EvacSafeX: A Multi-Agent Model for Aircraft Evacuation Simulation

Abstract

Throughout the last decades, several simulation models have been proposed in an attempt to reproduce aircraft evacuation scenarios and provide an alternative to real certi cation trials. Furthermore, simulation models have been proven to be a useful tool when designing new aircraft enclosures. Among these, the airEXODUS model has seen widespread application and validation, being successful in predicting past certi cation trials and examining issues related to aircraft enclosure layout. This work introduces EvacSafeX, a multi-agent model centered around proper representation of human behaviour in aircraft evacuation scenarios. EvacSafeX nds its inspiration in complex systems and in the airEXODUS model, seeking to make complex interactions and behaviour emergence from individual modeling of human passengers. The model also takes novel approaches to represent human behaviour and passengers movement along the aircraft cabin. EvacSafeX adopts a perception-action approach to represent agent's capabilities, following a behavioral model de ned by a rule list brain. Passengers are also characterised by both physical and psychological attributes identi ed as the most relevant in evacuation scenarios. In addition to the many components already included in the model, its generic architecture allows other ones to be easily incorporated. The components implemented beforehand in EvacSafeX prototype were veri ed through a set of validation experiments. At rst sight, it was observed a signi cant sensitivity of some passenger's personal attributes, representative of their in uence in real life cases. Furthermore, the proposed model demonstrated a high exibility and diversity in the representation of passenger's behaviour, leading to an emergence of several di erent phenomena observed in real evacuation scenarios. Finally, promising results were obtained in an attempt to reproduce real certi cation demonstrations results and other experiments conducted with state of the art models.