Short-term traffic flow forecasting: An experimental comparison of time-series analysis and supervised learning

IEEE Transactions on Intelligent Transportation Systems

Volumn 14, Issue 2, 2013, Pages 871-882

  Lippi, Marco ^a   Bertini, Matteo ^b   Frasconi, Paolo ^b  

^a UNIVERSITY OF SIENA   (Italy)

^b UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Intelligent transportation systems; support vector machines; traffic forecasting

Indexed keywords

EXPERIMENTAL COMPARISON; INTELLIGENT TRANSPORTATION SYSTEMS; PERFORMANCE MEASUREMENTS; PROBABILISTIC GRAPHICAL MODELS; SHORT-TERM TRAFFIC FLOW FORECASTING; SUPPORT VECTOR REGRESSION MODELS; SUPPORT VECTOR REGRESSOR; TRAFFIC FORECASTING;

ALGORITHMS; FORECASTING; INTELLIGENT SYSTEMS; SUPPORT VECTOR MACHINES;

TRAFFIC CONTROL;

EID: 84878696679     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2013.2247040     Document Type: Article

References (69)

1. L. A. Klein, M. K. Mills, and D. R. P. Gibson, Traffic Detector Handbook, 3rd ed. Washington, DC, USA: U. S. Dept. of Transportation, 2006.
2. J. Wohlers, A. Mertins, and N. Fliege, "Time-delay estimation for compound point-processes using hidden Markov models, " in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., 1996, vol. 5, pp. 2817-2820.
3. R. Li, G. Rose, and M. Sarvi, "Evaluation of speed-based travel time estimation models, " J. Transp. Eng., vol. 132, no. 7, pp. 540-547, Jul. 2006.
4. G. Box, G. M. Jenkins, and G. Reinsel, Time Series Analysis: Forecasting & Control, 3rd ed. Englewood Cliffs, NJ, USA: Prentice-Hall, Feb. 1994.
5. C. Moorthy and B. Ratcliffe, "Short term traffic forecasting using time series methods, " Transp. Plan. Technol., vol. 12, no. 1, pp. 45-56, Jul. 1988.
6. S. Lee and D. B. Fambro, "Application of subset autoregressive integrated moving average model for short-term freeway traffic volume forecasting, " J. Transp. Res. Board, vol. 1678, pp. 179-188, Jan. 1999. (Pubitemid 30552723)
7. B. M. Williams and L. A. Hoel, "Modeling and forecasting vehicular traffic flow as a seasonal arima process: Theoretical basis and empirical results, " J. Transp. Eng., vol. 129, no. 6, pp. 664-672, Nov. 2003. (Pubitemid 37470989)
8. M. Van Der Voort, M. Dougherty, and S. Watson, "Combining Kohonen maps with arima time series models to forecast traffic flow, " Transp. Res. C, Emerg. Technol., vol. 4, no. 12, pp. 307-318, Oct. 1996.
9. T. Kohonen, "The self-organizing map, " Neurocomputing, vol. 21, no. 1-3, pp. 1-6, Nov. 1998. (Pubitemid 28526808)
10. Y. Kamarianakis and P. Prastacos, "Forecasting traffic flow conditions in an urban network: Comparison of multivariate and univariate approaches, " Transp. Res. Rec., vol. 1857, no. 2, pp. 74-84, Jan. 2003.
11. Y. Kamarianakis and P. Prastacos, "Space-time modeling of traffic flow, " in Proc. ERSA, Aug. 2002, pp. 1-21.
12. R. Engle, "GARCH 101: The Use of ARCH/GARCH Models in applied econometrics, " J. Econ. Perspect., vol. 15, no. 4, pp. 157-168, Fall 2001. (Pubitemid 33594781)
13. Y. Kamarianakis, A. Kanas, and P. Prastacos, "Modeling traffic volatility dynamics in an urban network, " Transp. Res. Rec., vol. 1923, no. 1, pp. 18-27, Dec. 2005.
14. M. Jun and M. Ying, "Research of traffic flow forecasting based on neural network, " in Proc. Workshop Intell. Inf. Technol. Appl., 2008, vol. 2, pp. 104-108.
