Stochastic demand dynamic traffic models using generalized beta-gaussian bayesian networks

IEEE Transactions on Intelligent Transportation Systems

Volumn 13, Issue 2, 2012, Pages 565-581

  Castillo, Enrique ^a   Nogal, María ^a   Menéndez, Joś María ^b   Sánchez Cambronero, Santos ^b   Jiménez, Pilar ^b  

^a UNIVERSITY OF CANTABRIA   (Spain)

^b UNIVERSITY OF CASTILLA LA MANCHA   (Spain)

Author keywords

Bayesian network; beta Gaussian; stochastic dynamic traffic model; traffic prediction

Indexed keywords

AS-LINKS; BETA-GAUSSIAN; CONFIDENCE INTERVAL; DISCRETE SETS; DYNAMIC TRAFFIC MODEL; LARGE NETWORKS; LINK DENSITY; LINK TRAVEL TIME; LINK-FLOW; LOCAL INFORMATION; MULTIVARIATE NORMAL; POINT ESTIMATE; REAL NETWORKS; REAL TIME; REAL TRAFFIC; SIMULATED DATA; STOCHASTIC DEMAND; STOCHASTIC DYNAMICS; TIME EVOLUTIONS; TRAFFIC PREDICTION; TRAFFIC VARIABLES; VERMONT;

BAYESIAN NETWORKS; FORECASTING; STOCHASTIC MODELS;

COMPUTER SIMULATION;

EID: 84861893734     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2011.2173933     Document Type: Article

References (34)

