APPLICATION OF EVIDENCE ACCUMULATION BASED ON ESTIMATION THEORY AND HUMAN PSYCHOLOGY FOR AUTOMOTIVE AIRBAG SUPPRESSION

Michael E. Farmer

2011

Abstract

The traditional D-S conditioning is based on a collection of ‘experts’ inputting their evidence and accumulating the beliefs. Researchers have often adopted this same mechanism for integrating evidence from single sources of evidence over time, such as seen in sensor networks. The traditional D-S conditioning ensures the order of inputs does not matter. While this is sensible for a collection of experts we propose that it is not suitable for a single input providing streams of evidence. Research in psychology show order of integration of evidence does matter, and depending on the application humans have a preference for recency or primacy. Estimation theory provides frameworks for analyzing data over time, and recently some researchers have proposed integrating evidence in an estimation-inspired manner. We then propose a Kalman-filter based approach for integrating temporal streams of evidence from a single sensor. We then propose the system uncertainty be modeled by the conflict defined by Dempster. We then define a real-time evidence accumulation system for airbag suppression and demonstrate that the Kalman filter-based approach indeed out-performs Dempster-Shafer based evidence accumulation.

References

  1. .7549 .6725 .6920 .7961 .8568 Baratgin, J., & Politzer, G. (2007). The psychology of dynamic probability judgment: order effect, normative theories, and experimental methodology. Mind & Society , 53-66.
  2. Benferhet, S., Dubois, D., & Prade, H. (2000). Kalmanlike filtering in a qualitative setting. INRIA.
  3. Dubois, D., & Prade, H. (1997). A synthetic view of belief revision with uncertain inputs in a framework of possibility theory. International Journal of Approximate Reasoning , 295-324.
  4. Farmer, M. E. (2006). Integrating temporal streams of image classifications using evidential reasoning. PRoc. of Conference on Electro-information Technology (pp. 360-365). IEEE.
  5. Farmer, M. E., & Reiman, J. (2006). Fusion of motion information with static classifications of occupant images for smart airbag applications. Proc. Intl. Conference on Information Fusion (pp. 1-8). IEEE .
  6. Gelb, A. (1974). Applied Optimal Estimation. Cambridge: MIT Press.
  7. Hogarth, R. M., & Einhorn, H. J. (1992). Order effects in belief updating: The belief-adjustment model. Cognitive Psychology , 1-55.
  8. Liu, W., & Hong, J. (2000). Re-investigating Dempster's idea on evidence combination. Knowledge and Information Systems , 223-241.
  9. McKenzie, C. R., Lee, S. M., & Chen, K. K. (2002). When negative evidence increases confidence: Change in belief after hearing two sides of a dispute. Journal of Behavioral Decision Making , 1-18.
  10. Premaratne, K., Dewasurendra, D. A., & Bauer, P. H. (2007). Evidence combination in an environment with heterogeneous sources. IEEE. Trans on Systems, Man, and Cybernetics-Part A: Systems and Humans , 298- 309.
  11. Schubert, J. (2008). Conflict management in DempsterShafer theory by sequential discounting using the degree of falsity. Procs. of Intl. Conf. on Information Processing and Management of Uncertainty in Knowledge-based Systems, (pp. 298-305).
  12. Shafer, G. (1976). A Mathematical Theory of Evidence. Princeton: Princeton University Press.
  13. Wang, H., Zhang, J., & Johnson, T. R. (1999). Order effects in human belief revision. Proceedings of the 1999 Cognitive Science Society Conference.
  14. Wu, H., Siegel, M., & Ablay, S. (2003). Sensor fusion using Dempster-Shafer theory II: Static weighting and Kalman filter-like dynamic weighting. Procs. of Instrumentation and Measurement Technology Conference (pp. 907-912). IEEE.
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Paper Citation


in Harvard Style

E. Farmer M. (2011). APPLICATION OF EVIDENCE ACCUMULATION BASED ON ESTIMATION THEORY AND HUMAN PSYCHOLOGY FOR AUTOMOTIVE AIRBAG SUPPRESSION . In Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ANNIIP, (ICINCO 2011) ISBN 978-989-8425-74-4, pages 470-476. DOI: 10.5220/0003650004700476


in Bibtex Style

@conference{anniip11,
author={Michael E. Farmer},
title={APPLICATION OF EVIDENCE ACCUMULATION BASED ON ESTIMATION THEORY AND HUMAN PSYCHOLOGY FOR AUTOMOTIVE AIRBAG SUPPRESSION},
booktitle={Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ANNIIP, (ICINCO 2011)},
year={2011},
pages={470-476},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003650004700476},
isbn={978-989-8425-74-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ANNIIP, (ICINCO 2011)
TI - APPLICATION OF EVIDENCE ACCUMULATION BASED ON ESTIMATION THEORY AND HUMAN PSYCHOLOGY FOR AUTOMOTIVE AIRBAG SUPPRESSION
SN - 978-989-8425-74-4
AU - E. Farmer M.
PY - 2011
SP - 470
EP - 476
DO - 10.5220/0003650004700476