15. H. Su, L. Zhang, and S. Yu, "Short-term traffic flow prediction based on incremental support vector regression, " in Proc. Int. Conf. Natural Comput., 2007, vol. 1, pp. 640-645.
16. G. Zhang, B. E. Patuwo, and M. Y. Hu, "Forecasting with artificial neural networks: The state of the art, " Int. J. Forecast., vol. 14, no. 1, pp. 35-62, Mar. 1998. (Pubitemid 128340470)
17. M. S. Dougherty and M. R. Cobbett, "Short-term inter-urban traffic forecasts using neural networks, " Int. J. Forecast., vol. 13, no. 1, pp. 21-31, Mar. 1997. (Pubitemid 127165541)
18. C.-H. Wu, J.-M. Ho, and D.-T. Lee, "Travel-time prediction with support vector regression, " IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, pp. 276-281, Dec. 2004.
19. M. Castro-Neto, Y.-S. Jeong, M.-K. Jeong, and L. D. Han, "Online-SVR for short-term traffic flow prediction under typical and atypical traffic conditions, " Exp. Syst. Appl., vol. 36, pt. 2, no. 3, pp. 6164-6173, Apr. 2009.
20. S. Sun, C. Zhang, and G. Yu, "A Bayesian network approach to traffic flow forecasting, " IEEE Trans. Intell. Transp. Syst., vol. 7, no. 1, pp. 124-132, Mar. 2006.
21. Y. An, Q. Song, and X. Zhao, "Short-term traffic flow forecasting via echo state neural networks, " in Proc. 7th ICNC, Y. Ding, H. Wang, N. Xiong, K. Hao, and L. Wang, Eds., Shanghai, China, Jul. 26-28, 2011, pp. 844-847.
22. G. A. Davis and N. L. Nihan, "Nonparametric regression and short-term freeway traffic forecasting, " J. Transp. Eng., vol. 117, no. 2, pp. 178-188, Mar. /Apr. 1991.
23. H. Sun, H. X. Liu, H. Xiao, and B. Ran, "Short Term Traffic Forecasting Using the Local Linear Regression Model, " Univ. of California, Irvine, Irvine, CA, USA, UCI-ITS-WP-02-2, 2002.
24. P. Lingras and P. Mountford, "Time delay neural networks designed using genetic algorithms for short term inter-city traffic forecasting, " in Engineering of Intelligent Systems, L. Monostori, J. Váncza, and M. Ali, Eds. Berlin, Germany: Springer-Verlag, 2001, ser. Lecture Notes in Computer Science, pp. 290-299.
25. E. I. Vlahogianni, M. G. Karlaftis, and J. C. Golias, "Optimized and metaoptimized neural networks for short-term traffic flow prediction: A genetic approach, " Transp. Res. C, Emerg. Technol., vol. 13, no. 3, pp. 211-234, Jun. 2005. (Pubitemid 41179185)
26. J. Zhu and T. Zhang, "A layered neural network competitive algorithm for short-term traffic forecasting, " in Proc. CORD Conf., Dec. 2009, pp. 1-4.
27. M. Lippi, M. Bertini, and P. Frasconi, "Collective traffic forecasting, " in Proc. ECML/PKDD, 2010, pp. 259-273.
28. J. G. Yu, C. Zhang, L. Zhuang, and J. Song, "Short-term traffic flow forecasting based on Markov chain model, " in Proc. IEEE Intell. Veh. Symp., 2003, pp. 208-212.
29. I. Okutani and Y. J. Stephanedes, "Dynamic prediction of traffic volume through Kalman filtering theory, " Transp. Res. B, Methodol., vol. 18, no. 1, pp. 1-11, Feb. 1984. (Pubitemid 14528238)
30. Y. Xie, Y. Zhang, and Z. Ye, "Short-term traffic volume forecasting using Kalman filter with discrete wavelet decomposition, " Comput.-Aided Civil Infrastruct. Eng., vol. 22, no. 5, pp. 326-334, Jul. 2007. (Pubitemid 46796355)
31. K. Leong, Book review: Periodicity and Stochastic Trends in Economic Time Series. Oxford, U. K. : Oxford Univ. Press, 1998.
