A framework for achieving realism in agent-based pedestrian crowd simulations

Alexander Fuchsberger, Nargess Tahmasbi, Brian Ricks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Pedestrian crowd simulations are used to predict the behavior of human crowds. Decision makers, however, often feel crowd simulations look mechanized and do not accurately reflect the motion of real crowds. Thus, current research focuses less on computational efficiency and more on improving simulation realism. In this conceptual work, we analyze recent, major contributions in the computer science field to identify current endeavors in crowd simulation research that lead to increased realism. We provide a framework that can be used to identify components in agent-based crowd simulations that contribute towards realism. External and internal factors influence the realism of any crowd simulation. We show that crowd simulations typically address environmental, situational and physiological factors. Agents however are rarely implemented to also consider psychological and cultural factors. As a result, the realism and therefore model accuracy and trustworthiness of crowd simulations is undermined.

Original languageEnglish (US)
Title of host publicationAMCIS 2017 - America's Conference on Information Systems
Subtitle of host publicationA Tradition of Innovation
PublisherAmericas Conference on Information Systems
Volume2017-August
ISBN (Electronic)9780996683142
StatePublished - Jan 1 2017
EventAmerica�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017 - Boston, United States
Duration: Aug 10 2017Aug 12 2017

Other

OtherAmerica�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017
CountryUnited States
CityBoston
Period8/10/178/12/17

Fingerprint

Computational efficiency
Computer science

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications

Cite this

Fuchsberger, A., Tahmasbi, N., & Ricks, B. (2017). A framework for achieving realism in agent-based pedestrian crowd simulations. In AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation (Vol. 2017-August). Americas Conference on Information Systems.
Fuchsberger, Alexander ; Tahmasbi, Nargess ; Ricks, Brian. / A framework for achieving realism in agent-based pedestrian crowd simulations. AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation. Vol. 2017-August Americas Conference on Information Systems, 2017.
@inproceedings{9bc493698dff411abdde92e691fb9650,
title = "A framework for achieving realism in agent-based pedestrian crowd simulations",
abstract = "Pedestrian crowd simulations are used to predict the behavior of human crowds. Decision makers, however, often feel crowd simulations look mechanized and do not accurately reflect the motion of real crowds. Thus, current research focuses less on computational efficiency and more on improving simulation realism. In this conceptual work, we analyze recent, major contributions in the computer science field to identify current endeavors in crowd simulation research that lead to increased realism. We provide a framework that can be used to identify components in agent-based crowd simulations that contribute towards realism. External and internal factors influence the realism of any crowd simulation. We show that crowd simulations typically address environmental, situational and physiological factors. Agents however are rarely implemented to also consider psychological and cultural factors. As a result, the realism and therefore model accuracy and trustworthiness of crowd simulations is undermined.",
author = "Alexander Fuchsberger and Nargess Tahmasbi and Brian Ricks",
year = "2017",
month = "1",
day = "1",
language = "English (US)",
volume = "2017-August",
booktitle = "AMCIS 2017 - America's Conference on Information Systems",
publisher = "Americas Conference on Information Systems",

}

Fuchsberger, A, Tahmasbi, N & Ricks, B 2017, A framework for achieving realism in agent-based pedestrian crowd simulations. in AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation. vol. 2017-August, Americas Conference on Information Systems, America�s Conference on Information Systems: A Tradition of Innovation, AMCIS 2017, Boston, United States, 8/10/17.

A framework for achieving realism in agent-based pedestrian crowd simulations. / Fuchsberger, Alexander; Tahmasbi, Nargess; Ricks, Brian.

AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation. Vol. 2017-August Americas Conference on Information Systems, 2017.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - A framework for achieving realism in agent-based pedestrian crowd simulations

AU - Fuchsberger, Alexander

AU - Tahmasbi, Nargess

AU - Ricks, Brian

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Pedestrian crowd simulations are used to predict the behavior of human crowds. Decision makers, however, often feel crowd simulations look mechanized and do not accurately reflect the motion of real crowds. Thus, current research focuses less on computational efficiency and more on improving simulation realism. In this conceptual work, we analyze recent, major contributions in the computer science field to identify current endeavors in crowd simulation research that lead to increased realism. We provide a framework that can be used to identify components in agent-based crowd simulations that contribute towards realism. External and internal factors influence the realism of any crowd simulation. We show that crowd simulations typically address environmental, situational and physiological factors. Agents however are rarely implemented to also consider psychological and cultural factors. As a result, the realism and therefore model accuracy and trustworthiness of crowd simulations is undermined.

AB - Pedestrian crowd simulations are used to predict the behavior of human crowds. Decision makers, however, often feel crowd simulations look mechanized and do not accurately reflect the motion of real crowds. Thus, current research focuses less on computational efficiency and more on improving simulation realism. In this conceptual work, we analyze recent, major contributions in the computer science field to identify current endeavors in crowd simulation research that lead to increased realism. We provide a framework that can be used to identify components in agent-based crowd simulations that contribute towards realism. External and internal factors influence the realism of any crowd simulation. We show that crowd simulations typically address environmental, situational and physiological factors. Agents however are rarely implemented to also consider psychological and cultural factors. As a result, the realism and therefore model accuracy and trustworthiness of crowd simulations is undermined.

UR - http://www.scopus.com/inward/record.url?scp=85048435221&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85048435221&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:85048435221

VL - 2017-August

BT - AMCIS 2017 - America's Conference on Information Systems

PB - Americas Conference on Information Systems

ER -

Fuchsberger A, Tahmasbi N, Ricks B. A framework for achieving realism in agent-based pedestrian crowd simulations. In AMCIS 2017 - America's Conference on Information Systems: A Tradition of Innovation. Vol. 2017-August. Americas Conference on Information Systems. 2017