Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Approximating probabilistic inference in Bayesian belief networks is NP-hard
Artificial Intelligence
Induction of fuzzy decision trees
Fuzzy Sets and Systems
Crowd simulation in immersive space management
Proceedings of the Eurographics workshop on Virtual environments and scientific visualization '96
Modeling Individual Behaviors in Crowd Simulation
CASA '03 Proceedings of the 16th International Conference on Computer Animation and Social Agents (CASA 2003)
Capturing the quake player: using a BDI agent to model human behaviour
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Simulation with Arena
Method of crowd simulation by using multiagent on cellular automata
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
Tutorial on agent-based modeling and simulation
WSC '05 Proceedings of the 37th conference on Winter simulation
A concept prototype for integrated gaming and simulation for incident management
Proceedings of the 38th conference on Winter simulation
Efficient agent-based simulation framework for multi-node supercomputers
Proceedings of the 38th conference on Winter simulation
A comparative study of assembly planning in traditional and virtualenvironments
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
| Hi-index | 0.00 |
Manufacturing facilities are expected to maintain a high level of production and at the same time, employ strict safety standards to ensure the safe evacuation of the people in the event of emergencies (fire is considered in this paper). These two goals are often conflicting. This paper presents a methodology to evaluate evacuation safety versus productivity concurrently for various, widely known manufacturing layouts. While the safety performance indicators such as evacuation times are inferred from the crowd (agent based) simulation, the productivity performance indicators (e.g. throughput) are analyzed using the discrete event simulation. To this end, this research focuses on creating innovative techniques for developing accurate crowd simulations, where Belief-Desire-Intention (BDI) agent framework is employed to build each person's individual actions and the interactions between them. The data model and rule based action algorithms for each agent are reverse-engineered from the human-in-the-loop experiments in the immersive virtual reality environments. Finally, experiments are conducted using the constructed simulations to compare safety and productivity for different layouts. To demonstrate the proposed methodology, an automotive power-train (engine and transmission) manufacturing plant was used. Initial results look quite promising.