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Application of dynamic sensor activation on operating automated headlights

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Abstract

The controller in an automated vehicle relies on sensors to collect the information needed for handling traffic situations, and reducing the frequency of using sensors could prolong their lifespans. We present in this paper the application of dynamic sensor activation algorithms in discrete event systems to activate/deactivate sensors for collecting information when it is only necessary to automatically operate headlights based on traffic rules. The framework developed in this paper forms a basis for automatically activating/deactivating sensors for other components in an automated vehicle in the future.

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References

  1. P. J. Ramadge, W. M. Wonham. Supervisory control of a class of discrete event processes. SIAM Journal on Control and Optimization, 1987, 25(1): 206–230.

    Article  MathSciNet  Google Scholar 

  2. F. Lin, W. M. Wonham. On observability of discrete-event systems. Information Sciences, 1988, 44(3): 173–198.

    Article  MathSciNet  Google Scholar 

  3. R. Cieslak, C. Desclaux, A. S. Fawaz, et al. Supervisory control of discrete-event processes with partial observations. IEEE Transactions on Automatic Control, 1988, 33(3): 249–260.

    Article  Google Scholar 

  4. W. Wang, S. Lafortune, F. Lin, et al. Minimization of sensor activation in discrete event systems for the purpose of control. IEEE Transactions on Automatic Control, 2010, 55(11): 2447–2461.

    Article  MathSciNet  Google Scholar 

  5. W. Wang, S. Lafortune, A. R. Girard, et al. Optimal sensor activation for diagnosing discrete event systems. Automatica, 2010, 46(7): 1165–1175.

    Article  MathSciNet  Google Scholar 

  6. J. H. van Schuppen. Decentralized control with communication between controllers. Unsolved Problems in Mathematical Systems and Control Theory. V. D. Blondel, A. Megretski, eds. Princeton: Princeton University Press, 2004: 144–150.

    Google Scholar 

  7. W. Wang, S. Lafortune, F. Lin. Minimization of communication of event occurrences in acyclic discrete event systems. IEEE Transactions on Automatic Control, 2008, 53(9): 2197–2202.

    Article  MathSciNet  Google Scholar 

  8. W. Wang, S. Lafortune, F. Lin. On the minimization of communication in networked systems with a central station. Discrete Event Dynamic Systems: Theory and Applications, 2008, 18(4): 415–443.

    Article  MathSciNet  Google Scholar 

  9. W. Wang, S. Lafortune, F. Lin. An algorithm for calculating indistinguishable states and clusters in finite-state automata with partially observable transitions. Systems & Control Letters, 2007, 56(9): 656–661.

    Article  MathSciNet  Google Scholar 

  10. W. Wang, A. R. Girard, S. Lafortune, et al. On codiagnosability and coobservability with dynamic observations. IEEE Transactions on Automatic Control, 2011, 56(7): 1551–1566.

    Article  MathSciNet  Google Scholar 

  11. X. Yin, S. Lafortune. Verification complexity of a class of observational properties for modular discrete events systems. Automatica, 2017, 83: 199–205.

    Article  MathSciNet  Google Scholar 

  12. X. Yin, S. Lafortune. Synthesis of maximally permissive supervisors for partially-observed discrete-event systems. IEEE Transactions on Automatic Control, 2015, 61(5): 1239–1254.

    Article  MathSciNet  Google Scholar 

  13. X. Yin, S. Lafortune. A uniform approach for synthesizing property-enforcing supervisors for partially-observed discrete-event systems. IEEE Transactions on Automatic Control, 2015, 61(8): 2140–2154.

    Article  MathSciNet  Google Scholar 

  14. D. Thorsley, D. Teneketzis. Active acquisition of information for diagnosis and supervisory control of discrete event systems. Discrete Event Dynamic Systems: Theory and Applications, 2007, 17(4): 531–586.

    Article  MathSciNet  Google Scholar 

  15. F. Cassez, S. Tripakis. Fault diagnosis with static and dynamic observers. Fundamenta Informaticae, 2008, 88(4): 497–540.

    MathSciNet  MATH  Google Scholar 

  16. M. Sampath, R. Sengupta, S. Lafortune, et al. Diagnosability of discrete event systems. IEEE Transactions on Automatic Control, 1995, 40(9): 1555–1575.

