Results

this research proposal paper has presented a holistic framework that attempts to address all emergency evaluation aspects and that facilitates the reuse, extension and interconnection of its major componentsThe paper has also described the methodological framework required for this novel combination of technologies, which emphasizes the integration of previous works and the diffusion of each little advance in the construction of this holistic framework.

We presented a robust, modular algorithm for context-based urban terrain modeling from sensor data. Except for the choice of parameter values and integration of additional sources of information, the algorithm is automatic and requires only a 2.5D elevation map as input.The elevation map may stem from an airborne laser scan or may be computed by a dense matching algorithm

Multiple GuidelinesDesign guidelines for synthesis support toolsSynthesis strategiesOur research provides an initial examination of part of the geovisualization research process that has until now had little attention. The results of our experiments show that synthesis conducted in the individual realm is an intricate and varied activity.

Simulation results from the demonstration indicate that occupant’s exit preferences, visual perception of the signage system, herding behavior, and social behavior among groups can lead to very different reactions to cues.The first test studies the effect of additional exit signs on evacuation performance. The total evacuation time is 165 s (averaged over 10 simulation runs). As highlighted in the figure, in this initial exit sign arrangement, agents take detours and explore the floor before find their way to exit. With additional exit signs posted, the agents travel with more direct routes and the evacuation time takes 119 s (a decrease of 28 % in time compared to that of initial layout of fewer exit signs).The second test illustrates how changing the exit orientation can help direct crowd flow. With the sign arrangement in the first test case, agents tend to exit through the main entrance and cause the congestions at the main entrance. With the proper exit orientation, more agents perceived the exit sign and its direction and evacuated through the near exit. Consequently, the evacuation time is 89 s, a further improvement of 25 %. During the simulation, the agents query the spatial model with the known exits and retrieve the shortest paths to the known exits. At the decision making stage, the agents choose to move to the visible navigation points along the shortest paths to get to their known exits.During evacuation, members belonging to a group, such as families and close friends, concerned the safety of their group members and often seek out and evacuate with the entire group even when evacuation is urgent. Often, as opposed to moving toward familiar exits, people may follow social cues and choose the exits preferred by the crowd as they observe others’ actions. We model the ‘‘following the crowd’’ behavior as follows: during the simulation, the herding agent (who is seeking to follow other agents) perceives the space and detects visible floor objects. At the decision-making stage, the herding agent assesses, for each visible floor object, the number of neighbors who are traveling toward the floor object. The herding agent chooses the visible floor object with the highest number of neighboring agents traveling toward because the agent considers the movement of its neighbors as a social cue to explore potential areas for exits. If there are no visible floor objects that other agents move to, the agent then will adopt other navigation strategies, such as referring to their known exits or following the visual cues.

In the case of big events, task force units must be located nearby the event area to ensure safety and help. In this paper, first it was revealed how the number of required task force units is usually determined in Germany. It is realized that very rough estimates are used. Where to locate these task force units best is mainly done by experience of the decision maker. Herewith it was developed mathematical models to give a better decision support in such situations. Basically, three problems were discussed: (1) How many task force units are needed and where to locate them, (2) given a limited number of task force units, where should they be located to cover the event area best to ensure help in a predefined response time, and (3) given a limited number of task force units, where should they be located to cover the event area with a shortest possible response time until help. In addition we discussed the problem of relocating task force units. Although, besides the relocation problem, all these problems are theoretically hard to optimize, computational studies revealed that instances of practical relevance can be solved optimally in short time using standard software. Eventually, we have shown that our approach provides decision support for a real-world case from the city of Dresden where 50000 people gathered together.

It was shown that more knowledge about environment dynamics leads to better service in both homogenous and heterogeneous cases. With decreasing the gap between knowledge acquisition about the environmental dynamics (flood and traffic) from first to fourth scenario we observe increase of a number of successfully escaped agents. It was shown that the knowledge sharing between agents can be a good alternative to the navigation system acquiring knowledge about the environment from a lot of sensors.

When tabletop exercises are constructed with the same formality as computer simulations, there are numerous benefits. Fewer erroneous assertions can be anticipated. Distinct aspects of the system can, once recognized by modeling, be stressed independently to evaluate the multiple facets of workforce response to disaster challenges. Performance measurements, as a formality introduced by simulation modeling, provides metrics by which readiness for disaster may be gauged and status quantified, progress monitored or alternatives compared.

To sum, it is found that the merge flow ratio influences sequence of floors to be evacuated and time required for complete evacuation when coefficient of flow rate and velocity of walking remained a constant. It consumes least time for total evacuation when merge flow ratio R is equal to 1. The occupants of the lower floors finish evacuation sooner when R is less than 1. The occupants of the higher floors arrive at safe areas sooner when R is more than 1, which is similar to NFPA method. The simulation results are also illustrated that with same walking speed value, the influence of coefficient of specific exit flow and specific stair flow is obvious. The higher the coefficient value, the shorter the total evacuation time is. When stagnation happened in the floors, increasing walking speed do not influence much in shortening the evacuation time.

The results indicate that key informants were highly confident in their workforces’ efficacy, ability, willingness, and motivation to directly engage local communities in Environmental Health Emergency Preparedness.

The multi-emergency rescue dynamic allocation model that is proposed herewith considers the dynamic nature that the casualties of trapped victims change over time. The model for the allocation of rescue resources maximizes the overall emergency rescue effectiveness of rescue proposal of the allocated and the unallocated resources at each stage during the planning period, and allows for the cost of allocation resources. Considering the purchasing cost, inventory cost, and opportunity loss cost during the cost objectives construction, the proposed method combines ideal point method and unit cost utility method to solve the allocation model by utilizing the LINGO software. Numerical examples to test the model and its algorithm are given in detail in the paper.