DOI: 10.5061/dryad.2ngf1vhs6
title: Data from: Multiobjective optimization algorithm for accurate MADYMO reconstruction of vehicle-pedestrian accidents

description: Uncertainty in reconstruction accuracy is a critical problem faced in the
 current traffic accident reconstruction process. The purpose of this study
 is to explore the use of an improved optimization algorithm combined with
 MAthematical DYnamic MOdels (MADYMO) multibody simulations and crash data
 to conduct accurate reconstructions of vehicle–pedestrian accidents. The
 performance of three commonly employed multiobjective optimization
 algorithms, including nondominated sorting genetic algorithm-II (NSGA-II),
 neighbourhood cultivation genetic algorithm (NCGA) and multiobjective
 particle swarm optimization (MOPSO) were compared and evaluated. The
 effects of the number of objective functions, the selection of different
 objective functions and the optimal number of iterations are also
 investigated. The present study indicated that NSGA-II had better
 convergence and generated more noninferior solutions and better final
 solutions than NCGA and MOPSO. And multibody simulations coupled with
 optimization algorithms can be used to accurately reconstruct
 vehicle-pedestrian collisions.
description: We selected the commercial DJI Inspire 2 (DJI, China) to document
 the accident scene and established the accident scene model based
 on Context Capture software (Bentley, USA). We compared this model with
 video information to determine the speed of the vehicle at the time of the
 accident. Faro Focus 3D S120 laser scanning and postprocessing software
 FARO SCENE (FARO, US) were used to scan the accident vehicle and obtain
 point cloud data that were processed in Geomagic 2017 software (3D Systems
 Corporation, America). The facet model of the vehicle was obtained. And we
 built the accident collision model in MADYMO using the human
 model provided by TNO. The relevant models have been uploaded in the
 metadata. Based on the actual accident results, the
 objective function was established by different collision markers. The
 optimization algorithms were used to optimize the parameters of the
 accident crash model by Isight software (DS SIMULIA) to study the effects
 of different algorithms and different preimpact parameters on the
 optimization results. We created two datasets (described below) including
 three subsets of optimization results for different algorithms and 11
 subsets of optimization results for different preimpact parameters,
 respectively.
description: ZIP files contains the accident scene model, the vehicle facet
 model and two datasets of accident simulation parameters obtained by
 algorithms, and two datasets of validation cases. The
 download links for the related software are as follows:
 Context Capture software: https://www.bentley.com/software/contextcapture/   FARO SCENE: https://www.faro.com/en/Products/Software/SCENE-Software  Geomagic: https://cn.3dsystems.com/software and alternative software Meshlab: https://www.meshlab.net/  Isight: https://www.3ds.com/newsroom/press-releases/dassault-systemes-announces-isight-abaqus and alternative software R：https://www.r-project.org/  MADYMO: https://tass.plm.automation.siemens.com/cn/madymo-0  Hypermesh: https://www.altair.com/hypermesh/ and alternative software ANSA https://www.ansa-usa.com/software/ansa/