3DGIS-based multi-agent geosimulation model for building evacuation - Macatulad, Edgardo G.
Geographic Information System (GIS) is one of the invaluable tools to study real world data, processes, and phenomena that are related to geographic locations. With the continuous development and advancement in digital and computing technology, more capabilities of analysing geospatial data and processes inside a GIS virtual environment become possible. Recent GIS applications and researches have already begun to extend spatial modeling, visualization and analysis from the traditional 2D and 2.5D environment to the 3D space. Through utilization of 3DGIS data and data models, indoor environments and spatial phenomena can be represented and analyzed through data representation in 3D, such as for building emergency response and evacuation systems. GIS though is oftentimes static, representing spatial data for a specific time. But since geospatial data and processes are in reality dynamic both spatially and temporally, we would want to utilize simulations and animations to address this limitation. Integrating 3DGIS with agent-based modeling (ABM), simulation models can be developed for more dynamic analysis of spatial data and processes. One such application is on building evacuation in which ABM can be integrated with 3D indoor spatial data to model human behavior during evacuation events and simulate evacuation scenarios visualized in 3D. In building evacuation planning, the goal is to evaluate the egress of building occupants in relation to the exit locations, the escape routes, and the corresponding egress times. The traditional approach utilizes drills which usually incur corresponding costs, disruption, and inconvenience. In this research, a 3DGIS-based multi-agent goe-simulation model for building evacuation model is developed, such that we can perform dynamic analyses of building evacuation through simulations fo different scenarios. The 3DGIS dataset of the Melchor Hall building in University of the Philippines Diliman (UPD) is used as input in ABM, through the GAMA simulation platform. This model is intended to be a complement to earthquake and fire drills. In the prototype model, PEOPLE agents are modeled to represent the building occupants. FLOORS, ROOMS, INDOOR_PATHS and EXIT_POINTS agents are modeled from the 3DGIS building layers and assigned their respective attributes. PEOPLE agents are placed in the ROOMS of the building, based on room capacity and actual student population referred to a crs_schedule value. A chance_panic attribute of the PEOPLE agent is checked this sets the agent to either panic or not. If the chance_panic value is true, the speed of the particular PEOPLE agent is multiplied by a value given by the variable panic_effect which is set in the initialization of the model. If the chance_panic value is false, the PEOPLE agent retains the base speed value of 0.83 m/s. Another attribute, the chance_knowledge_exit is then checked. If the chance_knowledge_exit value is true, the designated_exit attribute of the ROOMS where the PEOPLE agent is located is assigned as the target exit for that particular PEOPLE agent. If the chance_knowledge_exit value is false, the PEOPLE agent is programmed to select a random exit. PEOPLE agents will evacuate to their target EXIT_POINTS along the INDOOR_PATH. Their movement is affected by their chance_panic and chance_knowledge_exit attributes, as well as by weights applied to the INDOOR_PATH which is computed from the number of PEOPLE agents currently on the same INDOOR_PATH. Several building evacuation case scenarios are ran, including scenarios based on the student schedules, implementation of egress time limit, and using extreme building occupant count. The simulations can be implemented through GUI-based simulation experiments or batch simulation experiments. The resulting egress time for the different simulations can be computed and analyzed in order to look at the effects of changing the chance_panic and chance_knowledge_exit parameter values to the evacuation time of the PEOPLE agents. This kind of evacuation simulation model may be used not only to evaluate exits and egress routes for different scenarios, but also to repeat experiments when necessary, before implementing in actual drills. In the simulation results, it was noted that in general, the increase in chance_panic values resulted to an increase in the total egress time. Extreme values were obtained at chance_panic equal to 1 in which the movement speed of the PEOPLE agents greatly decreased the total egress time. It can also be noted in the total egress time results for the chance_panic equal to 1, the increase in chance_knowledge_exit could still further decrease the total egress time. Looking at the effect of the chance_knowledge_exit parameter, it can be seen that as this parameter is increased there is a decrease in the total egress time result, even if slightly. It can be seen though that at chance_knowledge_exit equal to 1, the increase in chance_panic would still contribute to increased total egress time. It can be concluded from the results that even if panicking PEOPLE are moving faster, it will be more efficient if they have knowledge of the exit. Likewise, even if PEOPLE have knowledge of exit, they can evacuate efficiently if they do not panic.