Computing Methods in the Analysis of Road Accident Reconstruction Uncertainty

Marek Guzek , Zbigniew Lozia

Abstract

The study is dedicated to the problem of uncertainty in the analysis of accident situations in road traffic. The term “uncertainty” is generally known when used with reference to measurement techniques, but its application to the analyses of accident situations in road traffic, including accident reconstruction, is a relatively new field of knowledge. The objectives of this work include the presentation and examination of selected aspects related to the taking of uncertainty into account when analysing the course of an accident and making the necessary calculations. Apart from the scientific objectives, an important utilitarian goal may also be pointed out. The data and methods presented may be used by automotive technology experts in their accident reconstruction work. The paper shows seven methods that enable the taking into account of the uncertainty of the data used for calculations, i.e. extreme values method, total differential method, higher-order total differential method, finite-difference method, Gauss method, method based on the description of stochastic processes, and Monte-Carlo method. Apart from formal (mathematical) descriptions of the methods, an example of their use for the estimation of uncertainty of selected quantities that describe an accident situation has been demonstrated. The bad and good points of individual methods have been shown in the context of the application considered.
Author Marek Guzek (FT / DVMO)
Marek Guzek,,
- Department of Vehicle Maintance and Operation
, Zbigniew Lozia (FT / DVMO)
Zbigniew Lozia,,
- Department of Vehicle Maintance and Operation
Journal seriesArchives of Computational Methods in Engineering, ISSN 1134-3060, e-ISSN 1886-1784
Issue year2020
Pages1-18
Publication size in sheets0.85
ASJC Classification1706 Computer Science Applications; 2604 Applied Mathematics
DOIDOI:10.1007/s11831-020-09462-w
URL https://link.springer.com/article/10.1007/s11831-020-09462-w
Languageen angielski
LicenseJournal (articles only); published final; Uznanie Autorstwa (CC-BY); after publication
File
Guzek-Lozia2020_Article_ComputingMethodsInTheAnalysisO.pdf 2.86 MB
Score (nominal)200
Score sourcejournalList
ScoreMinisterial score = 200.0, 14-07-2020, ArticleFromJournal
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2018 = 3.484; WoS Impact Factor: 2018 = 7.242 (2) - 2018=6.807 (5)
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