A Modelling Approach To Human Navigation in Constrained Spaces

In this thesis, we consider algorithms and systems which dynamically guide evacuees towards exits during an emergency to minimise building evacuation time. We observe that the “shortest safe path” routing approach is inadequate when congestion is a predominant factor, and therefore focus on systems which manage congestion. We first implement a “Reactive” metric which compares paths based on real-time transit times. We find that regular route corrections must be issued to address the constant changes in path delays, and that routes oscillate. We also implement a model-based “Proactive” metric which forecasts the increase in future congestion that results from every routing decision, allowing the routing algorithm to operate offline. We combine both metrics with the Cognitive Packet Network (CPN), a distributed selfaware routing algorithm which uses neural networks to efficiently explore the building graph. We also present the first thorough sensitivity analysis on CPN’s parameters, and use this to tune CPN for optimal performance. We then compare the proactive and reactive approaches through simulation and find both approaches reduce building evacuation times – especially when evacuees are not evenly distributed in the building. We also find major differences between the Proactive and Reactive approach, in terms of stability, flexibility, sensory requirements, etc. Finally, we consider guiding evacuees using dynamic exit signs, whose pointing direction can be controlled. Dynamic signs can readily be used with Reactive routing, but since Proactive routing issues routes on an individual basis, one display is required for each evacuee. This is incompatible with dynamic signs; therefore we propose a novel algorithm which controls the dynamic signs according to the Proactive algorithm’s output. We simulate both systems, compare their performance, and review their practical limitations. For both approaches, we find that updating the sign’s display more often improves performance, but this may reduce evacuee compliance and make the system inefficient in real-life conditions.