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Modular Verification of Vehicle Platooning with Respect to Decisions, Space and Time

  • Maryam Kamali
  • Sven LinkerEmail author
  • Michael Fisher
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 1008)

Abstract

The spread of autonomous systems into safety-critical areas has increased the demand for their formal verification, not only due to stronger certification requirements but also to public uncertainty over these new technologies. However, the complex nature of such systems, for example, the intricate combination of discrete and continuous aspects, ensures that whole system verification is often infeasible. This motivates the need for novel analysis approaches that modularise the problem, allowing us to restrict our analysis to one particular aspect of the system while abstracting away from others. For instance, while verifying the real-time properties of an autonomous system we might hide the details of the internal decision-making components. In this paper we describe verification of a range of properties across distinct dimensions on a practical hybrid agent architecture. This allows us to verify the autonomous decision-making, real-time aspects, and spatial aspects of an autonomous vehicle platooning system. This modular approach also illustrates how both algorithmic and deductive verification techniques can be applied for the analysis of different system subcomponents.

Keywords

Modular verification Hybrid agent architecture Spatial reasoning 

References

  1. 1.
    Aitken, J., et al.: Autonomous nuclear waste management. Intell. Syst. (2018).  https://doi.org/10.1109/MIS.2018.111144814
  2. 2.
    Amoozadeh, M., Deng, H., Chuah, C.N., Zhang, H.M., Ghosal, D.: Platoon management with cooperative adaptive cruise control enabled by vanet. Veh. Commun. 2(2), 110–123 (2015)Google Scholar
  3. 3.
    Balachandran, S., Muñoz, C., Consiglio, M., Feliú, M., Patel, A.: Independent configurable architecture for reliable operation of unmanned systems with distributed on-board services. In: Proceedings of the 37th Digital Avionics Systems Conference (DASC 2018) (2018)Google Scholar
  4. 4.
    Behrmann, G., et al.: UPPAAL 4.0. In: Proceedings of International Conference on Quantitative Evaluation of Systems, pp. 125–126 (2006)Google Scholar
  5. 5.
    Blackburn, P., van Benthem, J., Wolter, F. (eds.): Handbook of Modal Logic. Elsevier, New York (2006)Google Scholar
  6. 6.
    Burns, A.: How to verify a safe real-time system: the application of model checking and timed automata to the production cell case study. Real-Time Syst. 24(2), 135–151 (2003)CrossRefGoogle Scholar
  7. 7.
    Clarke, E.M., Grumberg, O., Long, D.E.: Model checking and abstraction. ACM Trans. Program. Lang. Syst. 16(5), 1512–1542 (1994)CrossRefGoogle Scholar
  8. 8.
    Cortier, V.: Verification of security protocols. In: Jones, N.D., Müller-Olm, M. (eds.) VMCAI 2009. LNCS, vol. 5403, pp. 5–13. Springer, Heidelberg (2008).  https://doi.org/10.1007/978-3-540-93900-9_5CrossRefGoogle Scholar
  9. 9.
    Dennis, L.A., Farwer, B.: Gwendolen: a BDI language for verifiable agents. In: Proceedings of AISB 2008 Symposium Logic and the Simulation of Interaction and Reasoning, pp. 16–23 (2008)Google Scholar
  10. 10.
    Dennis, L.A., Fisher, M., Webster, M.P., Bordini, R.H.: Model checking agent programming languages. Autom. Softw. Eng. 19(1), 5–63 (2012)CrossRefGoogle Scholar
  11. 11.
    Fulton, N., Mitsch, S., Quesel, J.-D., Völp, M., Platzer, A.: KeYmaera X: an axiomatic tactical theorem prover for hybrid systems. In: Felty, A.P., Middeldorp, A. (eds.) CADE 2015. LNCS (LNAI), vol. 9195, pp. 527–538. Springer, Cham (2015).  https://doi.org/10.1007/978-3-319-21401-6_36CrossRefGoogle Scholar
  12. 12.
    Gabbay, D., Kurucz, A., Wolter, F., Zakharyaschev, M.: Many-Dimensional Modal Logics: Theory and Applications. Elsevier, New York (2003)zbMATHGoogle Scholar
  13. 13.
