Evaluation of driver satisfaction of travel information on variable message signs using fuzzy aggregation

Journal of Advanced Transportation

Volumn 42, Issue 1, 2008, Pages 5-22

  Lee, Dongmin ^a   Lee, Chungwon ^b   Pietrucha, Martin T ^c  

^a Korea Transport Institute (KOTI)   (South Korea)

^b University of Seoul   (South Korea)

^c PENNSYLVANIA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION ANALYSIS; MESSAGE PASSING; TRAFFIC CONTROL;

FUZZY AGGREGATION; VARIABLE MESSAGE SIGNS (VMS);

AUTOMOBILE DRIVERS;

EID: 37249071737     PISSN: 01976729     EISSN: None     Source Type: Journal    
DOI: 10.1002/atr.5670420103     Document Type: Article

References (18)

1. Dong, W. M. and F. S. Wong. 1987. Fuzzy Weighted Averages and Implementation of the Extension Principle. Fuzzy Sets and Systems, Vol. 27:183-199.
2. Juang, C. H., J. E. Clark, and P. Ghosh. 1993. Representatio, Processing, and Interpretation of Fuzzy Information in Civil Engineering, Transportation Research Record 1399, TRB, National Research Council, Washington, D.C.:20-26.
3. Juang, C. H., X. H. Huang, and S. D. Shiff. 1992. Determination of weight of criteria for decision making by the fuzzy eigenvector method. Civil Engineering System, Vol. 9:1-16.
4. Kraan, M, N. Van Der Zijpp, B. Tutert, T. Vonk, and D. Van Megen. 1999. Evaluating Networkwide Effects of Variable Message Signs in the Netherlands, Transportation Research Record 1689, TRB, National Research Council, Washington, D.C.:60-67
5. Lee, D. M., M.T. Pietrucha, and E.T. Donnell. 2006. Hierarchical Fuzzy Inference System to Evaluate Experts' Opinions of Median Safety, Transportation Research Record 1961, TRB, National Research Council, Washington, D.C.:34-43
6. Lee, D., M.T. Pietrucha, and S. K. Sinha. 2005. Use of Fuzzy Sets to Evaluate Driver Perception of Variable Message Signs. Transportation Research Record 1937, TRB, National Research Council, Washington, D.C.:96-104.
7. Lee, D. 2006. A Generalized Approach for Analyzing Transportation User Perception Using Fuzzy Sets. Ph.D. Dissertation, The Pennsylvania State University.
8. McCauley-Bell, P. and A. B. Badiru. 1996. Fuzzy Modeling and Analytic Hierarchy Processing to Qualify Risk Levels Associated with Occupational Injuries Part I, IEEE Transactions on Fuzzy Systems, Vol. 4, No. 2:124-131.
9. Patten, M. L., O. Pribyl, and K.G. Goulias. 2003. Evaluation of The Pennsylvania Turnpike's Advanced Traveler Information System (ATIS) Project Phase III. Pennsylvania Transportation Institute.
10. Ran, B., B Barrett, and E. Johnson. 2004. Evaluation of Variable Message Signs in Wisconsin: Driver Survey, Final Report, Wisconsin DOT.
11. nd Annual Meeting:564-568
12. Ribeiro, R. A. 1996. Fuzzy multiple attribute decision making: A review and new preference elicitation techniques. Fuzzy Sets and Systems, Vol. 75:155-181.
13. Saaty, T. L. 1977. The scaling method for priorities in hierarchical structures. Journal of Mathematical Psychology, Vol 15, No 3:234-281.
14. Seoul Development Institute. 2001. Evaluation of the ATIS in the Nam-Mountain Tunnel, Final Report.
15. Yen, J. and R. Langari. 1998. Fuzzy Logic: Intelligence, control, and information, Prentice Hall, New Jersey.
16. Yim, Y. and J. L. Ygnace. 1996. Link Flow Evaluation Using Loop Detector Data: Traveler Response to Variable-Message Signs. Transportation Research Record 1550, TRB, National Research Council, Washington, D.C.:58-64
17. Zadeh, L. A. 1965. Fuzzy Sets. Information and Control, Vol. 5:338-353
18. Zhang, Lin. 2004. Signalized Intersection Level-of-Service that Accounts for User Perceptions, Ph.D. Dissertation, University of Hawaii