A visual model of collective behavior in crowds

Dachner, Gregory Carter

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Year:: 2021
Contributor:: Dachner, Gregory Carter (creator); Warren, William (Advisor); Domini, Fulvio (Reader); Serre, Thomas (Reader); Brown University. Department of Cognitive, Linguistic, and Psychological Sciences (sponsor)
Genre:: theses
Subject:: Visual perception; agent-based models; Collective behavior
Extent:: xvii, 135 p.

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Abstract:: Abstract of A visual model of collective behavior in crowds, by Gregory C. Dachner, Ph.D., Brown University, May 2021. Collective motion in human crowds emerges from local interaction rules operating over a neighborhood. Most models of collective motion are based on the physical positions and velocities of others in a neighborhood of interaction. Previously we found a pedestrian matches the average heading direction and speed of neighbors, weighted by their distance: weights decay gradually to the nearest neighbor, and more rapidly in the crowd (PRSB 2018, CDPS 2018). In this work, I developed a visual model for collective motion, in which a pedestrian’s heading and speed are controlled by nulling the average angular velocity and optical expansion of neighbors, which are sinusoidal functions of eccentricity (VSS 2017, 2019). In Chapter 1, I lay the groundwork for the problem of visual information in collective following. Chapter 2 develops, fits, and tests a model with the given visual information. This work begins in this way so as to take a bottom-up approach, where once the interactions of a pedestrian and a single neighbor are understood, these rules can be generalized to multiple neighbors by the concept of superposition. Chapter 3 expands the model to include multiple neighbors (by the superposition of interactions) to account for collective motion and following a crowd. Chapter 4 experimentally tests whether neighbor occlusion influences following a crowd and then adds and tests this as a component to the model. Chapter 5 examines the model’s performance using multi-agent simulations of large crowds with varied initial conditions to test the robustness of the model for collective motion and to find novel predictions. Chapter 6 tests other sources of visual information that a pedestrian may use in a crowd. Finally, Chapter 7 concludes the dissertation by discussing the overarching themes found with visual information and following a crowd and outlining future work. Together, this work adds new insights into how visual information governs human crowds and provides an important theoretical advance in our understanding of collective motion.
Notes:: Thesis (Ph. D.)--Brown University, 2021

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Dachner, Gregory Carter, "A visual model of collective behavior in crowds" (2021). Cognitive, Linguistic, and Psychological Sciences Theses and Dissertations. Brown Digital Repository. Brown University Library. https://repository.library.brown.edu/studio/item/bdr:8y92n95s/

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Cognitive, Linguistic, and Psychological Sciences Theses and Dissertations

Theses and Dissertations for the Cognitive, Linguistic, and Psychological Sciences department.
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