On-Street and off-street parking availability prediction using multivariate spatiotemporal models

IEEE Transactions on Intelligent Transportation Systems

Volumn 16, Issue 5, 2015, Pages 2913-2924

  Rajabioun, Tooraj ^a   Ioannou, Petros ^b  

^a University of Southern California   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Parking guidance systems; parking prediction; spatiotemporal models

Indexed keywords

INTELLIGENT SYSTEMS; PARKING;

AVAILABILITY PREDICTIONS; INTELLIGENT TRANSPORTATION SYSTEMS; MULTIVARIATE AUTOREGRESSIVE MODELS; PARKING FACILITIES; PARKING LOCATIONS; PREDICTION ERRORS; SPATIO-TEMPORAL MODELS; TEMPORAL AND SPATIAL CORRELATION;

FORECASTING;

EID: 84961181176     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2015.2428705     Document Type: Article

References (31)

1. W. Xiang, Y. Huang, and S. Majhi, "The design of a wireless access for vehicular environment (WAVE) prototype for intelligent transportation system (ITS) and vehicular infrastructure integration (VII)," in Proc. 68th IEEE VTCFall, 2008, pp. 1-2.
2. C. D. Nugent, X. Hong, J. Hallberg, D. Finlay, and K. Synnes, "Assessing the impact of individual sensor reliability within smart living environments," in Proc. IEEE Int. Conf. CASE, 2008, pp. 685-690.
3. D. C. Shoup et al., The High Cost of Free Parking, vol. 7. Washington, DC, USA: Planners Press, American Planning Association, 2005.
4. D. Teodorovic and P. Lucic, "Intelligent parking systems," Eur. J. Oper. Res., vol. 175, no. 3, pp. 1666-1681, Dec. 2006.
5. F. Caicedo, "The use of space availability information in PARC systems to reduce search times in parking facilities," Transp. Res. C, Emerging Technol., vol. 17, no. 1, pp. 56-68, Feb. 2009.
6. M. K. Y. Asakura, "Effects of parking information on system performance: A simulation model approach," in Proc. Veh. Navig. Inf. Syst. Conf., 1994, pp. 251-254.
7. M. Y. I. Idris, Y. Y. Leng, E. M. Tamil, N. M. Noor, and Z. Razak, "Car park system: A review of smart parking system and its technology," Information Technology Journal, 2009, [Accessed: 22 Feb. 2013]. [Online]. Available: http://scialert.net/fulltext/?doi=itj.2009.101.113&org=11
8. Y. Geng and C. G. Cassandras, "A new smart parking system based on optimal resource allocation and reservations," in Proc. 14th IEEE ITSC, 2011, pp. 979-984.
9. T. Rajabioun, B. Foster, and P. Ioannou , "Intelligent parking assist," in Proc. 21st MED Control Autom. Conf., 2013, pp. 1156-1161.
10. F. Caicedo, C. Blazquez, and P. Miranda, "Prediction of parking space availability in real time," Expert Syst. Appl., vol. 39, no. 8, pp. 7281-7290, Jun. 2012.
11. E. Wu, J. Sahoo, C. Liu, M. Jin, and S. Lin, "Agile urban parking recommendation service for intelligent vehicular guiding system," Intell. Transp. Syst. Mag. IEEE, vol. 6, no. 1, pp. 35-49, Spring 2014.
12. B. D. Park, L. R. Rilett, and G. Han, "Spectral basis neural networks for real-time travel time forecasting," J. Transp. Eng., vol. 125, no. 6, pp. 515-523, no. Nov./Dec. 1999.
13. L. D. Vanajakshi, "Estimation and prediction of travel time from loop detector data for intelligent transportation systems applications," Ph.D Dissertation, Texas A&M Univ., College Station, TX, USA, 2004.
14. 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.
15. H. Ji, A. Xu, X. Sui, and L. Li, "The applied research of Kalman in the dynamic travel time prediction," in Proc. 18th Int. Conf. Geoinf., 2010, pp. 1-5.
16. J. Rice and E. Van Zwet, "A simple and effective method for predicting travel times on freeways," IEEE Trans. Intell. Transp. Syst., vol. 5, no. 3, pp. 200-207, Sep. 2004.
17. J. Kwon, B. Coifman, and P. Bickel, "Day-to-day travel time trends and travel time prediction from loop detector," Transp. Res. Rec., J. Transp. Res. Board, vol. 1717, pp. 1-18, 2000.
18. 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.
19. M. Van Der Voort, M. Dougherty, and S. Watson, "Combining Kohonen maps with ARIMA time series models to forecast traffic flow," Transp. Res. C, Emerging Technol., vol. 4, no. 5, pp. 307-318, Oct. 1996.
20. 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.
21. B. L. Smith, B. M.Williams, and R. Keith 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.
22. [Online]. Available: http://sfpark.org/
23. [Online]. Available: http://www.streetline.com/
24. Z. Wu, N. E. Huang, S. R. Long, and C.-K. Peng, "On the trend, detrending, and variability of nonlinear and nonstationary time series," Proc. Nat. Acad. Sci. USA, vol. 104, no. 38, pp. 14889-94, Sep. 2007.
25. K. H. Chan, J. C. Hayya, and J. K. Ord, "A note on trend removal methods: The case of polynomial regression versus variate differencing," Econom. J. Econom. Soc., vol. 45, no. 3, pp. 737-744, Apr. 1977.
26. B. Y. R. Shebata, "Selection of the order of an autoregressive model by Akaikes information criterion," Biometrika, vol. 63, no. 1, pp. 117-126, Apr. 1976.
27. J. M. Mendel, Lessons in Estimation Theory for Signal Processing, Communications, and Control. Boca Raton, FL, USA: Prentice-Hall, 1995.
28. P. Billingsley, Convergence of Probability Measures, vol. 493. Hoboken, NJ, USA: Wiley, 2009.
29. A. S. Goldberger et al., Econometric Theory. Hoboken, NJ, USA: Wiley, 1964.
30. J. M. Cioffi and T. Kailath, "Fast, recursive-least-squares transversal filters for adaptive filtering," IEEE Trans. Acoust. Speech Signal Process., vol. ASSP-32, no. 2, pp. 304-337, Apr. 1984.
31. J. D. Hamilton, Time Series Analysis, vol. 2. Princeton, NJ, USA: Princeton Univ. Press, 1994.