Travel time prediction with support vector regression

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Volumn 2, Issue , 2003, Pages 1438-1442

  Wu, Chun Hsin ^a   Wei, Chia Chen ^a   Su, Da Chun ^a   Chang, Ming Hua ^a   Ho, Jan Ming ^a  

^a INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

Author keywords

Intelligent transportation systems; Support vector machines; Support vector regression; Time series analysis; Travel time prediction

Indexed keywords

FORECASTING; HARMONIC ANALYSIS; HIGHWAY TRAFFIC CONTROL; INTELLIGENT SYSTEMS; INTELLIGENT VEHICLE HIGHWAY SYSTEMS; MEAN SQUARE ERROR; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES; TIME SERIES ANALYSIS; TIME VARYING CONTROL SYSTEMS; TRANSPORTATION; TRAVEL TIME; VECTORS;

GENERALIZATION ABILITY; GLOBAL MINIMA; HIGHWAY TRAFFIC; INTELLIGENT TRANSPORTATION SYSTEMS; ROOT MEAN SQUARED ERRORS; SUPPORT VECTOR REGRESSION (SVR); TRAFFIC DATA ANALYSIS; TRAVEL TIME PREDICTION;

ADVANCED TRAVELER INFORMATION SYSTEMS;

EID: 33744972790     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ITSC.2003.1252721     Document Type: Conference Paper

References (21)

1. K.-R Nuller, A. J. Smofa, G. Ratsch, B. Scholkopf, J. kohlmorgen and V. Vapnils "Predicting lime series with support vector machine " in Proc ICANN 1997, Springer LNCS1327. pp. 999-1004.
2. S. R. Gunn, Support vector machine for classification and regression", Technical Report, U. of Shouthampton, May 1998.
3. H. Yang, L. Chan and I. King, "Support vector machine regression for volatile stock market prediction." in Proc. IDEAL 2002 Springer LNCS 24412 pp. 391-396.
4. B. J. Chen, M. W. Chang and C. J. Lin, "Load forecasting using support vector machines; a study on EUN1TE competition 2001" report for EUNITE Competition for Smart Adaptive System. Available: http://www.eunite.org.
5. D. Matterra and S. Haykin, "Support vector machines for dynamic reconstruction of a chaotic system, " in Advances in Kernel Methods, B. SchOlkopf, C.J.C B urges, and A J. Smola Eds., pp. 211-241, MIT Press, 1999.
6. A. Ding, X, Zhao and L Jiao "Traffic flow time series prediction based on statistics learning theory' in Proc, IEEE 5th International Conference on Intelligent Transportation Systems 2002 pp. 727-730.
7. D. C. Sansom, T. Downs and T K. Saha, Evaluation of support vector machine based forecasting tool in electricity price forecasting for Australian National Electricity Market Participants, in Proc, Australasian Universities Power Engineering Conference, 2002.
8. J.W.C van Lint, S.P, Hoogendoom and HJ. van Zuylen, ''Robust and adaptive travel time prediction with neural networks." proceedings of the 6th annual TRAIL Congress (part 2), December 2000.
9. E. Fraschini and K. Ashausen, "Day on day dependencies in travel time: first result using ARIMA modeling, " ETH, IVT. Institut filr Verkehrsplanung, Transporttechnik. Strasen- und Eisenbahnbau, February 2001.
10. X. Zhang, J. Rice and P. Bickel, "Empirical comparison of travel lime estimation methods, " Report for MOV 353, UCB-ITS-PRR-99-43 December 1999.
11. J. Rice and E. van Zwet, "A simple and effective method for predicting travel times on freeways" in Proc, IEEE 4th International Conference on Transportation Systems 2001 pp. 227 -232.
12. Sheng Lit "Nonlinear combination of travel-time prediction model based on wavelet network, " in Proc. IEEE 5th International Conference on Intelligent Transportation Systems 2002, pp. 741 -746.
13. D. Park, and L. R. Ritett, "Forecasting multiple-period freeway link travel times using modular neural networks " presented at the 77th Annual Meeting of the Transportation Research Board, Washington, D.C., January 1998.
14. H. Sun, R Liu and B. Ran, "Short term traffic forecasting using the local linear regression model, 'presented at the 82th Annual Meeting of the Transportation Research Board, 2003.
15. X. Zhang and J. A. Rice, "Short-term travel time prediction using A time-varying coefficient linear model", Technical Report, Dept, Statistics, U.C. Berkeley, March 2001.
16. R. Chrobok, O. Kallmann, J, Wahle and M. Schreckenbcrg, "Three categories of traffic data: historical, current, and predictive, " in Proc. 9th IFAC Syposium Control in Transportation Systems 2000 pp250-25.
17. V.N. Vapnik. The Nature of Statistical Learning Theory: Springer, New York, 1995.
18. K.R. Muller, A. Smola, G. Ratch, B. Scholkopf, J. Kohlmorgen and V.N. Vapnik, "Using support vector support machines for time series prediction, " Image Processing Services Research Lab, AT&T Labs.
19. C H. Wu, D.C. Su, J. Chang, C.C Wei, J.M. Ho, K.J. Lin and D, T. Lee, "An advanced traveler information system with emerging network technologies", in Proc. 6th Asia-Pacific Conference on Intelligent Transportation Systems, 2003.
20. CH Wu, D C. Sm J. Chang, C.C. Wei, K.J. Lin and J.M. Ho, "The design and implementation of intelligent transportation web services, " in Proc. IEEE Conference on E-commerce, 2003.
21. S. Ruping, "mySVM software, " Available:http://www-ai.cs.uni-dortmund.de/SOFTWARE/MYSVM.