Traffic Flow Prediction for Road Transportation Networks With Limited Traffic Data

IEEE Transactions on Intelligent Transportation Systems

Volumn 16, Issue 2, 2015, Pages 653-662

  Abadi, Afshin ^a   Rajabioun, Tooraj ^a   Ioannou, Petros A ^b  

^a Department of Electrical Engineering University of Southern California ^*  (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Historical time traffic flows; least squares method; optimization; traffic flow prediction

Indexed keywords

ALGORITHMS; FORECASTING; INFORMATION MANAGEMENT; INTELLIGENT SYSTEMS; LEAST SQUARES APPROXIMATIONS; MONTE CARLO METHODS; OPTIMIZATION; POLLUTION CONTROL; ROADS AND STREETS; SIMULATORS; STREET TRAFFIC CONTROL; TRAFFIC CONTROL; TRANSPORTATION; VEHICLE ACTUATED SIGNALS;

LEAST SQUARES METHODS; MACROSCOPIC TRAFFIC FLOWS; OPTIMIZATION METHODOLOGY; ROAD TRANSPORTATION NETWORKS; TRAFFIC FLOW; TRAFFIC FLOW FORECASTING; TRAFFIC FLOW INFORMATION; TRAFFIC FLOW PREDICTION;

TRAFFIC CONGESTION;

EID: 84927562466     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2014.2337238     Document Type: Article

References (49)

