A microscopic pedestrian-simulation model and its application to intersecting flows

We develop a microscopic pedestrian-simulation model in which pedestrian positions are updated at discrete time steps. At each time step, each pedestrian probabilistically selects a direction of movement from a predetermined set according to a logit-type function that considers the dynamics of other pedestrians around, and then selects a step size that satisfies a certain distribution. We perform a number of field experiments on real intersecting pedestrian flows with four different angles. We then validate and calibrate the model using sample data on the deviation angles, step velocities, and velocity–density relations obtained from the experiments.