Literature DB >> 24511143

Follow the leader: visual control of speed in pedestrian following.

Kevin W Rio1, Christopher K Rhea, William H Warren.   

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.

Entities:  

Keywords:  crowd dynamics; locomotion; pedestrian model; visual control

Mesh:

Year:  2014        PMID: 24511143      PMCID: PMC3919103          DOI: 10.1167/14.2.4

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  23 in total

1.  Novel type of phase transition in a system of self-driven particles.

Authors: 
Journal:  Phys Rev Lett       Date:  1995-08-07       Impact factor: 9.161

2.  Optical information for car following: the driving by visual angle (DVA) model.

Authors:  George J Andersen; Craig W Sauer
Journal:  Hum Factors       Date:  2007-10       Impact factor: 2.888

3.  Social force model for pedestrian dynamics.

Authors: 
Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics       Date:  1995-05

4.  Visuo-motor delay, information-movement coupling, and expertise in ball sports.

Authors:  Cyrille Le Runigo; Nicolas Benguigui; Benoit G Bardy
Journal:  J Sports Sci       Date:  2010-02       Impact factor: 3.337

5.  Endpoint error in smoothing and differentiating raw kinematic data: an evaluation of four popular methods.

Authors:  P F Vint; R N Hinrichs
Journal:  J Biomech       Date:  1996-12       Impact factor: 2.712

6.  Necessary conditions for the perception of motion in depth.

Authors:  D Regan; C J Erkelens; H Collewijn
Journal:  Invest Ophthalmol Vis Sci       Date:  1986-04       Impact factor: 4.799

7.  Binocular and monocular stimuli for motion in depth: changing-disparity and changing-size feed the same motion-in-depth stage.

Authors:  D Regan; K I Beverley
Journal:  Vision Res       Date:  1979       Impact factor: 1.886

8.  Properties of pedestrians walking in line. II. Stepping behavior.

Authors:  Asja Jelić; Cécile Appert-Rolland; Samuel Lemercier; Julien Pettré
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2012-10-31

9.  Interaction with an immersive virtual environment corrects users' distance estimates.

Authors:  Adam R Richardson; David Waller
Journal:  Hum Factors       Date:  2007-06       Impact factor: 2.888

10.  Behavioral dynamics of intercepting a moving target.

Authors:  Brett R Fajen; William H Warren
Journal:  Exp Brain Res       Date:  2007-02-02       Impact factor: 2.064

View more
  12 in total

1.  Collective Motion in Human Crowds.

Authors:  William H Warren
Journal:  Curr Dir Psychol Sci       Date:  2018-07-11

2.  How cognitive heuristics can explain social interactions in spatial movement.

Authors:  Michael J Seitz; Nikolai W F Bode; Gerta Köster
Journal:  J R Soc Interface       Date:  2016-08       Impact factor: 4.118

3.  Effects of visual information on decision making during way-finding in emergency and non-emergency situations.

Authors:  Gregory C Dachner; Max Kinateder
Journal:  Collect Dyn       Date:  2016

4.  Local interactions underlying collective motion in human crowds.

Authors:  Kevin W Rio; Gregory C Dachner; William H Warren
Journal:  Proc Biol Sci       Date:  2018-05-16       Impact factor: 5.349

5.  Quantifying and Modeling Coordination and Coherence in Pedestrian Groups.

Authors:  Adam W Kiefer; Kevin Rio; Stéphane Bonneaud; Ashley Walton; William H Warren
Journal:  Front Psychol       Date:  2017-06-28

6.  Hypernetworks Reveal Compound Variables That Capture Cooperative and Competitive Interactions in a Soccer Match.

Authors:  João Ramos; Rui J Lopes; Pedro Marques; Duarte Araújo
Journal:  Front Psychol       Date:  2017-08-28

7.  Intercepting a moving target: On-line or model-based control?

Authors:  Huaiyong Zhao; William H Warren
Journal:  J Vis       Date:  2017-05-01       Impact factor: 2.240

8.  Timing and correction of stepping movements with a virtual reality avatar.

Authors:  Omar Khan; Imran Ahmed; Joshua Cottingham; Musa Rahhal; Theodoros N Arvanitis; Mark T Elliott
Journal:  PLoS One       Date:  2020-02-28       Impact factor: 3.240

9.  Decoding collective communications using information theory tools.

Authors:  K R Pilkiewicz; B H Lemasson; M A Rowland; A Hein; J Sun; A Berdahl; M L Mayo; J Moehlis; M Porfiri; E Fernández-Juricic; S Garnier; E M Bollt; J M Carlson; M R Tarampi; K L Macuga; L Rossi; C-C Shen
Journal:  J R Soc Interface       Date:  2020-03-18       Impact factor: 4.118

10.  Nonverbal leadership emergence in walking groups.

Authors:  Maria Lombardi; William H Warren; Mario di Bernardo
Journal:  Sci Rep       Date:  2020-11-03       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.