Data-based modeling of vehicle collisions by nonlinear autoregressive model and feedforward neural network

Information Sciences

Volumn 235, Issue , 2013, Pages 65-79

  Pawlus, Witold ^a   Karimi, Hamid Reza ^a   Robbersmyr, Kjell G ^a  

^a UNIVERSITY OF AGDER   (Norway)

Author keywords

Data based modeling; Feedforward neural network; Nonlinear autoregressive model; Vehicle crash

Indexed keywords

AUTOREGRESSIVE SYSTEMS; DATA-BASED MODELING; KINEMATIC RESPONSE; NONLINEAR AUTOREGRESSIVE MODEL; VEHICLE ACCELERATION; VEHICLE COLLISIONS; VEHICLE CRASHES; VISUAL INSPECTION;

AUTOMOBILE TESTING; COMPLEX NETWORKS; CRASHWORTHINESS; FEEDFORWARD NEURAL NETWORKS; KINEMATICS; VEHICLES;

ACCIDENTS;

EID: 84875950847     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2012.03.013     Document Type: Article

References (47)

1. H. Abedelwahab, M.A. Abdel-Aty, Development of artificial neural networks models to predict driver injury severity in traffic accidents at signalized intersections, in: Transportation Research Board 80th Annual Meeting, Washington, DC, USA, 2001.
2. M. Basso, L. Giarré, S. Groppi, and G. Zappa NARX models of an industrial power plant gas turbine IEEE Transactions on Control Systems Technology 13 4 2005 599 604
3. J. Bock, and J. Hettenhausen Discrete particle swarm optimisation for ontology alignment Information Sciences 192 2012 152 173
4. T. Belytschko On computational methods for crashworthiness Computers and Structure 1992
5. C.H. Cheng, T.L. Chen, and L.Y. Wei A hybrid model based on rough sets theory and genetic algorithms for stock price forecasting Information Sciences 180 9 2010 1610 1629
6. K.H. Chon, and R.J. Cohen Linear and nonlinear ARMA model parameter estimation using an artificial neural network IEEE Transactions on Biomedical Engineering 44 3 1997
7. J.T. Connor, R.D. Martin, and L.E. Atlas Recurrent neural networks and robust time series prediction IEEE Transactions on Neural Networks 5 2 1994 240 254
8. S.F. Crone, and N. Kourentzes Feature selection for time series prediction-a combined filter and wrapper approach for neural networks Neurocomputing 73 10-12 2010 1923 1936
9. M. Crucianu, Z. Uhry, R. Boné, J.-P. Asselin de Beauville, NAR time-series prediction: a Bayesian framework and an experiment, in: Proceedings of the European Symposium on Artificial Neural Networks (ESANN'98), Bruges, Belgium, April 1998.
10. A. Deb, and K.C. Srinivas Development of a new lumped-parameter model for vehicle side-impact safety simulation Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 222 2008 1793 1811
11. A. Eskandarian, D. Marzougui, N.E. Bedewi, Finite Element Model and Validation of a Durrogate Crash Test Vehicle for Impacts with Roadside Objects, Technical Report, National Crash Analysis Center, Virginia, USA, 1997.
12. L. Faes, G. Nollo, and K.H. Chon Linear and nonlinear parametric model identification to assess granger causality in short-term cardiovascular interactions Computers in Cardiology 35 2008 793 796
13. M. Gan, H. Peng, X. Peng, X. Chen, and Garba Inoussa A locally linear RBF network-based state-dependent AR model for nonlinear time series modeling Information Sciences 180 22 2010 4370 4383
14. U.N. Gandhi, and S.J. Hu Data-based approach in modeling automobile crash International Journal of Impact Engineering 16 1 1995 95 118
15. Z.X. Guo, W.K. Wong, and M. Li Sparsely connected neural network-based time series forecasting Information Sciences 193 2012 54 71
16. M. Huang Vehicle Crash Mechanics 2002 CRC Press Boca Raton ISBN 0-8493-0104-1
17. ISO 6487:2000. Road Vehicles-Measurement Techniques in Impact Tests-Instrumentation.
18. K.-S. Jeong, D.-K. Kim, J.-M. Jung, M.-C. Kim, and G.-J. Joo Non-linear autoregressive modelling by Temporal Recurrent Neural Networks for the prediction of freshwater phytoplankton dynamics Ecological Modelling 211 3-4 2008 292 300
19. P. Jonsén, E. Isaksson, K.G. Sundin, and M. Oldenburg Identification of lumped parameter automotive crash models for bumper system development International Journal of Crashworthiness 14 6 2009 533 541
20. H.R. Karimi, and K.G. Robbersmyr Signal analysis and performance evaluation of a vehicle crash test with a fixed safety barrier based on Haar wavelets International Journal of Wavelets, Multiresolution and Image Processing 9 1 2011 131 149
21. H.S. Kim, S.Y. Kang, I.H. Lee, S.H. Park, and D.C. Han Vehicle frontal crashworthiness analysis by simplified structure modeling using nonlinear spring and beam elements International Journal of Crashworthiness 2 1 1996 107 118
22. E. van der Laan, F. Veldpaus, B. de Jager, M. Steinbuch, LPV modeling of vehicle occupants, in: 9th International Symposium on Advanced Vehicle Control (AVEC '08), Kobe, Japan, October 2008.
