Skip to main content

Jam Avoidance with Autonomous Systems

  • Conference paper
  • First Online:
Traffic and Granular Flow '15

Abstract

Many car-following models have been developed for jam avoidance in highways. Two mechanisms are used to improve the stability: feedback control with autonomous models and increasing of the interaction within cooperative ones. In this paper, we compare the linear autonomous and collective optimal velocity (OV) models. We observe that the stability is significantly increased by adding predecessors in interaction with collective models. Yet, autonomous and collective approaches are close when the speed difference term is taken into account. In the linear OV models tested, the autonomous models including speed difference are sufficient to maximise the stability.

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 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
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

Similar content being viewed by others

References

  1. Bando, M., Hasebe, K., Nakayama, A., Shibata, A., Sugiyama, Y.: Dynamical model of traffic congestion and numerical simulation. Phys. Rev. E 51(2), 1035–1042 (1995)

    Article  Google Scholar 

  2. Davis, L.C.: Effect of adaptative cruise control systems on traffic flow. Phys. Rev. E 69, 066110 (2004)

    Google Scholar 

  3. Hasebe, K., Nakayama, A., Sugiyama, Y.: Dynamical model of a cooperative driving system for freeway traffic. Phys. Rev. E 68, 026102 (2003)

    Google Scholar 

  4. Hu, Y., Ma, T., Chen, J.: An extended multi-anticipative delay model of traffic flow. Commun. Nonlinear Sci. Numer. Simul. 19(9), 3128–3135 (2014)

    Article  MathSciNet  Google Scholar 

  5. Jiang, R., Wu, Q., Zhu, Z.: Full velocity difference model for a car-following theory. Phys. Rev. E 64, 017101 (2001)

    Google Scholar 

  6. Jin, Y., Hu, H.: Stabilization of traffic flow in optimal velocity model via delayed-feedback control. Commun. Nonlinear Sci. Numer. Simul. 18(4), 1027–1034 (2013)

    Article  MATH  MathSciNet  Google Scholar 

  7. Kesting, A., Treiber, M., Schönhof, M., Helbing, D.: Adaptive cruise control design for active congestion avoidance. Trans. Res. Part C Emerg. Technol. 16(6), 668–683 (2008)

    Article  Google Scholar 

  8. Kesting, A., Treiber, M., Schönhof, M., Kranke, F., Helbing, D.: Jam-avoiding adaptive cruise control (ACC) and its impact on traffic dynamics. In: Traffic and Granular Flow’05, pp. 633–643 (2007)

    Google Scholar 

  9. Konishi, K., Kokame, H., Hirata, H.: Coupled map car-following model and its delayed-feedback control. Phys. Rev. E 60, 4000–4007 (1999)

    Article  Google Scholar 

  10. Konishi, K., Kokame, H., Hirata, K.: Decentralized delayed-feedback control of an optimal velocity traffic model. Eur. Phys. J. B-Condens. Matter Complex Syst. 15(4), 715–722 (2000)

    Article  MATH  Google Scholar 

  11. Lenz, H., Wagner, C., Sollacher, R.: Multi-anticipative car-following model. Eur. Phys. J. B-Condens. Matter Complex Syst. 7(2), 331–335 (1999)

    Google Scholar 

  12. Monteil, J., Billot, R., Sau, J., El Faouzi, N.E.: Linear and weakly nonlinear stability analyses of cooperative car-following models. IEEE Trans. Intell. Trans. Syst. 15(5), 2001–2013 (2014)

    Article  Google Scholar 

  13. Nakayama, A., Sugiyama, Y., Hasebe, K.: Effect of looking at the car that follows in an optimal velocity model of traffic flow. Phys. Rev. E 65, 016112 (2001)

    Google Scholar 

  14. Treiber, M., Kesting, A.: Traffic Flow Dynamics. Springer, Berlin (2013)

    Book  MATH  Google Scholar 

  15. Wilson, R., Berg, P., Hooper, S., Lunt, G.: Many-neighbour interaction and non-locality in traffic models. Eur. Phys. J. B-Condens. Matter Complex Syst. 39(3), 397–408 (2004)

    Article  Google Scholar 

  16. Zhao, X., Gao, Z.: Controlling traffic jams by a feedback signal. Eur. Phys. J. B-Condens. Matter Complex Syst. 43(4), 565–572 (2005)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Antoine Tordeux .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Tordeux, A., Lassarre, S. (2016). Jam Avoidance with Autonomous Systems. In: Knoop, V., Daamen, W. (eds) Traffic and Granular Flow '15. Springer, Cham. https://doi.org/10.1007/978-3-319-33482-0_52

Download citation

Publish with us

Policies and ethics