32. Y. Li, E. P. Campbell, D. Haswell, R. J. Sneeuwjagt, and W. N. Venables, "Statistical forecasting of soil dryness index in the southwest of Western Australia, " Forest Ecol. Manage., vol. 183, no. 1-3, pp. 147-157, Sep. 2003. (Pubitemid 37065259)
33. E. Cadenas and W. Rivera, "Wind speed forecasting in the south coast of Oaxaca, México, " Renew. Energy, vol. 32, no. 12, pp. 2116-2128, Oct. 2007. (Pubitemid 46394521)
34. F.-M. Tseng and G.-H. Tzeng, "A fuzzy seasonal arima model for forecasting, " Fuzzy Sets Syst., vol. 126, no. 3, pp. 367-376, Mar. 2002. (Pubitemid 34154806)
35. L. Xuemei, D. Lixing, D. Yuyuan, and L. Lanlan, "Hybrid support vector machine and arima model in building cooling prediction, " in Proc. Int. Symp. Comput. Commun. Control Autom., May 2010, vol. 1, pp. 533-536.
36. J. Whittaker, S. Garside, and K. Lindveld, "Tracking and predicting a network traffic process, " Int. J. Forecast., vol. 13, no. 1, pp. 51-61, Mar. 1997. (Pubitemid 127165544)
37. B. Ghosh, B. Basu, and M. O'Mahony, "Bayesian time-series model for short-term traffic flow forecasting, " J. Transp. Eng., vol. 133, no. 3, pp. 180-189, Mar. 2007.
38. E. Horvitz, J. Apacible, R. Sarin, and L. Liao, "Prediction, expectation, and surprise: Methods, designs, and study of a deployed traffic forecasting service, " CoRR, vol. abs/1207. 1352, Jul. 2012.
39. B. L. Smith and M. J. Demetsky, "Traffic flow forecasting: Comparison of modeling approaches, " J. Transp. Eng., vol. 123, no. 4, pp. 261-266, Jul. 1997.
40. S. Sun and Q. Chen, "Kernel regression with a Mahalanobis metric for short-term traffic flow forecasting, " in Intelligent Data Engineering and Automated Learning (IDEAL), C. Fyfe, D. Kim, S.-Y. Lee, and H. Yin, Eds. Berlin, Germany: Springer-Verlag, 2008, ser. Lecture Notes in Computer Science, pp. 9-16.
41. F. Wang, G. Tan, and Y. Fang, "Multiscale wavelet support vector regression for traffic flow prediction, " in Proc. 3rd Int. Conf. IITA, 2009, pp. 319-322.
42. J. Fan and Q. Yao, Nonlinear Time Series: Nonparametric and Parametric Methods. New York, NY, USA: Springer-Verlag, 2005, ser. Series in Statistics.
43. S. Clark, "Traffic prediction using multivariate nonparametric regression, " J. Transp. Eng., vol. 129, no. 2, pp. 161-168, 2003. (Pubitemid 36294824)
44. T. Zhang, L. Hu, Z. Liu, and Y. Zhang, "Nonparametric regression for the short-term traffic flow forecasting, " in Proc. Int. Conf. MACE, Jun. 2010, pp. 2850-2853.
45. H. Sun, H. X. Liu, H. Xiao, and B. Ran, "Use of local linear regression model for short-term traffic forecasting, " Transp. Res. Rec., J. Transp. Res. Board, vol. 1838, no. 1, pp. 143-150, Jan. 2003.
46. D. Nikovski, N. Nishiuma, Y. Goto, and H. Kumazawa, "Univariate shortterm prediction of road travel times, " in Proc. IEEE Intell. Transp. Syst. Conf., Vienna, Austria, 2005, pp. 1074-1079. (Pubitemid 44250350)
47. B. L. Smith, B. M. Williams, and R. K. Oswald, "Comparison of parametric and nonparametric models for traffic flow forecasting, " Transp. Res. C, Emerg. Technol., vol. 10, no. 4, pp. 303-321, Aug. 2002.
48. H. Drucker, C. J. C. Burges, L. Kaufman, A. J. Smola, and V. Vapnik, "Support vector regression machines, " in Advances in Neural Information Processing Systems 9, NIPS, M. Mozer, M. I. Jordan, and T. Petsche, Eds. Denver, CO, USA: MIT Press, Dec. 2-5, 1996, pp. 155-161.
