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Computing Methods in the Analysis of Road Accident Reconstruction Uncertainty

机译:公路事故重建分析的计算方法

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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.
机译:该研究致力于在公路交通中分析事故情况下的不确定性问题。当参考测量技术使用时,术语“不确定性”通常是已知的,但其在公路交通中的事故情况下的应用,包括事故重建,是一个相对较新的知识领域。这项工作的目标包括在分析事故过程中的过程和必要的计算时考虑到账户所需的所选方面的展示和审查。除了科学目标外,还可能指出一个重要的功利目标。提供的数据和方法可以通过汽车技术专家在其事故重建工作中使用。本文显示了七种方法,可以考虑到用于计算的数据的不确定性,即极值方法,总差分方法,高阶总差分方法,有限差分方法,高斯方法,基于描述的方法随机过程和蒙特卡罗方法。除了对方法的正式(数学)描述之外,已经证明了它们用于估计描述事故情况的所选数量不确定性的用途。在考虑的申请的背景下显示了个别方法的不良和良好点。

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