Walking Through a Crowd: Modeling Pedestrian Collision Avoidance Behavior

Veprek, Kyra

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Overview

Year:: 2023
Contributor:: Veprek, Kyra (creator); Warren, William (Advisor); Brown University. Department of Cognitive, Linguistic, and Psychological Sciences (sponsor)
Genre:: theses
Subject:: Virtual reality; perception and action; Pedestrians
Extent:: 3, 38 p.

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Description

Abstract:: Walking on our daily commutes, we encounter dozens of other pedestrians but rarely do we collide with them. Previous omniscient collision avoidance models assume 3D positions and velocities are known and predict the trajectories of all obstacles, which is not biologically plausible. Previous researchers developed a visual model that accurately predicts human collision avoidance of a single moving obstacle, based on the change in its bearing direction and visual angle. Here we test the model on avoiding single or multiple walking pedestrians. Participants walked to a goal at 7m while avoiding moving avatars presented in a head-mounted display. Experiment 1 (N=12) compared the avoidance of a moving pole and a walking avatar. The obstacle moved on a linear path at different angles (180°, ±157.5°, ±135°, ±112.5°, ±90° to the participant’s path) and speeds (1.0, 1.2 m/s), and the participant’s head position was recorded. There was no difference in trajectories around a pole and an avatar, which the model predicted equally well. The model thus generalizes from avoiding inanimate obstacles to avoiding walking pedestrians. In Experiment 2 , participants walked through a crowd of 16 avatars, which moved at the same speed (1.0 m/s) in a common direction (same angles as before). We compare the performance of models that avoid avatars closer than 4m or avoid avatars that exceed a visual threshold for optical expansion and bearing change. Together, the results demonstrate that a visual collision avoidance model with a single moving obstacle generalizes to avoiding multiple collisions when walking through a crowd.
Notes:: Thesis (Sc. M.)--Brown University, 2023

Content

Citation

Veprek, Kyra, "Walking Through a Crowd: Modeling Pedestrian Collision Avoidance Behavior" (2023). Cognitive, Linguistic, and Psychological Sciences Theses and Dissertations. Brown Digital Repository. Brown University Library. https://repository.library.brown.edu/studio/item/bdr:vvuavd9e/

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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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