    Article  MathSciNet  Google Scholar 

  17. W. Wang, C. Gong. Calculating all minimal transition-based sensor activation policies for the purpose of supervisory control. IEEE Transactions on Automatic Control, 2016, 62(11): 5894–5901.

    Article  MathSciNet  Google Scholar 

  18. W. Wang. Online minimization of sensor activation for supervisory control. Automatica, 2016, 73(3): 8–14.

    Article  MathSciNet  Google Scholar 

  19. W. Wang, C. Gong, D. Wang. Optimizing sensor activation in a language domain for fault diagnosis. IEEE Transactions on Automatic Control, 2018, 64(2): 743–750.

    Article  MathSciNet  Google Scholar 

  20. X. Yin, S. Lafortune. Minimization of sensor activation in decentralized discrete-event systems. IEEE Transactions on Automatic Control, 2017, 63(11): 3705–3718.

    Article  MathSciNet  Google Scholar 

  21. R. J. M. Theunissen, M. Petreczky, R. R. H. Schiffelers, et al. Application of supervisory control synthesis to a patient support table of a magnetic resonance imaging scanner. IEEE Transactions on Automation Science and Engineering, 2014, 11(1): 20–32.

    Article  Google Scholar 

  22. S. T. J. Forschelen, J. M. V. De Mortelfronczak, R. Su, et al. Application of supervisory control theory to theme park vehicles. Discrete Event Dynamic Systems, 2012, 22(4): 511–540.

    Article  MathSciNet  Google Scholar 

  23. R. Su, A. R. Shehabinia, O. P. Gan, et al. Modeling and supervisory control of dynamic material handling systems. Proceedings of the 32nd Chinese Control Conference, Xi’an: IEEE, 2013: 8336–8341.

    Google Scholar 

  24. C. G. Cassandras, S. Lafortune. Introduction to Discrete Event Systems. 2nd ed. Boston: Springer, 2007.

    MATH  Google Scholar 

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Correspondence to Chaohui Gong.

Additional information

This work was supported in part by the PowerChina Grant (No. KY2018-JT-20-01-2019), the National Natural Science Foundation of China (No. CNSF-61374058) and the Australian Research Council (No. DP-130100156).

Han DING received his B.Sc. degree in Engineering from Ningbo University of Science and Technology in 2015. He is currently studying for a M.Sc. degree in Control Science and Engineering, at the School of Optical-Electrical and Computer Engineering, the University of Shanghai for Science and Technology. His research interests include intelligent transportation systems and discrete event systems.

Yishan QIAN obtained her B.Sc. degree in Communication Engineering, from Nanjing University of Posts and Telecommunications in 2018. Currently she is studying for a M.Sc. degree in Control Science and Engineering, at the School of Optical-Electrical and Computer Engineering, the University of Shanghai for Science and Technology. Her research interests include intelligent transportation systems and discrete event systems.

Chaohui GONG received her M.Sc. degree in Mathematical Statistics from Wayne State University in 2007. She is with Zhejiang Research Center on Smart Rail Transportation. Her research interests include discrete event systems, optimization algorithms, and intelligent transportation systems.

Yunfeng HOU received his B.E. degree in Electrical Engineering from Shandong University of Technology in 2012 and his M.Sc. degree in Control Science and Engineering from the University of Shanghai for Science and Technology in 2015. His is currently with the University of Shanghai for Science and Technology. His research interests are in modeling, control and optimization in discrete-event systems and intelligent Transportation systems.

Weilin WANG received the M.Sc. degree in Electrical Engineering Systems, the M.S.E. degree in Industrial Engineering, and the Ph.D. degree in Electrical Engineering Systems from the University of Michigan, Ann Arbor, in 2003, 2006, and 2007, respectively. He is currently with Zhejiang Research Center on Smart Rail Transportation, PowerChina Huadong Engineering Corporation Limited. He is a senior member of Institute of Electrical and Electronics Engineers. His research interests include model checking, synthesis of sensor activation and communication strategies for control and diagnosis of discrete event systems, traffic signal coordination, and cooperative control for multi-robot systems.

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Ding, H., Qian, Y., Gong, C. et al. Application of dynamic sensor activation on operating automated headlights. Control Theory Technol. 18, 246–256 (2020). https://doi.org/10.1007/s11768-020-9190-6

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  • DOI: https://doi.org/10.1007/s11768-020-9190-6

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