Particle-based model for skiing traffic

Abstract

We develop and investigate a particle-based model for ski slope traffic. Skiers are modeled as particles with a mass that are exposed to social and physical forces, which define the riding behavior of skiers during their descents on ski slopes. We also report position and speed data of 21 skiers recorded with GPS-equipped cell phones on two ski slopes. A comparison of these data with the trajectories resulting from computer simulations of our model shows a good correspondence. A study of the relationship among the density, speed, and flow of skiers reveals that congestion does not occur even with arrival rates of skiers exceeding the maximum ski lift capacity. In a sensitivity analysis, we identify the kinetic friction coefficient of skis on snow, the skier mass, the range of repelling social forces, and the arrival rate of skiers as the crucial parameters influencing the simulation results. Our model allows for the prediction of speed zones and skier densities on ski slopes, which is important in the prevention of skiing accidents.