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dc.contributor.authorMunyazikwiye, Bernard B.
dc.contributor.authorKarimi, Hamid Reza
dc.contributor.authorRobbersmyr, Kjell Gunnar
dc.date.accessioned2018-03-20T09:50:09Z
dc.date.available2018-03-20T09:50:09Z
dc.date.created2017-03-01T13:59:16Z
dc.date.issued2017
dc.identifier.citationMunyazikwiye, B. B., Karimi, H. R. & Robbersmyr, K. G. (2017). Optimization of Vehicle-to-Vehicle Frontal Crash Model based on Measured Data using Genetic Algorithm. IEEE Access, 5, 3131-3138. doi:nb_NO
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/11250/2491210
dc.description.abstractIn this paper, a mathematical model for vehicle-to-vehicle frontal crash is developed. The experimental data are taken from the National Highway Traffic Safety Administration. To model the crash scenario, the two vehicles are represented by two masses moving in opposite directions. The front structures of the vehicles are modeled by Kelvin elements, consisting of springs and dampers in parallel, and estimated as piecewise linear functions of displacements and velocities, respectively. To estimate and optimize the model parameters, a genetic algorithm approach is proposed. Finally, it is observed that the developed model can accurately reproduce the real kinematic results from the crash test.nb_NO
dc.language.isoengnb_NO
dc.publisherIEEEnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleOptimization of Vehicle-to-Vehicle Frontal Crash Model based on Measured Data using Genetic Algorithmnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionpublishedVersionnb_NO
dc.rights.holder© 2020 The Author(s)
dc.source.pagenumber3131-3138nb_NO
dc.source.volume5nb_NO
dc.source.journalIEEE Accessnb_NO
dc.identifier.doi10.1109/ACCESS.2017.2671357
dc.identifier.cristin1455027
dc.description.localcodenivå1nb_NO
cristin.qualitycode1


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