Uncertainty of calculation results in vehicle collision analysis

Wach, Wojciech; Unarski, Jan

doi:10.1016/j.forsciint.2006.06.061

Cited by 47 publications

(24 citation statements)

References 1 publication

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“…Prova disso é que o MMC tem sido uma ferramenta essencial em diversas áreas da ciência, dentre elas: economia [6]; medicina [7]; medicina nuclear [8]; biologia [9]; ecologia [10,11]; física do clima [12]; climatologia [13,14]; engenharias [15,16]; modelagem de colisões veiculares [17][18][19][20].…”

Section: Método De Monte Carlounclassified

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Carvalho¹,

Armigliato²,

Almeida³

et al. 2016

Rev. Bras. Crimin.

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ResumoEste trabalho apresenta um modelo para análise probabilística de perícias de colisão de veículos automotores, apresentando um modelo computacional flexível para avaliação da confiabilidade por simulação Monte Carlo. Os procedimentos desenvolvidos buscaram a representação estatística dos parâmetros ambientais e psicomotores, tais como coeficientes de atrito e ritmo de Reação, em uma simulação, com 10.000 iterações, da confiabilidade em um modelo bidimensional aplicado a um estudo de caso de colisão frontal envolvendo dois veículos de passeio, obtendo intervalos unilaterais e bilaterais para as variáveis estudadas. AbstractThis paper presents a model for probabilistic analysis skills collision of motor vehicles, featuring a flexible computational model for the evaluation of reliability by Monte Carlo simulation. The developed procedures sought statistical representation of environmental and psychomotor parameters such as friction coefficient and reaction rate in a simulation with 10,000 iterations, reliability in a twodimensional model applied to a frontal collision case study involving two vehicles, obtaining unilateral and bilateral ranges for the variables studied.

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Section: Método De Monte Carlounclassified

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Carvalho¹,

Armigliato²,

Almeida³

et al. 2016

Rev. Bras. Crimin.

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“…The majority of typical measurements taken by the police officers in accident scenes are assumed to follow normal distributions (Wach and Unarski, 2007). The empirical parameters are usually assumed to follow the uniform distribution if no information is given (Liu, 1999).…”

Section: Distributions Of Independent Variablementioning

confidence: 99%

“…For example, the friction coefficient between vehicles and dry road is considered to be uniformly distributed in [0.7, 0.9]. More information about the distributions of independent variables can be found in Wach and Unarski (2007) and Liu (1999), as to what distribution a specific variable obeys is not discussed in depth in this study, and an assumption is made that distributions of independent variables are known.…”

Section: Distributions Of Independent Variablementioning

confidence: 99%

“…Deterministic methods include Total Differential Method (TDM) (Liu, 1999;Williams et al, 2012), Upper and Lower bound Method (ULM) (Lozia and Guzek, 2005;Brach and Brach, 2005), Finite Difference Method (FDM) (Bartlett and Fonda, 2003) and Response Surface Methodology (RSM) (Zou et al, 2012a;Du et al, 2009); probabilistic methods include Gauss Method (Brach and Brach, 2005), Methods with the Use of Stochastic Processes (Lozia and Guzek, 2005), Probabilistic Perturbation Method (Zhang and Li, 2007) and Monte Carlo Method (MCM) (Brach and Dunn, 2004;Kurzhanskiy and Varaiya 2012). The application of these methods in practice can be found in Bartlett (2003), Wood and O'riordain (1994), Bartlett et al (2002), Li et al (2004), Fonda (2004), Zou et al (2012b) and Wach (2007Wach ( , 2013. And the ULM, FDM and RSM can easily be applied to http://dx.doi.org/10.1016/j.trc.2014.09.004 0968-090X/Ó 2014 Elsevier Ltd. All rights reserved.…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of simulation uncertainty in accident reconstruction via combining Response Surface Methodology and Monte Carlo Method

Cai

Zou

Luo

et al. 2014

Transportation Research Part C: Emerging Technologies

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“…The calculable parameters are affected by uncertainties on the first available data, which propagate during the calculation process [24,25]. They also change based on the adopted physical model approximation that necessarily simplifies the phenomenon [26,27].…”

Section: Introductionmentioning

confidence: 99%

Vehicle Accident Databases: Correctness Checks for Accident Kinematic Data

Vangi

Cialdai

Gulino

et al. 2018

Designs

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(1) Background: Data collection procedures allow to obtain harmonization of in-depth road accident databases. Plausibility of calculable accident-related kinematic parameters depends on the constraints imposed on calculation, making their uncertainty degree higher than the one for measurable parameters (i.e., traces, airbag activation, etc.). Uncertainty translates in information loss, making the statistics based on databases analysis less consistent. Since kinematic parameters describe the global accident dynamics, their correctness assessment has a fundamental importance; (2) Methods: the paper takes as reference data collected in the Initiative for the GLobal harmonisation of Accident Data (IGLAD) database for vehicle-to-vehicle crashes. The procedure, however, has general nature and applies identically for other databases and multiple impacts between vehicles. To highlight issues which can arise in accident-related data collection, 3 different checks are proposed for parameters correctness assessment; (3) Results: by 4 examples, 1 with correct and 3 with incorrect parameters reported, the paper demonstrates that errors can go beyond simple calculation uncertainty, implying that a deeper analysis is desirable in data collection; (4) Conclusions: the step-by-step guidelines described in this paper will help in increasing goodness of collected data, providing for a methodology which can be used by each individual involved in accident data collection, both for collection itself and subsequent verification analysis.

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Uncertainty of calculation results in vehicle collision analysis

Cited by 47 publications

References 1 publication

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Análise probabilística de colisões veiculares pelo método de Monte Carlo

Evaluation of simulation uncertainty in accident reconstruction via combining Response Surface Methodology and Monte Carlo Method

Vehicle Accident Databases: Correctness Checks for Accident Kinematic Data

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