A numerical method for a class of Volterra integral equations with logarithmic perturbation kernel

We consider a class of integral equations of Volterra type with constant coefficients containing a logarithmic difference kernel. This class coincides for a=0 with the Symm's equation. We can transform the general integral equation into an equivalent singular equation of Cauchy type which allows us to give an explicit formula for the solution g. The numerical method proposed in this paper consists in substituting the Lagrange polynomial interpolating the known function f in the expression of the solution g.

An algorithm for the numerical resolution of a class of singular integral equations

We consider a class of integral equations of Volterra type with constant coefficients containing a logarithmic difference kernel. This equation can be transformed into an equivalent singular equation of Cauchy type which allows us to give the explicit formula for the solution. The numerical method proposed in this paper consists of applying the Lagrange interpolation to the inner Cauchy type singular integral in the latter formula after subtracting the singularity. For the error of this method weighted norm estimates as well as estimates on discrete subsets of knots are given.

From generalized kinetic theory to discrete velocity modeling of vehicular traffic. A stochastic game approach

This work reports on vehicular traffic modeling by methods of the discrete kinetic theory. The purpose is to detail a reference mathematical framework for some discrete velocity kinetic models recently introduced in the literature, which proved capable of reproducing interesting traffic phenomena without using experimental information as modeling assumptions. To this end, we firstly derive a general discrete velocity kinetic framework with binary nonlocal interactions.

High statistics measurements of pedestrian dynamics

Aiming at a quantitative understanding of basic aspects of pedestrian dynamics, extensive and high-accuracy measurements of real-life pedestrian trajectories have been performed. A measurement strategy based on Microsoft KinectTM has been used. Specifically, more than 100.000 pedestrians have been tracked while walking along a trafficked corridor at the Eindhoven University of Technology, The Netherlands.