The Application of Adaptive Kalman Filter in Traffic Flow Forecasting

Abstract:

The urban traffic usually has the characteristics of time-variation and nonlinearity, real-time and accurate traffic flow forecasting has become an important component of the Intelligent Transportation System (ITS). The paper gives a brief introduction of the basic theory of Kalman filter, and establishes the traffic flow forecasting model on the basis of the adaptive Kalman filter, while the traditional Kalman filtering model has the shortcomings of lower forecasting accuracy and easily running into filtering divergence. The Sage&Husa adaptive filtering algorithm will appropriately estimate and correct the unknown or uncertain noise covariance, so as to improve the dynamic characteristics of the model. The simulation results demonstrate that the adaptive Kalman filtering forecasting model has stronger tracking capability and higher forecasting precision, which is applicable to the traffic flow forecasting.

• Periodical: Advanced Materials Research (Volume 680)
• Pages: 495-500
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.680.495
• Online since: April 2013
• Authors: Jun Wei Gao, Zi Wen Leng, Bin Zhang, Xin Liu, Guo Qiang Cai
• Keywords: Adaptive Filtering Algorithm, Kalman Filter (KF), Noise Covariance, Traffic Flow Forecasting

References

[1] G. F. Yin: Advanced Materials Research, Vol. 219-220 (2011), p.882.

[2] J. W. Gao, G. C. Cai, Q. C. Li, X. Liu, Z. W. Leng: ICIC Express Letters, Vol. 5 (2011) No. 10, p.671.

[3] J. Ma, X. D. Li, Y. Meng: Acta Electronic Sinca, Vol. 37 (2009) No. 5, p.1092.

[4] M. F. Feng, J. C. Lu: Computer Simulation, Vol. 27 (2010) No. 12, p.323.

[5] Y. Ye, Z. L. Lu: Computer Engineering and Design, Vol. 30 (2009) No. 18, p.4296.

[6] S. Lee, D. Fambro: Transportation Res Rec, Vol. 1678 (1999), p.179.

[7] P. J. Shang, X. W. Li, S. Kamae: Chaos, Solitons and Fractals, Vol. 25 (2005) No. 1, p.121.

[8] Z. S. Yang, Z. Zhu: China Journal of Highway and Transport, Vol. 12 (1999) No. 3, p.63.

[9] M. G. Li, J. L. Sun, P. Liu: Relay, Vol. 32 (2004) No. 4, p.9.

[10] Z. L. Deng, Y. Xu: Control Theory & Applications, Vol. 21 (2004) No. 4, p.501.

[11] P. C. Vythoulkas: Transportation and Traffic Theory, Vol. 12 (1993), p.485.

[12] C. M. Wu, Y. G. Wang, B. Liu: Aerospace Shanghai, Vol. 2 (2002), p.37.

[13] J. F. Liu, Y. Jiang, C. H. Liu: Systems Engineering and Electronics, Vol. 30 (2008) No. 10, p.1824.

[14] M. Xu, J. Y. Liu, X. Yuan: Journal of Chinese Inertial Technology, Vol. 7 (1999) No. 3, p.14.

[15] J. B. Ma, H. G. Yang: Power System Technology, Vol. 29 (2005) No. 1, p.75.

[16] A. M. Fraser: IEEE Transactions on Information Theory, Vol. 35 (1989) No. 2, p.245.