Modeling and Statistical Analysis of Braking Parameters for Improving Traffic Safety

Abstract

This paper examines, from a combined engineering and statistical perspective, how key braking parameters affect traffic
safety, with the aim of proposing a robust framework for modeling and evaluation. The main variables considered, initial speed,
tire-road adhesion, the condition and temperature of the braking system, axle load distribution, hydraulic pressure, and driver
reaction time, are used to estimate braking distance, average deceleration, and their variation under real operating conditions.
Illustrative calculations and comparative scenarios are used to quantify how these factors, individually and in combination, affect
stopping performance, and to identify parameter combinations with a disproportionate impact on outcomes. Based on the resulting
model, operational thresholds for preventive maintenance are proposed, along with scenarios for reducing the variability of braking
response. The results indicate that incorporating thermal and mechanical effects into the predictive model produces more stable
estimates of braking distance and more reliable inputs for decision-making in vehicle design, approval, and maintenance. The
paper’s main contribution is an integrated deterministic model that combines classical stopping-distance mechanics with correction
factors for adhesion, thermal effects, and load distribution, offering an objective basis for prioritizing safety related technical
interventions.