1. RAND, Moving Los Angeles: Short-Term Transportation Policy Options for Improving Transportation, RAND Corporation, 2008.
2. "Traffic choices study: Summary report," Seattle, WA, USA, 2008.
3. T. P. Mamuneas and M. I. Nadri, "Contribution of highway capital to industry and national productivity growth," Transportation Research Board, Washington, DC, USA, 1996.
4. J. W. C. van Lint, S. P. Hoogendoorn, and H. J. van Zuylen, "Accurate freeway travel time prediction with state-space neural networks under missing data," Transp. Res. Part C Emerg. Technol., vol. 13, no. 5/6, pp. 347-369, Oct.-Dec. 2005.
5. th Int. IEEE Conf. Intell. Transp. Syst., Oct. 2008, pp. 85-90.
6. K. Y. Chan, T. S. Dillon, J. Singh, and E. Chang, "Neural-network-based models for short-term traffic flow forecasting using a hybrid exponential smoothing and Levenberg-Marquardt algorithm," IEEE Trans. Intell. Transp. Syst., vol. 13, no. 2, pp. 644-654, Jun. 2012.
7. D. Park, L. R. Rilett, and G. Han, "Spectral basis neural networks for realtime travel time forecasting," J. Transp. Eng., vol. 125, no. 6, pp. 515-523, Nov. 1999.
8. th Int. IEEE Conf. ITSC, 2010, pp. 1541-1546.
9. I. Okutani, "The Kalman filtering approaches in some transportation and traffic problems," Transp. Res. Rec., vol. 2, no. 1, pp. 397-416, 1987.
10. 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.
11. I. Okutani and Y. J. Stephanedes, "Dynamic prediction of traffic volume through Kalman filtering theory," Transp. Res. Part B Methodol., vol. 18, no. 1, pp. 1-11, 1984.
12. th Int. Conf. Geoinformat., 2010, pp. 1-5.
13. Y. Wang and M. Papageorgiou, "Real-time freeway traffic state estimation based on extended Kalman filter: A general approach," Transp. Res. Part B Methodol., vol. 39, no. 2, pp. 141-167, Feb. 2005.
14. M. Van Der Voort, M. Dougherty, and S. Watson, "Combining Kohonen maps with ARIMA time series models to forecast traffic flow," Transp. Res. Part C Emerg. Technol., vol. 4, no. 5, pp. 307-318, Oct. 1996.
15. B. M. Williams, M. Asce, L. A. Hoel, and F. Asce, "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.
16. D. Billings and J. S. Yang, "Application of the ARIMA models to urban roadway travel time," in Proc. IEEE Int. Conf. Syst., Man, Cybern., 2006, pp. 2529-2534.
17. C. Chen, J. Hu, Q. Meng, and Y. Zhang, "Short-time traffic flow prediction with ARIMA-GARCH model," in Proc. IEEE Intell. Veh. Symp., 2011, pp. 607-612.
18. B. M. Williams, P. K. Durvasula, and D. E. Brown, "Urban freeway traffic flow prediction application of seasonal autoregressive integrated," Transp. Res. Rec., vol. 1644, pp. 132-141, 1998.
19. E. J. Schmitt and H. Jula, "On the limitations of linear models in predicting travel times," in Proc. IEEE Intell. Transp. Syst. Conf., Sep. 2007, pp. 830-835.
20. th Int. IEEE Conf. Intell. Transp. Syst., 2010, pp. 1209-1214.
21. B. L. Smith, B. M. Williams, and R. Keith Oswald, "Comparison of parametric and nonparametric models for traffic flow forecasting," Transp. Res. Part C Emerging Technol., vol. 10, no. 4, pp. 303-321, Aug. 2002.
22. Y. Kamarianakis and P. Prastacos, "Space-time modeling of traffic flow," Comput. Geosci., vol. 31, no. 2, pp. 119-133, Mar. 2005.
23. W. Min and L. Wynter, "Real-time road traffic prediction with spatio-temporal correlations," Transp. Res. Part C Emerging Technol., vol. 19, no. 4, pp. 606-616, Aug. 2011.
24. L. Q. L. Qu, J. H. J. Hu, L. L. L. Li, and Y. Z. Y. Zhang, "PPCA-based missing data imputation for traffic flow volume: A systematical approach," IEEE Trans. Intell. Transp. Syst., vol. 10, no. 3, pp. 512-522, Sep. 2009.
25. C. Chen, Y. Wang, L. Li, J. Hu, and Z. Zhang, "The retrieval of intra-day trend and its influence on traffic prediction," Transp. Res. Part C Emerging Technol., vol. 22, pp. 103-118, 2012.
26. B. Smith, W. Scherer, and J. Conklin, "Exploring imputation techniques for missing data in transportation management systems," Transp. Res. Rec., vol. 1836, pp. 132-142, 2003.
27. S. Sun, C. Zhang, G. Yu, N. Lu, and F. Xiao, "Bayesian network methods for traffic flow forecasting with incomplete data," in Proc. Mach. Learn., ECML, 2004, pp. 419-428.
28. L. Li, Y. Li, and Z. Li, "Efficient missing data imputing for traffic flow by considering temporal and spatial dependence," Transp. Res. Part C Emerging Technol., vol. 34, pp. 108-120, 2013.
29. J. Haworth and T. Cheng, "Non-parametric regression for space-time forecasting under missing data," Comput. Environ. Urban Syst., vol. 36, no. 6, pp. 538-550, Nov. 2012.
30. H. Tan et al., "A tensor-based method for missing traffic data completion," Transp. Res. Part C Emerging Technol., vol. 28, pp. 15-27, Mar. 2013.
31. A. Khosravi et al., "Prediction intervals to account for uncertainties in travel time prediction," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 2, pp. 537-547, Jun. 2011.
32. S. S. S. Sun and C. Z. C. Zhang, "The selective random subspace predictor for traffic flow forecasting," IEEE Trans. Intell. Transp. Syst., vol. 8, no. 2, pp. 367-373, Jun. 2007.
33. 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.
34. S. Sun, R. Huang, and Y. Gao, "Network-scale traffic modeling and forecasting with graphical lasso and neural networks," J. Transp. Eng., vol. 138, no. 11, pp. 1358-1367, Nov. 2012.
35. E. Cascetta, "Estimation of trip matrices from traffic counts and survey data: A generalized least squares estimator," Transp. Res., vol. 18B, no. 4/5, pp. 289-299, 1984.
36. E. Codina and J. Barceló, "Adjustment of O-D trip matrices from observed volumes: An algorithmic approach based on conjugate directions," Eur. J. Oper. Res., vol. 155, pp. 535-557, 2004.
37. Y. Nie, H. M. Zhang, and W. W. Recker, "Inferring origin-destination trip matrices with a decoupled GLS path flow estimator," Transp. Res. Part B Methodol., vol. 39, pp. 497-518, 2005.
38. M. J. Maher, X. Zhang, and D. Van Vliet, "A bi-level programming approach for trip matrix estimation and traffic control problems with stochastic user equilibrium link flows," Transp. Res. Part B Methodol., vol. 35, pp. 23-40, 2001.
39. X. Zhou, X. Qin, and H. S. Mahmassani, "Dynamic origin-destination demand estimation using multi-day link traffic counts for planning applications," Transp. Res. Forum, vol. 5, no. 2, pp. 30-38, 2003.
40. X. Z. X. Zhou and H. S. 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.
41. D. de Ortúzar and L. G. Willumsen, Modelling Transport. Hoboken, NJ, USA: Wiley, 2011.
42. D. P. Smith and B. G. Hutchinson, "Goodness of fit statistics for trip distribution models," Transp. Res. Part A, Gen., vol. 15, pp. 295-303, 1981.
43. J. Desrosiers and M. E. Lübbecke, "A primer in column generation," Column Gener., vol. 3, pp. 1-32, 2005.
44. M. R. Garey and D. S. Johnson, "Computers and intractability: A guide to the theory of NP-completeness (series of books in the mathematical sciences)," in Computers and Intractability. New York, NY, USA: Macmillan, 1979, p. 340.
45. B. Y. R. Shebata, "Selection of the order of an autoregressive model by Akaike's information criterion," Biometrika, pp. 117-126, 1976.
46. J. M. Mendel, Lessons in Estimation Theory for Signal Processing, Communications, Control. Englewood Cliffs, NJ, USA: Prentice-Hall, 1995.
47. H. Akaike, "Fitting autoregressive models for prediction," Inn. Inst. Statist. Math., vol. 21, no. 1, pp. 243-247, 1969.
48. California Partners for Advanced Transportation TecHnology. [Online]. Available: www.path.berkeley.edu
49. PTV Group. [Online]. Available: http://vision-traffic.ptvgroup.com/en-us/products/ptv-visum/