Skip to main content

Adaptive Cruise Control for a Robotic Vehicle Using Fuzzy Logic

  • Conference paper
Mechatronics 2013
  • 2766 Accesses

Abstract

This paper presents the modelling, simulation, and implementation of an ACC system for a robotic vehicle using Fuzzy Logic control strategy. Implementation has been carried out using the graphical programming environment of LabVIEW and a robotic vehicle based on a real-time single board computer. The paper demonstrates control design process including the implementation of the fuzzy logic design rules, showing a good correlation between simulation behaviour and real-life implementation. The work is a part of a larger research informed teaching project for teaching engineering at Kingston University London.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Gerdes, J.C., Hedrick, J.K.: Vehicle speed and spacing control via coordinated throttle and brake actuation. Control Engineering Practice 5(11), 1607–1614 (1997)

    Article  Google Scholar 

  2. Holve, R., Protzel, P., Naab, K.: Generating fuzzy rules for the acceleration control of an adaptive cruise control system. In: 1996 Biennial Conference of the North American IEEE Fuzzy Information Processing Society, NAFIPS (1996)

    Google Scholar 

  3. Martinez, J., Canudas-de-Wit, C.: A Safe Longitudinal control for adaptive cruise control and stop-and-go scenarios. IEEE Transactions on Control Systems Technology 15(2), 246–258 (2007)

    Article  Google Scholar 

  4. National Instruments Fuzzy Logic Manual (2009), http://www.ni.com/pdf/manuals/372192d.pdf (retrieved May 12, 2013)

  5. Shakouri, P., Collier, G., Ordys, A.: Teaching control using NI starter kit robot. In: Proc. IEEE UKACC (2012)

    Google Scholar 

  6. Shakouri, P., Ordys, A., Laila, D.S., Askari, M.R.: Adaptive Cruise Control System: Comparing Gain-Scheduling PI and LQ Controllers. In: 18th IFAC Proc. Elsevier (2011)

    Google Scholar 

  7. Swain, N.K.: A survey of application of fuzzy logic in intelligent transportation systems (ITS) and rural ITS. In: Proc. IEEE SoutheastCon (2006)

    Google Scholar 

  8. Zimmerman, H.-J.: Fuzzy Set Theory and Its Application. Kluwer Academic Publishers, Dordrecht (2001)

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Hassan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Hassan, A., Collier, G. (2014). Adaptive Cruise Control for a Robotic Vehicle Using Fuzzy Logic. In: Březina, T., Jabloński, R. (eds) Mechatronics 2013. Springer, Cham. https://doi.org/10.1007/978-3-319-02294-9_68

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-02294-9_68

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02293-2

  • Online ISBN: 978-3-319-02294-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics