okine and B.M. Ayyub, eds., Applied research in uncertainty modeling and analysis. New York: Springer, 321-339.
39. Teodorović, D. and Vukadinovic, K., 1998. Traffic control and transport planning: a fuzzy sets and neural networks approach. Boston: Kluwer Academic Publishers.
40. Thompson, R.G. and Richardson, A.J., 1998. A parking search model. Transportation Research Part A, 32, 159-170.
41. Wong, S.C., et al., 2000. The development of parking demand models in Hong Kong. Journal of Urban Planning and Development, 126, 55-74.
42. Young, W., 2000. Modeling parking. In: D.A. Hensher and K.J. Button, eds. Handbook of transport modelling, Oxford: Elsevier Science, 409-420.
43. Zadeh, L.A., 1978. Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3-28.
44. Zimmermann, H.J., 1996. Fuzzy set theory and its applications. Boston: Kluwer Academic Publishers.