Skip to main content
SpringerLink
Log in

Driving in TORCS Using Modular Fuzzy Controllers

  • Conference paper
  • First Online:
Applications of Evolutionary Computation (EvoApplications 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10199))

Included in the following conference series:

Abstract

When driving a car it is essential to take into account all possible factors; even more so when, like in the TORCS simulated race game, the objective is not only to avoid collisions, but also to win the race within a limited budget. In this paper, we present the design of an autonomous driver for racing car in a simulated race. Unlike previous controllers, that only used fuzzy logic approaches for either acceleration or steering, the proposed driver uses simultaneously two fuzzy controllers for steering and computing the target speed of the car at every moment of the race. They use the track border sensors as inputs and besides, for enhanced safety, it has also taken into account the relative position of the other competitors. The proposed fuzzy driver is evaluated in practise and timed races giving good results across a wide variety of racing tracks, mainly those that have many turning points.

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Abraham, A.: Neuro fuzzy systems: state-of-the-art modeling techniques. In: Mira, J., Prieto, A. (eds.) IWANN 2001. LNCS, vol. 2084, pp. 269–276. Springer, Heidelberg (2001). doi:10.1007/3-540-45720-8_30

    Chapter  Google Scholar 

  2. Agapitos, A., Togelius, J., Lucas, S.M.: Evolving controllers for simulated car racing using object oriented genetic programming. In: Lipson, H. (ed.) Genetic and Evolutionary Computation Conference, GECCO 2007, Proceedings, London, England, UK, 7–11 July 2007, pp. 1543–1550. ACM (2007)

    Google Scholar 

  3. Butz, M.V., Lönneker, T.D.: Optimized sensory-motor couplings plus strategy extensions for the TORCS car racing challenge. In: Lanzi, P.L. (ed.) Proceedings of the 2009 IEEE Symposium on Computational Intelligence and Games, CIG 2009, Milano, Italy, 7–10 September 2009, pp. 317–324. IEEE (2009)

    Google Scholar 

  4. Cardamone, L., Loiacono, D., Lanzi, P.L.: Learning drivers for TORCS through imitation using supervised methods. In: Lanzi, P.L. (ed.) Proceedings of the 2009 IEEE Symposium on Computational Intelligence and Games, CIG 2009, Milano, Italy, 7–10 September 2009, pp. 148–155. IEEE (2009)

    Google Scholar 

  5. Cardamone, L., Loiacono, D., Lanzi, P.L.: On-line neuroevolution applied to the open racing car simulator. In: Proceedings of the Eleventh Conference on Congress on Evolutionary Computation, CEC 2009, pp. 2622–2629. IEEE Press, Piscataway (2009)

    Google Scholar 

  6. Fujii, S., Nakashima, T., Ishibuchi, H.: A study on constructing fuzzy systems for high-level decision making in a car racing game. In: IEEE World Congress on Computational Intelligence. IEEE, June 2008

    Google Scholar 

  7. Guadarrama.S, Vazquez, R.: Tuning a fuzzy racing car by coevolution. In: Genetic and Evolving Systems, GEFS 2008. IEEE, March 2008

    Google Scholar 

  8. Iancu, I.: A Mamdani Type Fuzzy Logic Controller. InTech, Rijeka (2012). pp. 325–352

    Book  Google Scholar 

  9. Liébana, D.P., Recio, G., Sáez, Y., Isasi, P.: Evolving a fuzzy controller for a car racing competition. In: Lanzi, P.L. (ed.) Proceedings of the 2009 IEEE Symposium on Computational Intelligence and Games, CIG 2009, Milano, Italy, 7–10 September 2009, pp. 263–270. IEEE (2009)

    Google Scholar 

  10. Loiacono, D., Cardamone, L., Lanzi, P.: Software manual of the car racing competition. TORCS news (2009). http://cig.dei.polimi.it/wpcontent/uploads/2008/04/manual v03.pdf

  11. Loiacono, D., Cardamone, L., Lanzi, P.: Simulated car racing championship competition software manual. TORCS news (2013)

    Google Scholar 

  12. Loiacono, D., Lanzi, P.L., Togelius, J., Onieva, E., Pelta, D.A., Butz, M., Lonneker, T.D., Cardamone, L., Perez, D., Saez, Y., Preuss, M., Quadflieg, J.: The 2009 simulated car racing championship. IEEE Trans. Comput. Intell. AI Games 2(2), 131–147 (2010)

