A methodology for deriving a probabilistic braking force model from traffic data

• DOI: 10.70465/ber.v2i2.28
• Publication Date: 2025-04-13T07:18:18Z
• Authors: Amirmahmoud Behzadi; Simone Celati; Michele D’Amato; Agnese Natali; Walter Salvatore

This study presents a methodology for deriving a probabilistic model for estimating the braking force that is, on the contrary, traditionally based on deterministic approaches in bridge design codes. The stochastic model resorts to the Weight-In-Motion (WIM) dataset collected from a provincial road bridge for observing the real traffic load probabilistic distributions in terms of vehicle gross weight and length, and inter-vehicle distance. Using Monte Carlo simulations, traffic convoys are generated for calculating the resultant braking force, by assuming deceleration profiles available in literature and different scenarios, to take into account different braking combinations among the vehicles within a convoy. Starting from the obtained Empirical Cumulative Distribution Function (ECDF) thus calculated, the probabilistic model provides the resultant braking force associated to a given return period, incorporating dynamic amplification factors, too. Comparisons done to highlight that, within the span lengths investigated, the probabilistic model proposed provides higher resultant braking forces than the ones given by the deterministic model adopted by the Eurocode and the Italian Standards, in the case of high return periods and low nominal lives (i.e. in the case of high no-occurrence probability). Whereas, values in agreement or lower than the ones calculated with the deterministic models considered are obtained in the other cases. Finally, some simplified design equations for the resultant braking forces are proposed for three different nominal lives, useful in assessing existing bridges or designing new ones.