MCMC-based tracking and identification of leaders in groups

We present a novel framework for identifying and tracking dominant agents in groups. Our proposed approach relies on a causality detection scheme that is capable of ranking agents with respect to their contribution in shaping the system's collective behaviour based exclusively on the agents' observed trajectories. Further, the reasoning paradigm is made robust to multiple emissions and clutter by employing a class of recently introduced Markov chain Monte Carlo-based group tracking methods. Examples are provided that demonstrate the strong potential of the proposed scheme in identifying actual leaders in swarms of interacting agents and moving crowds. © 2011 IEEE.

Parallels between wind and crowd loading of bridges

Parallels between the dynamic response of flexible bridges under the action of wind and under the forces induced by crowds allow each field to inform the other.Wind-induced behaviour has been traditionally classified into categories such as flutter, galloping, vortex-induced vibration and buffeting. However, computational advances such as the vortex particle method have led to a more general picture where effects may occur simultaneously and interact, such that the simple semantic demarcations break down. Similarly, the modelling of individual pedestrians has progressed the understanding of human–structure interaction, particularly for large amplitude lateral oscillations under crowd loading. In this paper, guided by the interaction of flutter and vortexinduced vibration in wind engineering, a framework is presented, which allows various human–structure interaction effects to coexist and interact, thereby providing a possible synthesis of previously disparate experimental and theoretical results.