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Proceedings Paper

iCrowd: agent-based behavior modeling and crowd simulator
Author(s): Vassilios I. Kountouriotis; Manolis Paterakis; Stelios C. A. Thomopoulos
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Paper Abstract

Initially designed in the context of the TASS (Total Airport Security System) FP-7 project, the Crowd Simulation platform developed by the Integrated Systems Lab of the Institute of Informatics and Telecommunications at N.C.S.R. Demokritos, has evolved into a complete domain-independent agent-based behavior simulator with an emphasis on crowd behavior and building evacuation simulation. Under continuous development, it reflects an effort to implement a modern, multithreaded, data-oriented simulation engine employing latest state-of-the-art programming technologies and paradigms. It is based on an extensible architecture that separates core services from the individual layers of agent behavior, offering a concrete simulation kernel designed for high-performance and stability. Its primary goal is to deliver an abstract platform to facilitate implementation of several Agent-Based Simulation solutions with applicability in several domains of knowledge, such as: (i) Crowd behavior simulation during [in/out] door evacuation. (ii) Non-Player Character AI for Game-oriented applications and Gamification activities. (iii) Vessel traffic modeling and simulation for Maritime Security and Surveillance applications. (iv) Urban and Highway Traffic and Transportation Simulations. (v) Social Behavior Simulation and Modeling.

Paper Details

Date Published: 17 May 2016
PDF: 11 pages
Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98420Q (17 May 2016); doi: 10.1117/12.2223109
Show Author Affiliations
Vassilios I. Kountouriotis, National Ctr. for Scientific Research Demokritos (Greece)
Manolis Paterakis, National Ctr. for Scientific Research Demokritos (Greece)
Stelios C. A. Thomopoulos, National Ctr. for Scientific Research Demokritos (Greece)

Published in SPIE Proceedings Vol. 9842:
Signal Processing, Sensor/Information Fusion, and Target Recognition XXV
Ivan Kadar, Editor(s)

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