    Article  Google Scholar 

  13. Loiacono, D., Cardamone, L., Butz, M., Lanzi, P.L.: The 2011 simulated car racing championship @ cig-2011. TORCS news (2011). http://cig.dei.polimi.it/wpcontent/

  14. Muñoz, J., Gutiérrez, G., Sanchis, A.: A human-like TORCS controller for the simulated car racing championship. In: Yannakakis, G.N., Togelius, J. (eds.) Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, CIG 2010, Copenhagen, Denmark, 18–21 August 2010, pp. 473–480. IEEE (2010)

    Google Scholar 

  15. Onieva, E., Pelta, D., Godoy, J., Milanés, V., Rastelli, J.: An evolutionary tuned driving system for virtual car racing games: the autopia driver. Int. J. Intell. Syst. 27, 217–241 (2012)

    Article  Google Scholar 

  16. Onieva, E., Pelta, D.A., Alonso, J., Milanés, V., Pérez, J.: A modular parametric architecture for the TORCS racing engine. In: Proceedings of the 5th IEEE Symposium on Computational Intelligence and Games (CIG 2009), pp. 256–262. IEEE Press, Piscataway (2009)

    Google Scholar 

  17. Quadflieg, J., Preuss, M., Kramer, O., Rudolph, G.: Learning the track and planning ahead in a car racing controller. In: Proceedings of the 6th IEEE Symposium on Computational Intelligence and Games (CIG 2010), pp. 395–402. IEEE Press (2010)

    Google Scholar 

  18. SeongKim, T., Na, J.C., Kim, K.J.: Optimization of an autonomous car controller using a self-adaptive evolutionary strategy. Int. J. Adv. Robot. Syst. 9, 73 (2012)

    Article  Google Scholar 

  19. Sourceforge: Web torcs. Web, November 2016. http://torcs.sourceforge.net/

  20. Tan, C.H., Ang, J.H., Tan, K.C., Tay, A.: Online adaptive controller for simulated car racing. In: Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2008, 1–6 June 2008, Hong Kong, China, pp. 2239–2245. IEEE (2008)

    Google Scholar 

  21. Thang, H.D., Garibaldi, J.M.: A novel fuzzy inferencing methodology for simulated car racing. In: FUZZ-IEEE 2008, IEEE International Conference on Fuzzy Systems, Hong Kong, China, 1–6 June 2008, Proceedings, pp. 1907–1914. IEEE (2008)

    Google Scholar 

Download references

Acknowledgements

This work has been supported in part by projects EPHEMECH (TIN2014-56494-C4-3-P, Spanish Ministerio de Economy Competitividad), PROY-PP2015-06 (Plan Propio 2015 UGR), PETRA (SPIP2014-01437, funded by Dirección General de Tráfico), CEI2015-MP-V17 (awarded by CEI BioTIC Granada), and PRY142/14 (funded by Fundación Pública Andaluza Centro de Estudios Andaluces en la IX Convocatoria de Proyectos de Investigación).

Author information

Authors and Affiliations

  1. University of Mascara, Mascara, Algeria

    Mohammed Salem

  2. Department of Architecture and Computer Technology, University of Granada, Granada, Spain

    Antonio Miguel Mora & Juan Julian Merelo

  3. Universiy of Cádiz, Cádiz, Spain

    Pablo García-Sánchez

Authors
  1. Mohammed Salem
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonio Miguel Mora
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juan Julian Merelo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pablo García-Sánchez
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammed Salem .

Editor information

Editors and Affiliations

  1. Politecnico di Torino, Turin, Italy

    Giovanni Squillero

  2. Edinburgh Napier University, Edinburgh, United Kingdom

    Kevin Sim

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Salem, M., Mora, A.M., Merelo, J.J., García-Sánchez, P. (2017). Driving in TORCS Using Modular Fuzzy Controllers. In: Squillero, G., Sim, K. (eds) Applications of Evolutionary Computation. EvoApplications 2017. Lecture Notes in Computer Science(), vol 10199. Springer, Cham. https://doi.org/10.1007/978-3-319-55849-3_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-55849-3_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55848-6

  • Online ISBN: 978-3-319-55849-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation