Data-consistent fuzzy approach for online driver behavior under information provision

Transportation Research Record

Volumn , Issue 1803, 2002, Pages 76-86

  Peeta, Srinivas ^a   Yu, Jeong W ^a  

^a PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMOBILE DRIVERS; COMPUTATIONAL METHODS; DATA REDUCTION; FUZZY SETS; INFORMATION SCIENCE; ONLINE SYSTEMS;

ROUTING DECISION;

MOTOR TRANSPORTATION;

EID: 0036992552     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/1803-11     Document Type: Article

References (26)

1. Wardman, M., P. W. Bonsall, and J. D. Shires. Driver Response to Variable Message Signs: A Stated Preference Investigation. Transportation Research C, Vol. 5, No. 6, 1997, pp. 389-405.
2. Peeta, S., J. L. Ramos, and R. Pasupathy. Content of Variable Message Signs and On-Line Driver Behavior. In Transportation Research Record: Journal of the Transportation Research Board, No. 1725, TRB, National Research Council, Washington, D.C., 2000, pp. 102-108.
3. Schofer, J. L., F. S. Koppelman, and W. A. Charlton. Perspectives on Driver Preferences for Dynamic Route Guidance Systems. In Transportation Research Record 1588, TRB, National Research Council, Washington, D.C., 1997, pp. 26-31.
4. Ben-Akiva, M., and S. R. Lerman. Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press, Cambridge, Mass., 1985.
5. Abdel-Aty, M. A., R. Kitamura, and P. P. Jovanis. Using Stated Preference Data for Studying the Effect of Advanced Traffic Information on Drivers' Route Choice. Transportation Research C, Vol. 5, No. 1, 1997, pp. 39-50.
6. Jha, M., S. Madanat, and S. Peeta. Perception Updating and Day-to-Day Travel Choice Dynamics in Traffic Networks with Information Provision. Transportation Research C, Vol. 6, No. 3, 1998, pp. 189-212.
7. Srinivasan, K. K., and H. S. Mahmassani. Modeling Inertia and Compliance Mechanisms in Route Choice Behavior Under Real-Time Information. In Transportation Research Record: Journal of the Transportation Research Board, No. 1725, TRB, National Research Council, Washington, D.C., 2000, pp. 45-53.
8. Lam, W. H. K., and K. S. Chan. A Model for Assessing the Effects of Dynamic Travel Time Information via Variable Message Signs. Transportation, Vol. 28, 2001, pp. 79-99.
9. Nakayama, S., and R. Kitamura. Route Choice Model with Inductive Learning. In Transportation Research Record: Journal of the Transportation Research Board, No. 1725, TRB, National Research Council, Washington, D.C., 2000, pp. 63-70.
10. Teodorović, D. Fuzzy Sets Theory Applications in Traffic and Transportation. European Journal of Operational Research, Vol. 74, 1994, pp. 379-390.
11. Teodorović, D. Fuzzy Logic Systems for Transportation Engineering: The State of the Art. Transportation Research A, Vol. 33, No. 5, 1999, pp. 337-364.
12. Teodorović, D., and M. Kalić. A Fuzzy Route Choice Model for Air Transportation Networks. Transportation Planning and Technology, Vol. 19, 1995, pp. 109-119.
13. Lotan, T., and H. N. Koutsopoulos. Models for Route Choice Behavior in the Presence of Information Using Concepts from Fuzzy Set Theory and Approximate Reasoning. Transportation, Vol. 20, 1993, pp. 129-155.
14. Lotan, T., and H. N. Koutsopoulos. Approximate Reasoning Models for Route Choice Behavior in the Presence of Information. In Transportation and Traffic Theory, 12th International Symposium on the Theory of Traffic Flow and Transportation, Berkeley, Calif., 1993, pp. 71-88.
15. Lotan, T., and H. N. Koutsopoulos. Modeling Default Behavior in the Presence of Information and Its Application to the Route Choice Problem. International Journal of Intelligent Systems, Vol. 14, 1999, pp. 501-533.
16. Lotan, T. Effects of Familiarity on Route Choice Behavior in the Presence of Information. Transportation Research C, Vol. 5, No. 3, 1997, pp. 225-243.
17. Lotan, T. Modeling Discrete Choice Behavior Based on Explicit Information Integration and Its Application to the Route Choice Problem. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 28, No. 1, 1998, pp. 100-114.
18. Pang, G. K. H., K. Takahashi, T. Yokota, and H. Takenaga. Adaptive Route Selection for Dynamic Route Guidance System Based on Fuzzy-Neural Approaches. IEEE Transactions on Vehicular Technology, Vol. 48, No. 6, 1999, pp. 2028-2040.
19. Henn, V. Fuzzy Route Choice Model for Traffic Assignment. Fuzzy Sets and Systems, Vol. 116, 2000, pp. 77-101.
20. Wonneberger, S. Generalization of an Invertible Mapping Between Probability and Possibility. Fuzzy Sets and Systems, Vol. 64, 1994, pp. 229-240.
21. Geer, J. F., and G. I. Klir. A Mathematical Analysis of Information-Preserving Transformations Between Probabilistic and Possibilistic Formulations of Uncertainty. International Journal of General Systems, Vol. 20, 1992, pp. 143-176.
22. Lapointe, S., and B. Bobée. Revision of Possibility Distributions: A Bayesian Inference Pattern. Fuzzy Sets and Systems, Vol. 116, 2000, pp. 119-140.
23. Tsoukaias, L. H., and R. E. Uhrig. Fuzzy and Neural Approaches in Engineering. John Wiley and Sons, Inc., New York, 1997.
24. Civanlar, M. R., and H. J. Trussell. Constructing Membership Functions Using Statistical Data. Fuzzy Sets and Systems, Vol. 18, 1986, pp. 1-13.
25. Mauris, G., V. Lasserre, and L. Foulloy. Fuzzy Modeling of Measurement Data Acquired from Physical Sensors. IEEE Transactions on Instrumentation and Measurement, Vol. 49, No. 6, 2000, pp. 1201-1205.
26. Dubois, D., and H. Prade. Unfair Coins and Necessity Measures: Towards a Possibilistic Interpretation of Histograms. Fuzzy Sets and Systems, Vol. 10, 1983, pp. 15-20.