How vision governs the collective behaviour of dense cycling pelotons

Abstract

In densely packed groups demonstrating collective behaviour, such as bird flocks, fish schools or packs of bicycle racers (cycling pelotons), information propagates over a network, with individuals sensing and reacting to stimuli over relatively short space and time scales. What remains elusive is a robust, mechanistic understanding of how sensory system properties affect interactions, information propagation and emergent behaviour. Here, we show through direct observation how the spatio-temporal limits of the human visual sensory system govern local interactions and set the network structure in large, dense collections of cyclists. We found that cyclists align in patterns within a ± 30° arc corresponding to the human near-peripheral visual field, in order to safely accommodate motion perturbations. Furthermore, the group structure changes near the end of the race, suggesting a narrowing of the used field of vision. This change is consistent with established theory in psychology linking increased physical exertion to the decreased field of perception. Our results show how vision, modulated by arousal-dependent neurological effects, sets the local arrangement of cyclists, the mechanisms of interaction and the implicit communication across the group. We furthermore describe information propagation phenomena with an analogous elastic solid mechanics model. We anticipate our mechanistic description will enable a more detailed understanding of the interaction principles for collective behaviour in a variety of animals.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 01, 2019
Source ID
10.1098/rsif.2019.0197

Entities

People

  • Andrew Meyer
  • Aren Hellum
  • Craig M. Pease
  • Jesse Belden
  • Jesús Pacheco
  • M. M. Mansoor
  • S. Koziol
  • S. R. Rahman
  • Tadd T Truscott

Organizations

  • Baylor University
  • Massachusetts Institute of Technology
  • Naval Undersea Warfare Center
  • Office of Naval Research
  • Utah State University

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Exercise and Sports Science.
  • Materials Science and Engineering.

Technology Areas

  • Space