Short-term traffic speed forecasting based on data recorded at irregular intervals

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Volumn , Issue , 2010, Pages 1541-1546

  Ye, Qing ^a   Wong, S C ^a   Szeto, W Y ^a  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

ARIMA MODELS; DATA COLLECTION TOOLS; DATA SOURCE; GPS DATA; HONG-KONG; LOOP DETECTOR; NEURAL NETWORK MODEL; REAL-TIME TRANSPORTATION; TIME INTERVAL; TIME SERIES FORECASTING; TRAFFIC FORECASTING; TRAFFIC SPEED;

FORECASTING; INTELLIGENT SYSTEMS; NEURAL NETWORKS; SPEED; TIME SERIES;

REAL TIME SYSTEMS;

EID: 78650482496     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITSC.2010.5625184     Document Type: Conference Paper

References (17)

1. J. D. Croston, "FORECASTING AND STOCK CONTROL FOR INTERMITTENT DEMANDS," Operational Research Quarterly, vol. 23, pp. 289-&, 1972.
2. R. H. Jones, "MAXIMUM-LIKELIHOOD FITTING OF ARMA MODELS TO TIME-SERIES WITH MISSING OBSERVATIONS," Technometrics, vol. 22, pp. 389-395, 1980.
3. D. J. Wright, "FORECASTING DATA PUBLISHED AT IRREGULAR TIME INTERVALS USING AN EXTENSION OF HOLT METHOD," Management Science, vol. 32, pp. 499-510, Apr 1986.
4. T. Cipra, et al., "HOLT-WINTERS METHOD WITH MISSING OBSERVATIONS," Management Science, vol. 41, pp. 174-178, Jan 1995.
5. J. L. Carmo and A. J. Rodrigues, "Adaptive forecasting of irregular demand processes," Engineering Applications of Artificial Intelligence, vol. 17, pp. 137-143, Mar 2004.
6. T. R. Willemain, et al., "A new approach to forecasting intermittent demand for service parts inventories," International Journal of Forecasting, vol. 20, pp. 375-387, Jul-Sep 2004.
7. W. F. Velicer and S. M. Colby, "A comparison of missing-data procedures for ARIMA time-series analysis," Educational and Psychological Measurement, vol. 65, pp. 596-615, Aug 2005.
8. T. Cipra, "Exponential smoothing for irregular data," Applications of Mathematics, vol. 51, pp. 597-604, 2006.
9. N. Altay, et al., "Adapting Wright's modification of Holt's method to forecasting intermittent demand," International Journal of Production Economics, vol. 111, pp. 389-408, Feb 2008.
10. T. Cipra and T. Hanzak, "Exponential smoothing for irregular time series," Kybernetika, vol. 44, pp. 385-399, 2008.
11. B. L. Smith and M. J. Demetsky, "Traffic flow forecasting: Comparison of modeling approaches," Journal of Transportation Engineering-Asce, vol. 123, pp. 261-266, Jul-Aug 1997.
12. B. L. Smith, et al., "Comparison of parametric and nonparametric models for traffic flow forecasting," Transportation Research Part C-Emerging Technologies, vol. 10, pp. 303-321, Aug 2002.
13. B. M. Williams and L. A. Hoel, "Modeling and forecasting vehicular traffic flow as a seasonal ARIMA process: Theoretical basis and empirical results," Journal of Transportation Engineering-Asce, vol. 129, pp. 664-672, Nov-Dec 2003.
14. W. Y. Szeto, et al., "Multivariate Traffic Forecasting Technique Using Cell Transmission Model and SARIMA Model," Journal of Transportation Engineering-Asce, vol. 135, pp. 658-667, Sep 2009.
15. M. C. Tan, et al., "An Aggregation Approach to Short-Term Traffic Flow Prediction," Ieee Transactions on Intelligent Transportation Systems, vol. 10, pp. 60-69, Mar 2009.
16. G. E. P. Box, Time series analysis; forecasting and control [by] George E. P. Box and Gwilym M. Jenkins. San Francisco: Holden-Day, 1970.
17. H. B. Yin, et al., "Urban traffic flow prediction using a fuzzy-neural approach," Transportation Research Part C-Emerging Technologies, vol. 10, pp. 85-98, Apr 2002.