Can we reliably predict and quantitatively describe how large groups of people behave? Here we discuss an emerging approach to this problem which is based on the quantitative methods of statistical physics. We demonstrate that in cases when the interactions between the members of a group are relatively well defined (e.g, pedestrian traffic, synchronization, panic) the corresponding models reproduce relevant aspects of the observed phenomena. In particular, people moving in the same environment typically develop specific patterns of collective motion including the formation of lanes, flocking or jamming at bottlenecks. We simulate such phenomena assuming realistic interactions between particles representing humans. The two specific cases to be discussed in more detail are waves produced by crowds at large sporting events and the main features of pedestrian escape panic under various conditions. Our models allow the prediction of crowd behavior even in cases when experimental methods are obviously not applicable and, thus, are expected to be useful in assessing the level of security in situations involving large groups of excited people.
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