Skip to main content
Log in

Wiener Filter and Neural Network Filter for Measuring the Road Profile

  • Published:
Moscow University Mechanics Bulletin Aims and scope

Abstract

Wiener filter and neural network filter are considered in relation to the problem of measuring the road profile. Road profile is identified using the inertial data from a smartphone rigidly fixed inside a moving car. The effectiveness of the approaches is compared by experimentally driving a car through a series of speed bumps.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. The equations are written in deviations from stationary motion, so gravity is not included in them.

REFERENCES

  1. M. W. Sayers and S. M. Karamihas, The Little Book of Profiling (Transportation Research Inst., Univ. Michigan, Ann Arbor, MI, 1998).

    Google Scholar 

  2. H. Imine, Y. Delanne, and N. K. M’Sirdi, ‘‘Road profile input estimation in vehicle dynamics simulation,’’ Veh. Syst. Dyn. 44, 285–303 (2006). doi 10.1080/00423110500333840

    Article  Google Scholar 

  3. H. Yan, W. Zhang, and D. Wang, ‘‘Wheel force sensor-based techniques for wear detection and analysis of a special road,’’ Sensors 18, 2493 (2018). doi 10.3390/s18082493

    Article  ADS  Google Scholar 

  4. M. Doumiati, A. Victorino, A. Charara, and D. Lechner, ‘‘Estimation of road profile for vehicle dynamics motion: Experimental validation,’’ in Proc. 2011 American Control Conf., San Francisco, 2011, pp. 5237–5242. doi 10.1109/ACC.2011.5991595

  5. A. Gonzalez, E. J. O’Brien, Y.-Y. Li, and K. Cashell, ‘‘The use of vehicle acceleration measurements to estimate road,’’ roughness,’’ Veh. Syst. Dyn. 46, 483–499 (2008).

    Article  Google Scholar 

  6. J. M. Celaya-Padilla, C. E. Galván-Tejada, F. E. López-Monteagudo, O. Alonso-González, A. M. Báez, A. Martinez-Torteya, J. I. Galván-Tejada, J. G. Arceo-Olague, H. Luna-Garcia, and H. Gamboa-Rosales, ‘‘Speed bump detection using accelerometric features: A genetic algorithm approach,’’ Sensors 18, 443 (2018). doi 10.3390/s18020443

    Article  ADS  Google Scholar 

  7. R. N. Jazar, Vehicle Dynamics: Theory and Application (Springer, New York, 2014). doi 10.1007/978-1-4614-8544-5

    Book  Google Scholar 

  8. G. Alessandroni, A. Carini, E. Lattanzi, V. Freschi, and A. Bogliolo, ‘‘A study on the influence of speed on road roughness sensing: The smartroadsense case,’’ Sensors 17, 305 (2017). doi 10.3390/s17020305

    Article  ADS  Google Scholar 

  9. J. T.-H. Lo, ‘‘Neural filtering,’’ Scholarpedia 4, 7868 (2009). doi 10.4249/scholarpedia.7868

    Article  ADS  Google Scholar 

  10. Yu. F. Golubev, ‘‘Neural networks in mechatronics,’’ J. Math. Sci. 147, 6607–6622 (2007). doi 10.1007/s10958-007-0497-3

    Article  MathSciNet  MATH  Google Scholar 

  11. J. T.-H. Lo, Neural Network Approach to Optimal Filtering, Technical Report No. RL-TR-94-197 (Rome Laboratory, Air Force Material Command, 1994).

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Yu. V. Bolotin or P. A. Egorov.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bolotin, Y.V., Egorov, P.A. Wiener Filter and Neural Network Filter for Measuring the Road Profile. Moscow Univ. Mech. Bull. 76, 44–49 (2021). https://doi.org/10.3103/S0027133021020035

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.3103/S0027133021020035

Keywords:

Navigation