    Hallé, S., Chaib-draa, B.: Collaborative driving system using teamwork for platoon formations. In: Applications of Agent Technology in Traffic and Transportation, pp. 133–151. Birkhäuser, Basel (2005)Google Scholar
  14. 14.
    Hilscher, M., Linker, S., Olderog, E.-R., Ravn, A.P.: An abstract model for proving safety of multi-lane traffic manoeuvres. In: Qin, S., Qiu, Z. (eds.) ICFEM 2011. LNCS, vol. 6991, pp. 404–419. Springer, Heidelberg (2011).  https://doi.org/10.1007/978-3-642-24559-6_28CrossRefGoogle Scholar
  15. 15.
    Hilscher, M., Schwammberger, M.: An abstract model for proving safety of autonomous urban traffic. In: Sampaio, A., Wang, F. (eds.) ICTAC 2016. LNCS, vol. 9965, pp. 274–292. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-46750-4_16CrossRefzbMATHGoogle Scholar
  16. 16.
    Hsu, A., Eskafi, F., Sachs, S., Varaija, P.: Protocol design for an automated highway system. Discret. Event Dyn. Syst. 2(1), 183–206 (1994)Google Scholar
  17. 17.
    Kamali, M., Dennis, L.A., McAree, O., Fisher, M., Veres, S.M.: Formal verification of autonomous vehicle platooning. Sci. Comput. Program. 148, 88–106 (2017)CrossRefGoogle Scholar
  18. 18.
    Konur, S., Fisher, M., Schewe, S.: Combined model checking for temporal, probabilistic, and real-time logics. Theor. Comput. Sci. 503, 61–88 (2013)MathSciNetCrossRefGoogle Scholar
  19. 19.
    Lam, S., Katupitiya, J.: Cooperative autonomous platoon maneuvers on highways. In: 2013 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 1152–1157 (2013)Google Scholar
  20. 20.
    Lincoln, N., Veres, S.M., Dennis, L.A., Fisher, M., Lisitsa, A.: An agent based framework for adaptive control and decision making of autonomous vehicles. In: Proceedings of IFAC Workshop on Adaptation and Learning in Control and Signal Processing (ALCOSP) (2010)Google Scholar
  21. 21.
    Linker, S.: Spatial reasoning about motorway traffic safety with Isabelle/HOL. In: Polikarpova, N., Schneider, S. (eds.) IFM 2017. LNCS, vol. 10510, pp. 34–49. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-66845-1_3CrossRefGoogle Scholar
  22. 22.
    Misra, J., Chandy, K.M.: Proofs of networks of processes. IEEE Trans. Softw. Eng. SE–7(4), 417–426 (1981)MathSciNetCrossRefGoogle Scholar
  23. 23.
    Müller, A., Mitsch, S., Retschitzegger, W., Schwinger, W., Platzer, A.: A component-based approach to hybrid systems safety verification. In: Ábrahám, E., Huisman, M. (eds.) IFM 2016. LNCS, vol. 9681, pp. 441–456. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-33693-0_28CrossRefGoogle Scholar
  24. 24.
    Platzer, A.: Logical Analysis of Hybrid Systems: Proving Theorems for Complex Dynamics. Springer, Heidelberg (2010).  https://doi.org/10.1007/978-3-642-14509-4CrossRefzbMATHGoogle Scholar
  25. 25.
    Rashid, A., Siddique, U., Hasan, O.: Formal verification of platoon control strategies. In: Johnsen, E.B., Schaefer, I. (eds.) SEFM 2018. LNCS, vol. 10886, pp. 223–238. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-92970-5_14CrossRefGoogle Scholar
  26. 26.
    Rinast, J., Schupp, S.: Static detection of zeno runs in UPPAAL networks based on synchronization matrices and two data-variable heuristics. In: Jurdziński, M., Ničković, D. (eds.) FORMATS 2012. LNCS, vol. 7595, pp. 220–235. Springer, Heidelberg (2012).  https://doi.org/10.1007/978-3-642-33365-1_16CrossRefzbMATHGoogle Scholar
  27. 27.
    Solyom, S., Coelingh, E.: Performance Limitations in vehicle platoon control. IEEE Intell. Transp. Syst. Mag. 5(4), 112–120 (2013)CrossRefGoogle Scholar
  28. 28.
    Tripakis, S.: Verifying progress in timed systems. In: Katoen, J.-P. (ed.) ARTS 1999. LNCS, vol. 1601, pp. 299–314. Springer, Heidelberg (1999).  https://doi.org/10.1007/3-540-48778-6_18CrossRefGoogle Scholar
  29. 29.
    Wooldridge, M.J.: Reasoning about Rational Agents. MIT Press, Cambridge (2000)zbMATHGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.NominetLondonUK
  2. 2.University of LiverpoolLiverpoolUK

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