Resource-Aware Design for Reliable Autonomous Applications with Multiple Periods

  • Rongjie Yan
  • Di Zhu
  • Fan Zhang
  • Yiqi Lv
  • Junjie Yang
  • Kai HuangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10951)


Reliability is the most important design issue for current autonomous vehicles. How to guarantee reliability and reduce hardware cost is key for the design of such complex control systems intertwined with scenario-related multi-period timing behaviors. The paper presents a reliability and resource-aware design framework for embedded implementation of such autonomous applications, where each scenario may have its own timing constraints. The constraints are formalized with the consideration of different redundancy based fault-tolerant techniques and software to hardware allocation choices, which capture the static and various causality relations of such systems. Both exact and heuristic-based methods have been implemented to derive the lower bound of hardware usage, in terms of processor, for the given reliability requirement. The case study on a realistic autonomous vehicle controller demonstrates the effectiveness and feasibility of the framework.



The authors would like to thank Jian Zhang and Feifei Ma for their assistance with the work and valuable comments on this paper.


  1. 1.
    Alur, R., Dill, D.L.: A theory of timed automata. Theor. Comput. Sci. 126(2), 183–235 (1994)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Axer, P., Sebastian, M., Ernst, R.: Reliability analysis for MPSoCs with mixed-critical, hard real-time constraints. In: CODES+ISSS, pp. 149–158. IEEE/ACM/IFIP (2011)Google Scholar
  3. 3.
    Baier, C., Katoen, J.-P., Larsen, K.G.: Principles of Model Checking. MIT Press, Cambridge (2008)zbMATHGoogle Scholar
  4. 4.
    Behrmann, G., David, A., Larsen, K.G.: A tutorial on Uppaal. In: Formal Methodsfor the Design of Real-Time Systems, pp. 33–35 (2004)Google Scholar
  5. 5.
    Burns, A., Davis, R.: Mixed criticality systems-a review. Department of Computer Science, University of York, Technical report (2013)Google Scholar
  6. 6.
    Chang, W., Chakraborty, S., et al.: Resource-aware automotive control systems design: a cyber-physical systems approach. Found. Trends® Electr. Des. Autom. 10(4), 249–369 (2016)Google Scholar
  7. 7.
    Dutertre, B.: Yices 2.2. In: Biere, A., Bloem, R. (eds.) CAV 2014. LNCS, vol. 8559, pp. 737–744. Springer, Cham (2014). Scholar
  8. 8.
    Glaß, M., Lukasiewycz, M., Streichert, T., Haubelt, C., Teich, J.: Reliability-aware system synthesis. In: DATE, pp. 1–6 (2007)Google Scholar
  9. 9.
    Huang, J., Barner, S., Raabe, A., Buckl, C., Knoll, A.: A framework for reliability-aware embedded system design on multiprocessor platforms. Microprocess. Microsyst. 38(6), 539–551 (2014)CrossRefGoogle Scholar
  10. 10.
    Jiang, J., Yu, X.: Fault-tolerant control systems: a comparative study between active and passive approaches. Ann. Rev. Control 36(1), 60–72 (2012)CrossRefGoogle Scholar
  11. 11.
    Pagetti, C., Forget, J., Boniol, F., Cordovilla, M., Lesens, D.: Multi-task implementation of multi-periodic synchronous programs. Discrete Event Dyn. Syst. 21(3), 307–338 (2011)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Pandey, S., Vermeulen, B.: Transient errors resiliency analysis technique for automotive safety critical applications. In: DATE, p. 9 (2014)Google Scholar
  13. 13.
    Sangiovanni-Vincentelli, A., Di Natale, M.: Embedded system design for automotive applications. Computer 40(10), 42–51 (2007)CrossRefGoogle Scholar
  14. 14.
    Yip, E., Kuo, M.M., Roop, P.S., Broman, D.: Relaxing the synchronous approach for mixed-criticality systems. In: RTAS, pp. 89–100. IEEE (2014)Google Scholar
  15. 15.
    Zhao, Q., Gu, Z., Zeng, H.: Design optimization for AUTOSAR models with preemption thresholds and mixed-criticality scheduling. J. Syst. Architect. 72, 61–68 (2017)CrossRefGoogle Scholar
  16. 16.
    Zheng, B., Liang, H., Zhu, Q., Yu, H., Lin, C.-W.: Next generation automotive architecture modeling and exploration for autonomous driving. In: VLSI (ISVLSI), pp. 53–58. IEEE (2016)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Rongjie Yan
    • 1
  • Di Zhu
    • 3
    • 4
  • Fan Zhang
    • 1
    • 2
  • Yiqi Lv
    • 1
    • 2
  • Junjie Yang
    • 3
    • 4
  • Kai Huang
    • 3
    • 4
    Email author
  1. 1.State Key Laboratory of Computer ScienceISCASBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Key Laboratory of Machine Intelligence and Advanced ComputingSun Yat-sen University, Ministry of EducationGuangzhouChina
  4. 4.School of Data and Computer ScienceSun Yat-sen UniversityGuangzhouChina

Personalised recommendations