Modelling the evolution of human trail systems

Abstract

Many human social phenomena, suchh as cooperation [1][2][3], the growth of settlements [4], traffic dynamics [5][6][7] and pedestrian movement [7][8][9][10], appear to be accessible to mathematical descriptions that invoke self-organization [11,12]. Here we develop a model of pedestrian motion to explore the evolution of trails in urban green spaces such as parks. Our aim is to address such questions as what the topological structures of these trail systems are [13], and whether optimal path systems can be predicted for urban planning. We use an 'active walker' model [14][15][16][17][18][19] that takes into account pedestrian motion and orientation and the concomitant feedbacks with the surrounding environment. Such models have previously been applied to the study of complex structure formation in physical [14][15][16], chemical [17] and biological [18,19] systems. We find that our model is able to reporduce many of the observed large-scale spatial features of trail systems.

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

“…• Trail formation: Although human and animal trails are formed for rather different purposes their structures have some similarities [20,21]. Often human trails are formed as a short-cut which makes it attractive to leave a paved path.…”

Absence of jamming in ant trails: Feedback control of self-propulsion and noise

“…Formation of these trails have been described theoretically in terms of active-walker models. The mechanism is ubiquitous in nature and similar to river basin formation [17], formation of pedestrian trails [18,19], and formation of axon bundles in mammalian sensory neurons [20,21].…”

Collective behavior of interacting self-propelled particles

“…As the motion of flocking organisms is usually controlled by interactions with their neighbors [1], the SPP models consist of locally interacting particles with an intrinsic driving force, hence with a finite steady velocity. Because of their simplicity, such models represent a statistical approach complementing other studies which take into account more details of the actual behavior [6,9,10], but treat only a moderate number of organisms and concentrate less on the large scale behavior.…”