Nonparametric regression and short-term freeway traffic forecasting

Journal of Transportation Engineering

Volumn 117, Issue 2, 1991, Pages 178-188

  Davis, Gary A ^a   Nihan, Nancy L ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

HIGHWAY ENGINEERING; HIGHWAY SYSTEMS; MOTOR TRANSPORTATION--TRAFFIC CONTROL; STATISTICAL METHODS--REGRESSION ANALYSIS;

K-NEAREST NEIGHBOR APPROACH; NONPARAMETRIC REGRESSION METHODS; SHORT TERM FREEWAY TRAFFIC FORECASTING; UNIVARIATE LINEAR TIME SERIES FORECASTS;

HIGHWAY TRAFFIC CONTROL;

EID: 0026128928     PISSN: 0733947X     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)0733-947X(1991)117:2(178)     Document Type: Article

References (18)

1. Ahmed, M. S., and Cook, A. R. (1982). “Application of time-series analysis techniques to freeway incident detection.” Transp. Res. Record, 841, 19-21.
2. Box, G., and Jenkins, G. (1976). Time series analysis: Forecasting and control. Hoden-Day, San Francisco, Calif.
3. Capelle, D. G., and Basu, S. (1982). “Freeway surveillance and control. " Transportation and traffic engineering handbook, W. Homburger, ed., Prentice-Hall, Englewood Cliffs, N.J.
4. Davis, G. A., Nihan, N. L., Hamed, M., and Jacobson, L. (1989). “Adaptive forecasting of freeway traffic congestion.” First ASCE Conference on Application of Advanced Tech. to Transp. Engrg. ASCE, San Diego, Calif.
5. Devijver, P. (1982). “Statistical pattern recognition.” Applications of pattern recognition, K. S. Fu, ed., CRC Press, Boca Raton, Fla., 15-36.
6. Eldor, M. (1977). “Demand predictors for computerized freeway control systems.” 7th Int. Symp. on Transp. and Traffic Theory, C. T. Susaki and T. Yonoko, eds., Inst, of Systems Sci. Res., Kyoto, Japan, 341-370.
7. Gartner, N. H. (1982). “Prescription for demand-responsive urban traffic control.” Transp. Res. Record, 881, 73-76.
8. Goodwin, G., and Sin, K. (1984). Adaptive filtering, prediction and control. Prentice- Hall, Englewood Cliffs, N.J.
9. IMSL reference manual. (1977). 9th Ed., IMSL, Houston, Tex.
10. Kreer, J. B. (1975). “Factors affecting the relative performance of traffic responsive and time-of-day signal control.” Transp. Res., 10 (2), 75-81.
11. Luk, J. (1984). “Two traffic responsive area traffic control methods: SCAT and SCOOT.” Traffic Engrg. and Control, 25 (Jan.), 14-22.
12. Okutani, I., and Stephanedes, Y. (1984). “Dynamic prediction of traffic volume through Kalman filtering theory.” Transp. Res., 18 (1), 1-11.
13. Payne, H. J. (1985). “Discontinuity in equilibrium freeway traffic control.” Transp. Res. Record, 971, 140-146.
14. Ryan, T., Joiner, B., and Ryan, B. (1982). Minitab reference manual Univ. of Washington, Seattle, Wash.
15. Stephanedes, Y., Michalopoulos, P., and Plum, R. (1981). “Improved estimation of traffic flow for real time control.” Transp. Res. Record, 795, 28-39.
16. Yakowitz, S. (1987). “Nearest-neighbor methods for time-series analysis.” J. Time Series Analysis, 8(2), 235-247.
17. Yakowitz, S., and Karlsson, M. (1987). “Nearest neighbor methods for time series, with application to rainfall/runoff prediction.” Stochastic hydrology, 1. MacNeill and G. Umphrey, eds., Reidell, Norwell, Mass., 149-160.
18. Yakowitz, S., Unny, T., and Wong, A. (1983). “Pattern recognition applications to river flow analysis.” Computers and statistics, J. Gentle, ed., North-Holland, Amsterdam, The Netherlands, 180-185.