Development of multiregime speed-density relationships by cluster analysis

Transportation Research Record

Volumn , Issue 1934, 2005, Pages 64-71

  Sun, Lu ^a   Zhou, Jie ^b  

^a Catholic University of America   (United States)

^b NORTHERN ILLINOIS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; DATA REDUCTION; MATHEMATICAL MODELS; REGRESSION ANALYSIS;

CLUSTER ANALYSIS; DATA SEGMENTATION; MODELERS; SPEED - DENSITY DATA;

HIGHWAY TRAFFIC CONTROL;

EID: 33645764663     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/1934-07     Document Type: Article

References (31)

1. Shekhar, S., C. T. Lu, S. Chawla, and P. Zhang. Data Mining and Visualization of Twin Cities Traffic Data. Technical Report. Department of Computer Science, University of Minnesota, Minneapolis - St. Paul, 2000.
2. Sun, L. Characterizing Stochastic Fluctuation of Traffic Speed. Presented at 80th Annual Meeting of the Transportation Research Board, Washington, D.C., 2001.
3. Nagel, K., and M. Schreckenberg. A Cellular Automaton Model for Freeway Traffic. Journal of Physique I, Vol. 2, 1992, p. 2,221.
4. Zhang, H. M., and T. Kim. Car-Following Theory for Multiphase Vehicular Traffic Flow. Presented at 80th Annual Meeting of the Transportation Research Board, Washington, D.C., 2001.
5. Lipkin, R. Intricate Patterns from Cellular Automata. Science News, Vol. 146, 1994, p. 109.
6. Kerner, B. S., and H. Rehborn. Experimental Properties of Complexity in Traffic Flow. Physical Review E, Vol. 53, 1996, p. 4,275.
7. Kerner, B. S. Experimental Features of Self-Organization in Traffic Flow. Physical Review Letters, Vol. 81, 1998, p. 3,797.
8. Helbing, D. Traffic and Related Self-Driven Many-Particle Systems. Reviews of Modern Physics, Vol. 73, No. 4, 2001, pp. 1,067-1,141.
9. Lee, H. Y., H. W. Lee, and D. Kim. Phase Diagram of Congested Traffic Flow: An Empirical Study. Physical Review E, Vol. 62, 2000, p. 4,737.
10. Cassidy, M. J., and R. L. Bertini. Some Traffic Features at Freeway Bottlenecks. Transportation Research, Part B, Vol. 33, 1999, pp. 25-42.
11. Treiber, M., A. Hennecke, and D. Helbing. Derivation, Properties, and Simulation of a Gas-Kinetic-Based, Non-Local Traffic Model. Physical Review E, Vol. 59, 2000, p. 239.
12. Helbing, D., A. Hennecke, and M. Treiber. Phase Diagram of Traffic States in the Presence of Inhomogeneities. Physical Review Letters, Vol. 82, 1999, pp. 4,360-4,363.
13. Weiss, P. Stop-and-Go Science. Science News Online, Vol. 156, No. 1, 1999. http://www.sciencenews.org/pages/sn_arc99/7_3_99/bob1.htm. Accessed July 25, 2004.
14. Helbing, D., and M. Treiber. Jams, Waves, and Clusters. Science, Vol. 282, No. 11, 1998, pp. 2,001-2,003.
15. Budiansky, S. The Physics of Gridlock. The Atlantic Monthly, Vol. 286, No. 6, 2000, pp. 20-24.
16. Daganzo, C. F. A Behavioral Theory of Multi-Lane Traffic Flow. II. Merges and the Onset of Congestion. Research Report UCB-ITS-RR-99-6. Institute of Transportation Studies, University of California, Berkeley, 1999.
17. Highway Capacity Manual. TRB, National Research Council, Washington, D.C., 2000.
18. Edie, L. C. Car Following and Steady-State Theory for Non-Congested Traffic. Operations Research, Vol. 9, 1961, pp. 66-76.
19. Drake, J. S., J. L. Schofer, and A. D. May. A Statistical Analysis of Speed Density Hypotheses. Proc., Third International Symposium on the Theory of Traffic Flow. Elsevier North-Holland, Inc., New York, 1967.
20. Quandt, R. E. The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes. Journal of the American Statistical Association, Vol. 53, 1958, pp. 873-880.
21. Quandt, R. E. Tests of Hypothesis That a Linear Regression System Obeys Two Separate Regimes. Journal of the American Statistical Association, Vol. 53, 1960, pp. 324-330.
22. May, A. D. Traffic Flow Fundamentals. Prentice Hall, Englewood Cliffs, N.J., 1990.
23. Kockelman, K. M. Modeling Traffic's Row - Density Relation: Accommodation of Multiple Flow Regimes and Traveler Types. Transportation, Vol. 28, No. 4, 2001, pp. 363-374.
24. Maddala, G.S. Limited-Dependent and Qualitative Variables in Econometrics. Econometric Society Monographs in Quantitative Economics. Cambridge University Press, Cambridge, United Kingdom, 1983.
25. Bhat, C. Endogenous Segmentation Mode Choice Model with an Application to Intercity Travel. Transportation Science, Vol. 31, No. 1, 1997, pp. 34-48.
26. Bezdek. J. C. Pattern Recognition with Fuzzy Objective Function. Plenum Press, New York, 1981.
27. Pedrycz, W. Fuzzy Clustering with Partial Supervision. IEEE Transaction on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 27, No. 5, 1997, pp. 2-20.
28. Duda, R. O., P. E. Hart, and D. O. Stork. Pattern Classification, 2nd ed. John Wiley and Sons, Inc., New York, 2001.
29. Bow, S. T. Pattern Recognition: Applications to Large Data Set Problems. Marcel Dekker, Inc., New York, 1984.
30. Khisty, C. J., and B. K. Lall. Transportation Engineering: An Introduction. Prentice Hall, Upper Saddle River, New Jersey, 2003.
31. Wardrop, J. G. Some Theoretical Aspects of Road Traffic Research. Proceedings of the Institute of Civil Engineers, Part II, Vol. 1, 1952, pp. 325-378.