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Sensor Fusion as an Enabling Technology for Safety-critical Driver Assistance Systems

Journal Article
2010-01-2339
ISSN: 1946-4614, e-ISSN: 1946-4622
Published October 19, 2010 by SAE International in United States
Sensor Fusion as an Enabling Technology for Safety-critical Driver Assistance Systems
Sector:
Citation: Altendorfer, R., Wirkert, S., and Heinrichs-Bartscher, S., "Sensor Fusion as an Enabling Technology for Safety-critical Driver Assistance Systems," SAE Int. J. Passeng. Cars - Electron. Electr. Syst. 3(2):183-192, 2010, https://doi.org/10.4271/2010-01-2339.
Language: English

References

  1. van der Horst, R. Hogema, J. Time-to-collision and collision avoidance systems Proceedings of the sixth ICTCT workshop Salzburg, Austria 1 12 1993
  2. Muntzinger, M. M. Zuther, S. Dietmayer, K. Probability estimation for an automotive pre-crash application with short filter settling times Proceedings of IEEE Intelligent Vehicles Symposium 411 416 2009
  3. Steinberg, A.N. Bowman, C.L. White, F.E. Revisions to the JDL data fusion model Proceedings of SPIE, Sensor Fusion: Architectures, Algorithms, and Applications III 3719 430 441 1999
  4. Dasarathy, B.V. Information fusion - what, where, why, when, and how? Information Fusion 2 2 75 76 2001
  5. Hall, D.L. McMullen, S.A.H. Mathematical techniques in multisensor data fusion Artech House 2004 second
  6. Levanon, N. Radar Principles Wiley 1988
  7. Sun, Z. Bebis, G. Miller, R. On-road vehicle detection: A review IEEE Transactions on Pattern Analysis and Machine Intelligence 28 5 694 711 2006
  8. Altendorfer, R. Observable dynamics and coordinate systems for automotive target tracking Proceedings of IEEE Intelligent Vehicles Symposium 741 746 2009
  9. Grewal, M.S. Andrews, A.P. Kalman Filtering Wiley 2001
  10. Song, Y.K. Grizzle, J.W. The extended Kalman filter as a local asymptotic observer for nonlinear discrete-time systems Journal of Mathematical Systems, Estimation and Control 5 1 59 78 1995
  11. Aidala, V. Hammel, S. Utilization of modified polar coordinates for bearings-only tracking IEEE Transactions on automatic control 28 3 283 294 1983
  12. Altendorfer, R. Matzka, S. A confidence measure for vehicle tracking based on a generalization of Bayes estimation Proceedings of IEEE Intelligent Vehicles Symposium 766 772 2010
  13. Thrun, S. Burgard, W. Fox, D. Probabilistic Robotics MIT Press 2005
  14. Blackman, S. Popoli, R. Design and analysis of modern tracking systems Artech House Boston 1999
  15. Blackman, S. Multiple-Target Tracking with Radar Applications Artech House 1986
  16. Weinberg, G. V. Estimation of false alarm probabilities in cell averaging constant false alarm rate detectors via Monte Carlo methods Technical Report DSTO-TR-1624 Defence Science and Technology Organisation (Australia) 2004
  17. Viola, P. Jones, M. Rapid object detection using a boosted cascade of simple features IEEE Conference on Computer Vision and Pattern Recognition 1 511 518 2001
  18. Tu, Z. Probabilistic boosting-tree: learning discriminative models for classification, recognition, and clustering Proceedings of IEEE International Conference on Computer Vision 1589 1596 2005
  19. Schweiger, R. Hamer, H. Löhlein, O. Determining posterior probabilities on the basis of cascaded classifiers as used in pedestrian detection systems Proceedings of IEEE Intelligent Vehicles Symposium 1284 1289 2007
  20. Sittler, R.W. An optimal data association problem in surveillance theory IEEE Transactions on Military Electronics 8 2 125 139 1964
  21. Mählisch, M. Szczot, M. Löhlein, O. Munz, M. Dietmayer, K. Simultaneous processing of multitarget state measurements and object individual sensory existence evidence with the joint integrated probabilistic data association filter Proceedings of WIT 2008: 5th International Workshop on Intelligent Transportation 2008
  22. Musicki, D. Evans, R. Stankovic, S. Integrated probabilistic data association IEEE Transactions on automatic control 39 6 1237 1241 1994

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