Follow the leader: Visual control of speed in pedestrian following

Abstract

When people walk together in groups or crowds they must coordinate their walking speed and direction with their neighbors. This paper investigates how a pedestrian visually controls speed when following a leader on a straight path (one-dimensional following). To model the behavioral dynamics of following, participants in Experiment 1 walked behind a confederate who randomly increased or decreased his walking speed. The data were used to test six models of speed control that used the leader's speed, distance, or combinations of both to regulate the follower's acceleration. To test the optical information used to control speed, participants in Experiment 2 walked behind a virtual moving pole, whose visual angle and binocular disparity were independently manipulated. The results indicate the followers match the speed of the leader, and do so using a visual control law that primarily nulls the leader's optical expansion (change in visual angle), with little influence of change in disparity. This finding has direct applications to understanding the coordination among neighbors in human crowds.

The Visual Coupling between Neighbors in Real and Virtual Crowds

“…The understanding of collective behavior has been advanced tremendously by theoretical models and largescale simulations, but there is a growing consensus that this effort must be informed by rigorous observational and experimental studies to specify the local rules or control laws that give rise to global phenomena. Driven in part by recent advances in tracking technologies, there is a rising tide of data-driven approaches to collective behavior, including work on fish schools (Ward et al (2008)), bird flocks (Ballerini et al (2008); Cavagna et al (2010)), as well as pedestrian behavior (Moussaid et al (2009) ;Lemercier et al (2012); Rio et al (2014)) and crowd dynamics (Moussaid et al (2010); Bonneaud et al (2012)) in humans. Data can be utilized in many ways, from calibrating the parameters of proposed models (Johansson et al (2007)) to identifying the information individual agents utilize to guide behavior (Ballerini, et al (2008)).…”

“…Previously, we have advocated for an experimental approach to collective behavior that begins by developing dynamical models of simple pedestrian inte and Warren (2003) and Warren (2007); Rio et al (2014)), extends them to more complex scenarios (Kiefer et al (2013)), and ultimately uses them to predict patterns of crowd dynamics (Bonneaud et al (2014)). We recently showed that a pedestrian follows a neighbor by matching the leader's speed and heading direction, based on visual information ; Dachner and Warren (2014)).…”

Emergent complexity matching in interpersonal coordination: Local dynamics and global variability.

“…A useful illustration of these concepts is found in a study on inter personal leader-follower coordination during locomotion. Rio et al (2014) demonstrated that following speed is likely controlled by a simple control law: Followers matched leader walking speed by minimizing the change in optical angle subtended by the leader at the follower's eye. This model was accurate even with random changes in leader speed.…”

How cognitive heuristics can explain social interactions in spatial movement

“…Specifically, spatial movement and social interactions play an important role in the context of pedestrian dynamics. Perceptual motor-control models can be used to describe individual steering behaviour, including collision avoidance [5][6][7]. Social interactions have been successfully studied with individual-based simulation models [8,9], which typically have a set of behavioural rules or equations of motion and are studied by varying the model's parameters to explore differences in behaviour.…”