TY - JOUR
T1 - Crowd simulation for emergency response using BDI agents based on immersive virtual reality
AU - Shendarkar, Ameya
AU - Vasudevan, Karthik
AU - Lee, Seungho
AU - Son, Young Jun
N1 - Funding Information:
This work was supported by Air Force Office of Scientific Research under AFOSR/MURI F49620-03-1-0377 and National Institute of Standards and Technology Grant under SB1341-05-W-0852.
PY - 2008/10
Y1 - 2008/10
N2 - This paper presents a novel methodology involving a Virtual Reality (VR)-based Belief, Desire, and Intention (BDI) software agent to construct crowd simulation and demonstrates the use of the same for crowd evacuation management under terrorist bomb attacks in public areas. The proposed BDI agent framework allows modeling of human behavior with a high degree of fidelity. The realistic attributes that govern the BDI characteristics of the agent are reverse-engineered by conducting human-in-the-loop experiments in the VR-based Cave Automatic Virtual Environment (CAVE). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes (e.g., maps, demographics, evacuation management parameters). The validity of the proposed data models are tested with two different evacuation scenarios. Finally, experiments are conducted to demonstrate the effect of various crowd evacuation management parameters on the key performance indicators in the evacuation scenario such as crowd evacuation rate and densities. The results reveal that constructed simulation can be used as an effective emergency management tool.
AB - This paper presents a novel methodology involving a Virtual Reality (VR)-based Belief, Desire, and Intention (BDI) software agent to construct crowd simulation and demonstrates the use of the same for crowd evacuation management under terrorist bomb attacks in public areas. The proposed BDI agent framework allows modeling of human behavior with a high degree of fidelity. The realistic attributes that govern the BDI characteristics of the agent are reverse-engineered by conducting human-in-the-loop experiments in the VR-based Cave Automatic Virtual Environment (CAVE). To enhance generality and interoperability of the proposed crowd simulation modeling scheme, input data models have been developed to define environment attributes (e.g., maps, demographics, evacuation management parameters). The validity of the proposed data models are tested with two different evacuation scenarios. Finally, experiments are conducted to demonstrate the effect of various crowd evacuation management parameters on the key performance indicators in the evacuation scenario such as crowd evacuation rate and densities. The results reveal that constructed simulation can be used as an effective emergency management tool.
KW - Agent-based simulation
KW - CAVE
KW - Crowd simulation
KW - Emergency response management
KW - Shortest path algorithm
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U2 - 10.1016/j.simpat.2008.07.004
DO - 10.1016/j.simpat.2008.07.004
M3 - Article
AN - SCOPUS:53349146619
SN - 1569-190X
VL - 16
SP - 1415
EP - 1429
JO - Simulation Modelling Practice and Theory
JF - Simulation Modelling Practice and Theory
IS - 9
ER -