Abstract
Background: The speed of a vehicle in a curve can be estimated by analysing yaw marks, which indicate its orientation around the vertical axis. When it exceeds the "critical speed," the vehicle slides laterally, evidenced by the oscillation of the rear tires relative to the front ones. Aim: To present a methodology for reconstructing yaw accidents, with an analysis of uncertainties. Methods: This article uses Monte Carlo simulation software to address uncertainties in determining the critical yaw speed of vehicles. The radius of curvature is calculated considering the chord, average arrow, and vehicle gauge, while the road is characterized by negative superelevation and specific friction coefficient. The simulation models input variables with probabilistic distributions, analysing uncertainties related to road characteristics, vehicle properties, environmental conditions, and measurement errors. Results: The simulation results provide a detailed assessment of the uncertainties involved in determining the critical yaw speed, highlighting the importance of a probabilistic approach to ensure a more realistic and reliable assessment of vehicular safety. Discussion: When evaluating measurement uncertainties, it is essential to consider the sensitivity coefficient to ensure a precise and comprehensive analysis of uncertainty sources. Conclusions: This study highlights the importance of analysing and controlling critical variables, such as the radius of curvature and friction coefficient, to accurately determine the critical yaw speed and ensure reliable vehicular safety measures..
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