By observing the collective movement of thousands of Chicago Marathon runners queueing up to the starting line, researchers find that the motion of large crowds is fluid-like and mathematically predictable. According to the new study, the collective behavior of large crowds can be described solely using principals based in hydrodynamic theory by applying a fluid-like model to crowd dynamics. The findings suggest that the predictive power of hydrodynamic crowd modeling may provide quantitative guidance in crowd management - particularly important in situations where crowd dynamics can turn dangerous, like in a panic situation created by accidents or violence. Understanding the collective movements of animals has largely been based on complex interactions between individuals within the group - each with a set of "rules" and motivations that govern behavior. For humans, however, this agent-based approach is limited in its ability to describe the movement of crowds. Presenting a different approach, Nicolas Bain and Denis Bartolo ignore individual agents and instead treat the crowd as an entity itself in order to establish a hydrodynamic theory of large-scale human movement free of behavioral assumption. Bain and Bartolo observed the motion of runners moving slowly towards the starting corrals of the Chicago Marathon and then stopping as small groups began the race. With each movement, the authors identified waves in crowd density and velocity cascading from the front of the line. What's more, these waves traveled throughout the crowd at a constant speed. The dynamics were able to be predictively modeled in other races that the researchers evaluated, including in Paris and Atlanta. "The success of Bain and Bartolo's approach opens many avenues or future work for collective behavior researchers more generally," writes Nicholas Ouellette in a related Perspective. Ouellette says this work lays the foundation for an empirically grounded theory of group behavior.