Vehicle Risk Level Estimation by Using Experimental Trajectories in Bend

This paper tackles the general context of road safety, focussing on the light vehicles safety in bends. It consists to use a reliability analysis in order to estimate the failure probability of vehicle trajectories. Firstly, we build probabilistic models able to describe measured trajectories in a given bend. The models are transforms of scalar normalized second order stochastic processes which are stationary, ergodic and non-Gaussian. The process is characterized by its probability density function and its power spectral density estimated starting from the experimental trajectories. The probability density is approximated by a development on the Hermite polynomials basis. The second part is devoted to apply a reliability strategy intended to associate a risk level to each class of trajectories. Based on the joint use of probabilistic methods for modelling uncertainties, reliability analysis for assessing risk levels and statistics for classifying the trajectories, this approach provides a realistic answer to the tackled problem.