Accurate and interpretable bayesian MARS for traffic flow prediction

IEEE Transactions on Intelligent Transportation Systems

Volumn 15, Issue 6, 2014, Pages 2457-2469

  Xu, Yanyan ^a   Kong, Qing Jie ^b   Klette, Reinhard ^c   Liu, Yuncai ^a  

^a Department of Automation   (China)

^b INSTITUTE OF AUTOMATION   (China)

^c UNIVERSITY OF AUCKLAND   (New Zealand)

Author keywords

Bayesian inference; interpretable model; Markov chain Monte Carlo (MCMC); multivariate adaptive regression splines (MARS); spatiotemporal relationship analysis; traffic flow prediction

Indexed keywords

ALGORITHMS; BAYESIAN NETWORKS; CHAINS; COMPUTER SIMULATION; FORECASTING; HIGHWAY TRAFFIC CONTROL; INFERENCE ENGINES; MARKOV PROCESSES; MONTE CARLO METHODS; REGRESSION ANALYSIS; ROADS AND STREETS; TRANSPORTATION;

BAYESIAN INFERENCE; MARKOV CHAIN MONTE CARLO; REGRESSION SPLINES; SPATIO-TEMPORAL RELATIONSHIPS; TRAFFIC FLOW PREDICTION;

STREET TRAFFIC CONTROL;

EID: 84915753270     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2014.2315794     Document Type: Article

References (28)

1. F.-Y. Wang, "Parallel control and management for intelligent transportation systems: Concepts, architectures, and applications," IEEE Trans. Intell. Transp. Syst., vol. 11, no. 3, pp. 630-638, Sep. 2010.
2. Q.-J. Kong, Y. Xu, S. Lin, D.Wen, F. Zhu, and Y. Liu, "UTN-model-based traffic flow prediction for parallel-transportation management systems," IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, pp. 1541-1547, Sep. 2013.
3. Y. Xu, Q.-J. Kong, S. Lin, and Y. Liu, "Urban traffic flow prediction based on road networkmodel," in Proc. 9th IEEE Int. Conf. Netw., Sens. Control, Beijing, China, 2012, pp. 334-339.
4. E. I. Vlahogianni, J. C. Golias, and M. G. Karlaftis, "Short-term traffic forecasting: Overview of objectives and methods," Transp. Rev., vol. 24, no. 5, pp. 533-557, Sep. 2004.
5. 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.
6. B. M.Williams, P. K. Durvasula, and D. E. Brown, "Urban freeway travel prediction: Application of seasonal ARIMA and exponential smoothing models," Transp. Res. Rec., J. Transp. Res. Board, vol. 1644, pp. 132-141, 1998.
7. S. Shekhar and B. M. Williams, "Adaptive seasonal time series models for forecasting short-term traffic flow," Transp. Res. Rec., J. Transp. Res. Board, vol. 2024, pp. 116-125, 2007.
8. B. L. Smith, B.M.Williams, and R. K. Oswald, "Comparison of parametric and nonparametric models for traffic flow forecasting," Transp. Res. C, Emerging Technol., vol. 10, no. 4, pp. 303-321, Aug. 2002.
9. T. T. Tchrakian, B. Basu, and M. O'Mahony, "Real-time traffic flow forecasting using spectral analysis," IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp. 519-526, Jun. 2012.
10. A. Hobeika and C. K. Kim, "Traffic-flow-prediction systems based on upstream traffic," in Proc. Veh. Navig. Inf. Syst. Conf., Yokohama, Japan, 1994, pp. 345-350.
11. 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.
12. E. I. Vlahogianni, M. G. Karlaftis, and J. C. Golias, "Spatio-temporal short-term urban traffic volume forecasting using genetically optimized modular networks," Comput.-Aided Civil Infrastruct. Eng., vol. 22, no. 5, pp. 317-325, Jul. 2007.
13. W. Min and L. Wynter, "Real-time road traffic prediction with spatiotemporal correlations," Transp. Res. C, Emerging Technol., vol. 19, no. 4, pp. 606-616, Aug. 2011.
14. Y. Zhang and Y. Xie, "Forecasting of short-term freeway volume with V-support vector machines," Transp. Res. Rec., J. Transp. Res. Board, vol. 2024, pp. 92-99, 2007.
15. 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. Part 2, no. 3, pp. 6164-6173, Apr. 2009.
16. S. Sun and X. Xu, "Variational inference for infinite mixtures of Gaussian processes with applications to traffic flow prediction," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 2, pp. 466-475, Jun. 2011.
17. Y. Qi and S. Ishak, "Stochastic approach for short-term freeway traffic prediction during peak periods," IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, pp. 660-672, Jun. 2013.
18. S. R. Chandra and H. Al-Deek, "Predictions of freeway traffic speeds and volumes using vector autoregressive models," J. Intell. Transp. Syst., vol. 13, no. 2, pp. 53-72, May 2009.
19. M. Lippi, M. Bertini, and P. Frasconi, "Short-term traffic flow forecasting: An experimental comparison of time-series analysis and supervised learning," IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, pp. 871-882, Jun. 2013.
20. Y. Kamarianakis and P. Prastacos, "Space-time modeling of traffic flow," Comput. Geosci., vol. 31, no. 2, pp. 119-133, Mar. 2005.
21. J. H. Friedman, "Multivariate adaptive regression splines," Annu. Stat., vol. 19, no. 1, pp. 1-67, Mar. 1991.
22. S. Ye, Y. He, J. Hu, and Z. Zhang, "Short-term traffic flow forecasting based on Mars," in Proc. 5th Int. Conf. Fuzzy Syst. Knowl. Discov., Jinan, China, 2008, vol. 5, pp. 669-675.
23. D. G. T. Denison, B. K. Mallick, and A. F. M. Smith, "Bayesian MARS," Stat. Comput., vol. 8, no. 4, pp. 337-346, Dec. 1998.
24. C. C. Holmes and B. K. Mallick, "Bayesian regression with multivariate linear splines," J. R. Stat. Soc. B, Stat. Methodol., vol. 63, no. 1, pp. 3-17, 2001.
25. P. Green, "Reversible jump Markov chain Monte Carlo computation and Bayesian model determination," Biometrika, vol. 82, no. 4, pp. 711-732, Dec. 1995.
26. The portal FHWA traffic data set, Portland State University, Portland, OR, USA, Accessed Apr. 11, 2013. [Online]. Available: http://portal.its.pdx. edu/
27. 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.
28. V. N. Vapnik, The Nature of Statistical Learning Theory. New York, NY, USA: Springer-Verlag, 1995.