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A Motion Certification Concept to Evaluate Operational Safety and Optimizing Operating Parameters at Runtime

  • Sebastian Müller
  • Peter Liggesmeyer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9338)

Abstract

For technical systems, which perform highly automated or so-called autonomous actions, there exist a large demand to evaluate their operational safety in a uniform way at runtime based on the combination of environmental threats and the conditions of subordinated system modules. To guarantee a safe motion based on autonomous decisions we have introduced a universal and transparent certification process which not only takes functional aspects like environment detection and collision avoidance techniques into account but especially identifies the associated system condition itself as a key aspect for the determination of operational safety and for an automated optimization of operating parameters. Similar to a feedback loop possible constraints for environment perception of sensor components or the ability of actuator components to interact with their environment have to be taken into account to introduce a generalized safetyevaluation for the entire system. Therefore, a model is derived to evaluate the operational safety for the autonomous driving robot RAVON from TU Kaiserslautern based on an integrated behavior-based control (IB2C).

Keywords

Condition monitoring Safety Autonomous vehicles Conditional safety certificates Modularity Adaptive systems Mobile robots 

References

  1. 1.
    Adamy, J., Bechtel, P.: Sicherheit mobiler Roborter (Safety of mobile robots). at-Automatisierungstechnik/Methoden und Anwendungen der Steuerungs-, Regelungs-und Informationstechnik 51(10), 435–444 (2003)Google Scholar
  2. 2.
    Liggesmeyer, P., Trapp, M.: Safety: Herausforderungen und lösungsansätze. In: Industrie 4.0 in Produktion, Automatisierung und Logistik. Springer Fachmedien Wiesbaden (2014)Google Scholar
  3. 3.
    Kaiser, B., Liggesmeyer, P., Maeckel, O.: A new component concept for fault trees. In: Australian Computer Society, I. (ed.): Proceedings of the 8th Australian Workshop on Safety Critical Systems and Software, vol. 33, pp. 37–46. Australian Computer Society, Canberra, Australia (2003)Google Scholar
  4. 4.
    Domis, D., Trapp, M.: Integrating safety analyses and component-based design. In: Harrison, M.D., Sujan, M.-A. (eds.) SAFECOMP 2008. LNCS, vol. 5219, pp. 58–71. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  5. 5.
    Stamatis, D.H.: Failure mode and effect analysis: FMEA from theory to execution. ASQ Quality Press, Milwaukee (2003)Google Scholar
  6. 6.
    Shalev, D.M., Tiran, J.: Condition-based fault tree analysis (CBFTA): A new method for improved fault tree analysis (FTA). Reliab. Eng. Syst. Saf. 92, 1231–1241 (2007)CrossRefGoogle Scholar
  7. 7.
    Kleinlützum, K., Brockmann, W., Rosemann, N.: Modellierung von anomalien in einer modularen roboter-steuerung. In: Berns, K., Luksch, T. (eds.) Autonome Mobile Systeme 2007, pp. 89–95. Springer, Berlin (2007)CrossRefGoogle Scholar
  8. 8.
    Schneider, D., Trapp, M.: Conditional safety certification of open adaptive systems. ACM Trans. Auton. Adapt. Syst. 8(2), 1–20 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Lehrstuhl für Software Engineering: DependabilityTechnische Universität KaiserslauternKaiserslauternGermany

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