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Driver’s Response Prediction Using Naturalistic Data Set

Journal Article
2019-01-0128
ISSN: 2641-9645, e-ISSN: 2641-9645
DOI: https://doi.org/10.4271/2019-01-0128
Published April 02, 2019 by SAE International in United States
Driver’s Response Prediction Using Naturalistic Data Set
Sector:
Citation: Lanka, V., Heydinger, G., and Guenther, D., "Driver’s Response Prediction Using Naturalistic Data Set," SAE Int. J. Adv. & Curr. Prac. in Mobility 1(2):524-530, 2019, https://doi.org/10.4271/2019-01-0128.
Language: English

References

  1. Victor , T. , Dozza , M. , Bärgman , J. , Boda , C.N. et al. 2015
  2. Pilipovic , M. , Spasojevic , D. , Velikic , I. , and Teslic , N. Toward Intelligent Driver-Assist Technologies and Piloted Driving: Overview, Motivation and Challenges Proceedings of the X International Symposium on Industrial Electronics (INDEL’14) 2014
  3. SAE Vehicle Dynamics Standards Committee Steady-State Directional Control Test Procedures for Passenger Cars and Light Trucks 1996
  4. Dingus , T.A. , Hankey , J.M. et al. 2015
  5. Parks , T.W. and Burrus , C.S. Digital Filter Design Wiley-Interscience 1987
  6. Baum , L.E. An Inequality and Associated Maximization Technique in Statistical Estimation for Probabilistic Functions of Markov Process Inequalities 3 1 8 1972
  7. Hassan , M.R. and Nath , B. Stock Market Forecasting Using Hiden Markov Model: A New Approach Intelligent Systems Design and Applications, 2005. ISDA’05. Proceeding. 5th International Conference on 182 196 2005
  8. Ocak , H. , and Loparo , K.A. A New Bearing Fault Detection and Diagnosis Scheme Based on Hidden Markov Modeling of Vibration Signals Acoustics, Speech, and Signal Processing, 2001. Proceedings.(ICASSP'01). 2001 IEEE International Conference on 5 3141 3144 2001
  9. Rabiner , L.R. , and Juang , B.H. Fundamentals of Speech Recognition 1993
  10. Moon , T.K. The Expectation-Maximization Algorithm IEEE Signal Processing Magazine 13 6 47 60 1996
  11. Rabiner , L.R. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition Proceedings of the IEEE 77 2 257 286 1989
  12. Quinlan , J.R. Induction of Decision Trees Machine Learning 1 81 106 1986
  13. Prasad , A.M. , Iverson , L.R. , and Liaw , A. Newer Classification and Regression Tree Techniques: Bagging and Random Forests for Ecological Prediction Ecosystems 9 2 181 199 2006
  14. Liaw , A. and Wiener , M. Classification and Regression by Random Forest R News 2 3 18 22 2002
  15. Geurts , P. , Ernst , D. , and Wehenkel , L. Extremely Randomized Trees Machine Learning 63 1 3 42 2006
  16. Wold , S. , Esbensen , K. , and Geladi , P. Principal Component Analysis Chemometrics and Intelligent Laboratory Systems 2 1-3 37 52 1987
  17. Geurts , P. , Ernst , D. , and Wehenkel , L. Extremely Randomized Trees Machine Learning 63 1 3 42 2006
  18. Shi , T. , Seligson , D. , Belldegrun , A.S. , Palotie , A. et al. Tumor Classification by Tissue Microarray Profiling: Random Forest Clustering Applied to Renal Cell Carcinoma Modern Pathology 18 4 547 2005
  19. Altman , N.S. An Introduction to Kernel and Nearest- Neighbor Nonparametric Regression The American Statistician 46 3 175 185 1992

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