1. E. Cascetta and S. Nguyen, "A unified framework for estimating or updating origin/destination matrices from traffic counts," Transp. Res. Part B, Methodological, vol. 22, no. 6, pp. 437-455, Dec. 1988.
2. E. Castillo, J. M. Menéndez, and S. Sánchez-Cambronero, "Predicting traffic flow using Bayesian networks," Transp. Res. Part B, Methodological, vol. 42, no. 5, pp. 482-509, Jun. 2008. (Pubitemid 351494483)
3. E. Castillo, J. M. Menéndez, and S. Sánchez-Cambronero, "Traffic estimation and optimal counting location without path enumeration using Bayesian networks," Comput.-Aided Civil Infrastructure Eng., vol. 23, no. 3, pp. 189-207, Apr. 2008. (Pubitemid 351260324)
4. S. Sánchez-Cambronero, E. Castillo, J. M. Menéndez, and P. Jiménez, "Dealing with error recovery in traffic flow prediction using Bayesian networks based on license plate scanning data," J. Transp. Eng. (ASCE), vol. 137, no. 9, pp. 615-629, Sep. 2011.
5. S. L. Sun, C. S. Zhang, and G. Q. Yu, "A Bayesian network approach to traffic flow forecasting," IEEE Trans. Intell. Transp. Syst., vol. 7, no. 1, pp. 124-132, Mar. 2006.
6. C. Queen and C. Albers. (2009). Intervention and causality: Forecasting traffic flows using a dynamic Bayesian network. J. Amer. Statist. Assoc. [Online]. vol. 104, no. 486, pp. 669-681. Avaiable: http://oro.open.ac.uk/17545
7. S. Sun, C. Zhang, and Y. Zhang, "Traffic flow forecasting using a spatio-temporal Bayesian network predictor," in Proc. ICANN, vol. 3697, Lecture Notes in Computer Science (LNCS), 2005, pp. 273-278.
8. Y. J. Yu and M. G. Cho, "A short-term prediction model for forecasting traffic information using Bayesian network," in Proc. 3rd Int. Conf. Convergence Hybrid Inf. Technol., 2008, pp. 242-247.
9. X. Zhou and H. Mahmassani, "Dynamic origin-destination demand estimation using automatic vehicle identification data," IEEE Trans. Intell. Transp. Syst., vol. 7, no. 1, pp. 105-114, Mar. 2006.
10. D. Helbing, "Gas-kinetic derivation of Navier-Stokes-like traffic equations," Phys. Rev. E, Statist. Nonlinear, Soft Matter Phys., vol. 53, no. 3, pp. 2366-2381, Mar. 1996. (Pubitemid 126583902)
11. M. J. Lighthill and G. B. Whitham, "On kinematic waves-Part I: Flow movement in long rivers; Part II: A theory of traffic flow on long crowded roads," Proc. R. Soc. Lond. A, vol. 229, no. 1178, pp. 281-345, May 1955.
12. C. F. Daganzo, "The cell transmission model: A dynamic representation of highway traffic consistent with the hydrodynamic theory," Transp. Res. Part B, Methodological, vol. 28, no. 4, pp. 269-287, Aug. 1993.
13. W. Y. Szeto and H. Lo, "Properties of dynamic traffic assignment with physical queues," J. Eastern Asia Soc. Transp. Studies, vol. 6, pp. 2108-2123, 2005.
14. S. Lee and D. B. Fambro, "Application of subsets autoregressive integrated moving average model for short-term freeway traffic volume forecasting," Transp. Res. Rec., J. Transp. Res. Rec., vol. 1678, pp. 179-188, 1999. (Pubitemid 30552723)
15. B. M. William, "Modeling and forecasting vehicular traffic flow as a seasonal stochastic time series process," Ph.D. dissertation, Univ. Virginia, Charlottesville, VA, 1999.
16. M. C. Tan, S. C. Wong, J. M. Xu, Z. R. Guan, and P. Zhang, "An aggregation approach to short-term traffic flow prediction," IEEE Trans. Intell. Transp. Syst., vol. 10, no. 1, pp. 60-69, Mar. 2009.
17. J. Hall and P.Mars, "The limitations of artificial neural networks for traffic prediction," in Proc. 3rd IEEE Symp. Comput. Commun., Athens, Greece, 1998, pp. 8-12.
18. Y. Sheffi, Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. San Francisco, CA: Morgan Kaufmann, 1988.
19. E. Castillo, J. M. Gutiérrez, and A. S. Hadi, Expert Systems and Probabilistic Network Models. New York: Springer-Verlag, 1997.
20. E. Castillo, J. M. Gutiérrez, A. S. Hadi, and C. Solares, "Symbolic propagation and sensitivity analysis in Gaussian Bayesian networks with application to damage assessment," Artif. Intell. Eng., vol. 11, no. 2, pp. 173-181, Apr. 1997. (Pubitemid 127415968)
21. E. Castillo, J. M. Sarabia, C. Solares, and P. Gómez, "Uncertainty analyses in fault trees and Bayesian networks using FORM/SORM methods," Reliab. Eng. Syst. Saf., vol. 65, no. 1, pp. 29-40, 1999.
22. F. V. Jensen, Bayesian Networks and Decision Graphs. New York: Springer-Verlag, 2001.
23. D. Heckerman, "A tutorial on learning with Bayesian networks," Microsoft Res., Microsoft Corp., Redmond, WA, Tech. Rep. MSR-TR-95-06, 1996.
24. C. R. Kenley, "Influence diagram models with continuous variables," Ph.D. dissertation, Stanford Univ., Stanford, CA, 1986.
25. R. Shachter and C. Kenley, "Gaussian influence diagrams," Manage. Sci., vol. 35, no. 5, pp. 527-550, May 1989.
26. E. Castillo, J. M. Gutiérrez, and A. S. Hadi, "Sensitivity analysis in discrete Bayesian networks," IEEE Trans. Syst., Man Cybern., vol. 27, no. 4, pp. 412-423, Jul. 1997. (Pubitemid 127770711)
27. L. Xu and J. Pearl, "Structuring causal tree models with continuous variables," in Uncertainty in Artificial Intelligence 3, L. N. Kanal, T. S. Levitt, and J. F. Lemmer, Eds. Amsterdam, The Netherlands: Elsevier, 1989, pp. 209-219.
28. K. C. Chang and R. Fung, "Symbolic probabilistic inference with continuous variables," in Proc. 7th Conf. Uncertainty Artif. Intell., 1991, pp. 77-85.
29. T. W. Anderson, An Introduction to Multivariate Statistical Analysis. New York: Wiley, 1984.
30. W. Gilks, S. Richardson, and D. J. Spiegelhalter, Markov Chain Monte Carlo in Practice. London, U.K.: Chapman & Hall, 1996.
31. R. Mínguez, S. Sánchez-Cambronero, E. Castillo, and P. Jiménez, "Optimal traffic plate scanning location in road networks," Transp. Res. Part B, Methodological, vol. 44, no. 2, pp. 282-298, Feb. 2010.
32. E. Castillo, J. M. Menéndez, M. Nogal, S. Sánchez- Cambronero, and P. Jiménez, "FIFO rule consistent model for the continuous dynamic network loading problem," IEEE Trans. Intell. Transp. Syst., 2011, DOI: 10.1109/TITS.2011.2169668, to be published.
33. E. Castillo, I. Gallego, S. Sánchez-Cambronero, and A. Rivas, "Matrix tools for general observability analysis in traffic networks," IEEE Trans. Intell. Transp. Syst., vol. 11, no. 4, pp. 799-813, Dec. 2010.
34. E. Castillo, I. Gallego, J. M. Menéndez, and A. Rivas, "Optimal use of plate-scanning resources for route flow estimation in traffic networks," IEEE Trans. Intell. Transp. Syst., vol. 11, no. 2, pp. 380-391, Jun. 2010.