A Modification of the Social Force Model by Foresight

The motion of pedestrian crowds (e.g. for simulation of an evacuation situation) can be modeled as a multi-body system of self driven particles with repulsive interaction. We use a few simple situations to determine the simplest allowed functional form of the force function. More complexity may be necessary to model more complex situations. There are many unknown parameters to such models, which have to be adjusted correctly. The parameters can be related to quantities that can be measured independently, like step length and frequency. The microscopic behavior is, however, only poorly reproduced in many situations, a person approaching a standing or slow obstacle will e.g. show oscillations in position, and the trajectories of two persons meeting in a corridor in opposite direction will be far from realistic and somewhat erratic. This is inpart due to the assumption of instantaneous reaction on the momentary situation. Obviously, persons react with a small time lag, while on the other hand they will anticipate changing situations for at least a short time. Thus basing the repulsive interaction on a (linear) extrapolation over a short time (e.g. 1 s) eliminates the oscillations at slowing down and smoothes the patterns of giving way to others to a more realistic behavior. A second problem is the additive combination of binary interactions. It is shown that combining only a few relevant interactions gives better model performance.

Modeling of pedestrian movement around 90 and 180 degree bends

For the planning of large pedestrian facilities, the movement of pedestrians in various situations has to be modelled. Many tools for pedestrian planning are based on cellular automata (CA), discrete in space and time, some use self driven pargticles (SDP), continuous in space and time. It is common experience that CA have problems with modelling sharp bends in wide corridors. They tend to move the pedestrians to the innermost lanes far too strongly, thereby reducing the capacity of the facility. With SDP, the problem seems to be less pronounced but still present. With CA, we compare the performance of two standard shortest distance based static floors on 90 and 180 degree bends with a newly defined one. For SDP, we demonstrate how variations in the modeling of the momentary destination of the agents influence trajectories and capacity.