49. S. Shekhar and B. M. Williams, "Adaptive seasonal time series models for forecasting short-term traffic flow, " Transp. Res. Rec., no. 2024, pp. 116-125, Jan. 2007. (Pubitemid 351345494)
50. C. Chatfield, The Analysis of Time Series: An Introduction, 6th ed. London, U. K. : Chapman & Hall, Jul. 2003.
51. H. Akaike, "A new look at the statistical model identification, " IEEE Trans. Autom. Control, vol. AC-19, no. 6, pp. 716-723, Dec. 1974.
52. H. Akaike, "On entropy maximization principle, " in Applications of Statistics. Amsterdam, The Netherlands: North Holland, 1977, pp. 27-41.
53. G. Schwarz, "Estimating the dimension of a model, " Ann. Stat., vol. 6, no. 2, pp. 461-464, Mar. 1978.
54. P. N. Pant and W. H. Starbuck, "Innocents in the forest: Forecasting and research methods, " J. Manage., vol. 16, no. 2, pp. 433-460, Jun. 1990.
55. L. J. Tashman, "Out-of-sample tests of forecasting accuracy: An analysis and review, " Int. J. Forecast., vol. 16, no. 4, pp. 437-450, Oct.-Dec. 2000.
56. S. Arlot and A. Celisse, "A survey of cross-validation procedures for model selection, " Stat. Surv., vol. 4, pp. 40-79, 2010.
57. L. Getoor and B. Taskar, Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning). Cambridge, MA, USA: MIT Press, 2007.
58. C. M. Queen and C. J. Albers, "Intervention and causality: Forecasting traffic flows using a dynamic Bayesian network, " J. Amer. Stat. Assoc., vol. 104, no. 486, pp. 669-681, Jun. 2009.
59. V. N. Vapnik, Statistical Learning Theory. Hoboken, NJ, USA: Wiley, 1998.
60. H. Shimodaira, T. Akae, M. Nakai, and S. Sagayama, "Jacobian adaptation of HMM with initial model selection for noisy speech recognition, " in Proc. ICSLP, Oct. 2000, pp. 1003-1006.
61. D. E. Rumelhart, G. E. Hinton, and R. J. Williams, "Learning representations by back-propagating errors, " in Neurocomputing: Foundations of Research, J. A. Anderson and E. Rosenfeld, Eds. Cambridge, MA, USA: MIT Press, 1988, pp. 696-699.
62. C. M. Bishop, Neural Networks for Pattern Recognition. New York, NY, USA: Oxford Univ. Press, Jan. 1996.
63. L. Bottou and Y. LeCun, "Large scale online learning, " in Advances in Neural Information Processing Systems 16, S. Thrun, L. Saul, and B. Schölkopf, Eds. Cambridge, MA, USA: MIT Press, 2004.
64. P. Varaiya, "Freeway performance measurement system: Final report, " Univ. of California Berkeley, Berkeley, CA, USA, Tech. Rep. UCB-ITSPWP-2001-1, 2001.
65. G. Gardner, A. C. Harvey, and G. D. A. Phillips, "Algorithm as 154: An algorithm for exact maximum likelihood estimation of autoregressivemoving average models by means of Kalman filtering, " J. Roy. Stat. Soc. C, Appl. Stat., vol. 29, no. 3, pp. 311-322, 1980.
66. R. H. Jones, "Maximum likelihood fitting of ARMA models to time series with missing observations, " Technometrics, vol. 22, no. 3, pp. 389-395, Aug. 1980.
67. "R: A language and environment for statistical computing, " Vienna Austria R Foundation for Statistical Computing, vol. 1, no. 10, p. 2673, Sep. 2009.
68. G. Melard, "Algorithm as 197: A fast algorithm for the exact likelihood of autoregressive-moving average models, " J. Roy. Stat. Soc. C, Appl. Stat., vol. 33, no. 1, pp. 104-114, 1984.
69. G. E. P. Box and G. M. Jenkins, "Time series analysis, " Forecasting and Control, 1970.