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.

该研究致力于道路交通事故情况分析中的不确定性问题。当结合测量技术使用时，术语“不确定性”通常是已知的，但是将其应用于道路交通事故情况分析（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介绍和检查与分析事故过程和进行必要的计算时考虑到不确定性有关的选定方面。除了科学目标之外，还可以指出一个重要的功利目标。所提供的数据和方法可能会被汽车技术专家用于事故重建工作。本文介绍了七个方法，这些方法可以考虑用于计算的数据的不确定性，即极值方法，总微分方法，高阶总微分方法，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洛方法。除了对方法的正式（数学）描述之外，还展示了使用这些方法来估计描述事故情况的选定数量的不确定性的示例。个别方法的优缺点已在所考虑的应用程序上下文中显示。随机过程的描述和蒙特卡洛方法。除了对方法的正式（数学）描述之外，还展示了使用这些方法来估计描述事故情况的选定量的不确定性的示例。个别方法的优缺点已在所考虑的应用程序上下文中显示。随机过程的描述和蒙特卡洛方法。除了对方法的正式（数学）描述之外，还展示了使用这些方法来估计描述事故情况的选定量的不确定性的示例。个别方法的优缺点已在所考虑的应用程序上下文中显示。