Simulating collective motion from particles to birds

Abstract

The main work of this thesis is the construction of a 3D computer model of animal flocking based on vision. The model took an additional input, to those usually considered in tradition models: the projection of all other flock members on to an individual's field of view. Making 2D models is easy (in fact 4 new ones are included in this thesis), but we should be drawing parallels with experimental data for behaviour in animal systems and we should be cautious indeed when drawing conclusions, based on those models. It is common in the literature not to compare model behaviours with measurable quantities of natural flocks. However this work makes a concerted effort to do so in the case of the 3D model. A direct comparison was made in this work between the simulations and an empirical study of starling flocks, of the scaling behaviour of the maximum distance through the flock and the number of flock members, for which the agreement was very good. Other flock properties were compared with the natural flocks, but with less satisfactory results. A careful literature survey was made to investigate and ultimately support the biological plausibility of the 3D projection model. Biological and physiological plausibility is a factor not often considered by computational modellers. A series of novel and related 2D computer flocking models were investigated with hopes to find a single flocking rule that could manifest the most important features of collective motion and thereby be highly parsimonious. The final part of this thesis concerns a 2D computer model of photothermophoresis based on langevin dynamics, which it may be possible to use to find evidence of a density transition found in the continuum model. There was some evidence that a transition from a transparent diffuse state to an opaque compact one may exist for the discrete particle simulation