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Nonlinear Dynamics

, Volume 49, Issue 4, pp 475–492 | Cite as

Collision avoidance strategies and coordinated control of passenger vehicles

  • Antonella FerraraEmail author
  • Claudio Vecchio
Original Article

Abstract

Recent research has demonstrated the efficaciousness of the coordinated control of platoons of vehicles in order to homogenize the traffic flows and improve the exploitation of the capacity of road networks. Yet, taking into account the necessity of reducing, in the next years, the number of accidents involving pedestrians or other vulnerable road users (VRUs), like cyclists and motorcyclists, it seems useful to provide the control systems of the vehicles of the platoon with some collision detection and avoidance capability. This issue is investigated in this paper. The control system presented in this paper allows to maintain cruise conditions, and, as a novelty with respect to consolidated proposals, to avoid the collision with possible VRUs present on the road. The proposed control system is realized by means of vehicle supervisors, which, on the basis of the data acquired by the sensors, make the decision on which is the appropriate current control mode for each controlled vehicle, and manage the switches among low-level controllers. These are designed relying on a simple bicycle model, and according to a sliding mode control methodology. This choice is motivated by the robustness features of the sliding mode design, which appears particularly appropriate dealing with the automotive context.

Keywords

Automated guided vehicles Cruise control Collision avoidance Sliding mode control Vehicle dynamics Antonella Ferrara 

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References

  1. 1.
    Bartolini, G., Ferrara, A., Usai, E.: Chattering avoidance by second-order sliding mode control. IEEE Trans. Autom. Control 43(2), 241–246 (1998)zbMATHCrossRefGoogle Scholar
  2. 2.
    Brogliato, B., Canudas de Wit, C.: Stability issues for vehicle platooning in automated highway systems. In: Proceedings of the IEEE International Conference on Control Applications, pp. 1377–1382, Kohala Coast-Island of Hawaii, Hawaii, (1999)Google Scholar
  3. 3.
    Chakravarthy, A., Ghose, D.: Obstacle avoidance in a dynamic environment: a collision cone approach. IEEE Trans. Syst. Man Cybern. 28, 562–574 (1998)Google Scholar
  4. 4.
    Chien, C.C., Ioannou, P.: Automatic vehicle following. In: Proceedings of the American Control Conference, Chicago, IL, pp. 1748–1752 (1992)Google Scholar
  5. 5.
    Cicilloni, R.: European Project IST-1999-10107 PROTECTOR: final report. Deliverable n. D06.5 (2003)Google Scholar
  6. 6.
    De Nicolao, G., Ferrara, A., Giacomini, L.: On board sensor-based collision risk assessment to improve pedestrians safety. IEEE Trans. Vehicular Technol., in pressGoogle Scholar
  7. 7.
    Edwards, C., Spurgeon, K.S.: Sliding Mode Control: Theory and Applications. Taylor & Francis, London (1998)Google Scholar
  8. 8.
    Ferrara, A.: Scaled experimental study of an automatic collision avoidance system for passenger cars. In: Proceedings of the 16th IFAC World Congress, Praga, Czech Republic (2005)Google Scholar
  9. 9.
    Gavrila, D.M., Kunert, M., Lages, U.: A multi-sensor approach for the protection of vulnerable traffic partecipants—the PROTECTOR project. In: Proceedings of the IEEE Instrumentation and Measurement Technology Conference, Budapest, Hungary, vol. 3, pp. 2044–2048, (2001)Google Scholar
  10. 10.
    Genta, G.: Motor Vehicle Dynamics. Modeling and Simulation. World Scientific, World Scientific, Singapore (1997)Google Scholar
  11. 11.
    Hallouzi, R., Verdult, V., Hellendoorn, H., Morsink, P.L.J., Ploeg, J.: Communication based longitudinal vehicle control using an extended kalman filter. In: Proc. IFAC Symposium on Advances in Automotive Control, Salerno, Italy (2004)Google Scholar
  12. 12.
    Levine, W., Athans, M.: On the optimal error regulation of a string of moving vehicles. IEEE Trans. Autom. Control 11, 355–361 (1966)CrossRefGoogle Scholar
  13. 13.
    Liang, C.Y., Peng, H.: Optimal adaptive cruise control with guaranteed string stability. Vehicle Syst. Dynam. 31, 313–330 (1999)CrossRefGoogle Scholar
  14. 14.
    Peppard, L.E.: String stability of relative-motion PID vehicle control systems. IEEE Trans. Autom. Control 19, 579–581 (1974)CrossRefGoogle Scholar
  15. 15.
    Sheikholeslam, S., Desoer, C.A.: Longitudinal control of a platoon of vehicles. In: Proceedings of the 1990 American Control Conference, San Diego, CA, pp. 291–297 (1990)Google Scholar
  16. 16.
    Swaroop, D., Hedrick, J.K.: String stability of interconnected systems. IEEE Trans. Autom. Control 41, 349–357 (1996)zbMATHCrossRefGoogle Scholar
  17. 17.
    Swaroop, D.: String stability of interconnected systems: An application to platooning in automated highway systems. Ph.D. thesis, University of California at Berkeley (1994)Google Scholar
  18. 18.
    Swaroop, D., Hedrick, J.K., Choi, S.B.: Direct adaptive longitudinal control of vehicle platoons. IEEE Trans. Vehicular Technol. 50(1), 150–161 (2001)CrossRefGoogle Scholar
  19. 19.
    Utkin, V.I.: Sliding Modes in Control and Optimization. Springer, Berlin (1992)zbMATHGoogle Scholar
  20. 20.
    Yanakiev, D., Kanellakapoulos, I.: A simplified framework for string stability analysis in AHS. In: Proceeding of the 13th IFAC World Congress, San Francisco, CA, pp. 177–182, (1996)Google Scholar
  21. 21.
    Zambou, N., Enning, M., Abel, D.: Longitudinal control of following vehicle within platoon, a model-based predictive approach. In: Proc. IFAC Symposium on Advances in Automotive Control, Salerno, Italy pp. 733–738. (2004)Google Scholar
  22. 22.
    Zhang, Y., Kosmatopoulos, E.B., Ioannou, P.A., Chien, C.C.: Autonomous Intelligent Cruise Control using front an back information for tight vehicle following maneuvers. IEEE Trans. Vehicular Tech. 48, 319–328 (1999)CrossRefGoogle Scholar
  23. 23.
    Zhou, J., Peng, H.: String stability conditions of adaptive cruise control algorithms. JSME Int. J. Ser. C 43, 671–677 (2000)Google Scholar

Copyright information

© Springer Science + Business Media B.V. 2006

Authors and Affiliations

  1. 1.Department of Computer Engineering and Systems ScienceUniversity of PaviaPaviaItaly

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