Agent architecture for crowd simulation in indoor environments
Authored by Juan Pavon, Rafael Pax
Date Published: 2017
DOI: 10.1007/s12652-016-0420-1
Sponsors:
European Union
Platforms:
Java
MASON
MASSIS
Model Documentation:
Other Narrative
Flow charts
Mathematical description
Model Code URLs:
https://github.com/rpax/MASSIS
Abstract
Simulation of crowds demands coping with scalability and performance
issues that are not usually well supported by general purpose agent
based simulation toolkits. On the other side, the use of agent models
provides a great degree of flexibility in the specification of the
behaviour of the entities and their interactions. The agent architecture
that is presented in this work addresses both types of requirements, by
taking advantage of the characteristics of its specific problem domain:
the simulation of crowds in indoor environments. Several algorithms are
implemented to improve the efficiency of the management of a high number
of agents in order to cope with the performance in the processing of
their movements and their representation. At the same time, different
models are supported to specify decision making of the agents in order
to allow rich behaviours. Agents can represent different types of
entities such as people, sensors and actuators. This is illustrated with
a realistic case study of the evacuation of the building of our Faculty
of Computer Science, where different types of human behaviours are
modelled in this kind of situations.
Tags
Agent based modelling
Crowd simulation
Ambient intelligence
Indoor
scenarios
Massis