Integrated Evacuation Planning and Spatial Field Estimation Using Level-Set Based Guidance with Trajectory Reconfiguration

This work proposes mid-course trajectory reconfigurations for humans escaping hazardous environments in indoor surroundings as part of disaster management in civil infrastructures. Hazardous environments are interpreted as spatial fields such as carbon monoxide concentrations, and have accumulated effects on escaping humans within indoor environments. When the spatial field is known and available to an evacuee then a level-set based guidance can provide an optimal trajectory to an escape exit that corresponds to the smallest accumulated amount of hazardous material in the evacuee's lungs. However, when the spatial field is unknown to an evacuee, an integrated estimation and trajectory planning scheme is warranted. This paper combines the asymptotic embedding approach for state estimation of spatially distributed processes via mobile sensor with a modified level-set trajectory generation scheme. Incorporating realism due to computing and planning time, a trajectory cycle is decomposed into a planning stage in which a mobile agent (human) is immobile and uses the most recent state estimate to generate viable escape trajectories, and the travel stage in which the mobile agent is executing the trajectory computed during the planning stage. As new process state information is updated, the escape trajectories are recalculated thereby leading to continuous escape trajectory reconfiguration. In both stages of a given cycle the mobile agent is continuously estimating the spatially distributed process but only using the most recent snapshot of the spatial process estimate for trajectory recalculation. Extensive numerical studies are included to shed light on the detrimental effects of accumulated amounts of hazardous environments on the escape trajectories of humans during indoor evacuation.