23. J. McFadden, W.T. Yang, and R.S. Durrans Application of artificial neural networks to predict speeds on two-lane rural highways Transportation Research Record 1751 2001 9 17
24. N.E. Mitrakis, and J.B. Theocharis A diversity-driven structure learning algorithm for building hierarchical neuro-fuzzy classifiers Information Sciences 186 1 2012 40 58
25. Z. Moumni, and F. Axisa Simplified modelling of vehicle frontal crashworthiness using a modal approach International Journal of Crashworthiness 9 3 2004 285 297
26. F. Nasoz, C.L. Lisetti, and A.V. Vasilakos Affectively intelligent and adaptive car interfaces Information Sciences 180 20 2010 3817 3836
27. T. Omar, A. Eskandarian, and N. Bedewi Vehicle crash modelling using recurrent neural networks Mathematical and Computer Modelling 28 9 1998 31 42
28. W. Pawlus, H.R. Karimi, and K.G. Robbersmyr Application of viscoelastic hybrid models to vehicle crash simulation International Journal of Crashworthiness 16 2 2011 195 205
29. W. Pawlus, H.R. Karimi, and K.G. Robbersmyr Development of lumped-parameter mathematical models for a vehicle localized impact Journal of Mechanical Science and Technology 25 7 2011 1737 1747
30. W. Pawlus, H.R. Karimi, and K.G. Robbersmyr Mathematical modeling of a vehicle crash test based on elasto-plastic unloading scenarios of spring-mass models International Journal of Advanced Manufacturing Technology 55 2011 369 378
31. W. Pawlus, K.G. Robbersmyr, and H.R. Karimi Mathematical modeling and parameters estimation of a car crash using data-based regressive model approach Applied Mathematical Modelling 35 2011 5091 5107
32. H.T. Pham, V.T. Tran, and B.-S. Yang A hybrid of nonlinear autoregressive model with exogenous input and autoregressive moving average model for long-term machine state forecasting Expert Systems with Applications 37 4 2010 3310 3317
33. K.G. Robbersmyr, Calibration Test of a Standard Ford Fiesta 1.1l, Model Year 1987, According to NS-EN 12767. Technical Report 43/2004, Agder Research, Grimstad, 2004.
34. A.F. Sheta, and K.D. Jong Time-series forecasting using GA-tuned radial basis functions Information Sciences 133 3-4 2001 221 228
35. C.A. Soto Structural topology optimization for crashworthiness International Journal of Crashworthiness 9 3 2004 277 284
36. V. Syrris, and V. Petridis A lattice-based neuro-computing methodology for real-time human action recognition Information Sciences 181 10 2011 1874 1887
37. T.L. Tenga, F.A. Changb, Y.S. Liuc, and C.P. Peng Analysis of dynamic response of vehicle occupant in frontal crash using multibody dynamics method Mathematical and Computer Modelling 48 11-12 2008 1724 1736
38. A.R. Várkonyi-Kóczy, A. Rövid, P. Várlaki, Intelligent methods for car deformation modeling and crash speed estimation, in: The 1st Romanian-Hungarian Joint Symposium on Applied Computational Intelligence, Timisoara, Romania, May 2004.
39. N.A. Vien, H. Yu, and T.C. Chung Hessian matrix distribution for Bayesian policy gradient reinforcement learning Information Sciences 181 9 2011 1671 1685
40. D. Wang, K.-Y. Lum, G. Yang, Parameter estimation of ARX/NARX model: a neural network based method, in: Proceedings of the 9th International Conference on Neural Information Processing (ICONIPOZ), Singapore, 2002.
41. Y. Xie, D. Lord, and Y. Zhang Predicting motor vehicle collisions using Bayesian neural network models: an empirical analysis Accident Analysis and Prevention 39 5 2007 922 933
42. G. Yang, Y. Lin, and P. Bhattacharya A driver fatigue recognition model based on information fusion and dynamic Bayesian network Information Sciences 180 10 2010 1942 1954
43. R. Zemouri, R. Gouriveau, and N. Zerhouni Defining and applying prediction performance metrics on a recurrent NARX time series model Neurocomputing 73 13-15 2010 2506 2521
44. ∞ Model reduction for switched LPV systems with average dwell time IEEE Transactions on Automatic Control 53 10 2008 2443 2448
45. L. Zhang, N. Cui, M. Liu, and Y. Zhao Asynchronous filtering of discrete-time switched linear systems with average dwell time IEEE Transactions on Circuits and Systems I: Regular Papers 58 5 2011 1109 1118
46. Y. Zhao, L. Zhang, S. Shen, and H. Gao Robust stability criterion for discrete-time uncertain Markovian jumping neural networks with defective statistics of modes transition IEEE Transactions on Neural Networks 22 1 2010 164 170
47. G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm Autoregressive moving average model for analyzing edge localized mode time series on Axially Symmetric Divertor Experiment (ASDEX) Upgrade tokamak Physics of Plasmas 11 12 2004 5658 5667