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Uneven distribution and mistarget beneficiaries are among problems encountered during post-disaster relief operations in 2010 Mount Merapi eruption. The purpose of this paper is to develop an empirically founded agent-based simulation model addressing the evacuation dynamics and to explore coordination mechanism and other promising strategies during last-mile relief delivery.

An agent-based model which was specified and parameterized by empirical research (interviews and survey) was developed to understand the mechanism of individual decision making underlying the evacuation dynamics. A set of model testing was conducted to evaluate confidence level of the model in representing the evacuation dynamics during post-disaster of 2010 Mount Merapi eruption. Three scenarios of last-mile relief delivery at both strategic and operational levels were examined to evaluate quantitatively the effectiveness of the coordination mechanism and to explore other promising strategies.

Results indicate that the empirically founded agent-based modeling was able to reproduce the general pattern of observable Internal Displaced Persons based on government records, both at micro and macro levels, with a statistically non-significant difference. Low hazard perception and leader-following behavior which refuses to evacuate are the two factors responsible for late evacuation. Unsurprisingly, coordination through information sharing results in better performance than without coordination. To deal with both uneven distribution and long-term demand fulfillment, coordination among volunteers during aid distribution (at downstream operation) is not sufficient. The downstream coordination should also be accompanied with coordination between aid centers at the upstream operation. Furthermore, the coordination which is combined with other operational strategies, such as clustering strategy, using small-sized trucks and pre-positioning strategy, seems to be promising. It appears that the combined strategy of coordination and clustering strategy performs best among other combined strategies.

The significant role of early evacuation and self-evacuation behavior toward efficient evacuation indicates that human factor (i.e. hazard perception and cultural factor) should be considered in designing evacuation plan. Early warning system through both technology and community empowerment is necessary to support early evacuation. The early warning system should also be accompanied with at least 69 percent of the population performing self-evacuation behavior for the effective evacuation. As information sharing through coordination is necessary to avoid redundant efforts, uneven distribution and eventually to reduce unmet demand, the government can act as a coordinating actor to authorize the operation and mobilize the resources. The combination of coordination and another strategy reducing lead time such as clustering analysis, thus increasing responsiveness, is seemly strategy for efficient and effective last-mile relief distribution.

Literature on coordination is dominated by qualitative approach, which is difficult to evaluate its effectiveness quantitatively. Providing realistic setting of the evacuation dynamics in the course of the 2010 Mount Merapi eruption, the empirically founded agent-based model can be used to understand the factors influencing the evacuation dynamics and subsequently to quantitatively examine coordination mechanisms and other potential strategies toward efficient and effective last-mile relief distribution.

This paper aims to focus on the combination of fire- and agent-based modelling approaches to assess the level of safety of a multi-storeyed building case study.

For an existing building to be occupied such as the engineering student dormitory of Mons (Belgium), engineers must establish, among the other things, that the building affords a sufficient level of safety during fire incident. This can be verified in accordance with prescriptive- and performance-based methodologies. The performance-based approach consists on using simulation tools such as fire dynamics simulator with evacuation to ensure/verify the level of safety required. In this paper, a model case study was built and then various scenarios have been implemented to answer some safety questions.

For this building layout, the results demonstrate that combining different egress components (i.e. stairs and outdoor ladders) has a negative impact on the evacuation process than using only the stairs to evacuate the building; phased evacuation strategy will not necessarily lead to faster evacuation; adding fire doors in the stairs and between the floors has a beneficial effect on the evacuation process.

This case study proposes some recommendations about adapted evacuation strategy and investments to improve the safety of high-rise student’s dormitory in case of fire.

It is of paramount importance to ensure safe and fast evacuation routes in cities in case of natural disasters, environmental accidents or acts of terrorism. The same applies to large-scale events such as concerts, sport events and religious pilgrimages as airports and to traffic hubs such as airports and train stations. The prediction of pedestrian is notoriously difficult because it varies depending on circumstances (age group, cultural characteristics, etc.). In this study, the Ensemble Kalman Filter (EnKF) data assimilation technique, which uses the updated observation data to improve the accuracy of the simulation, was applied to improve the accuracy of numerical simulations of pedestrian flow.

The EnKF, one of the data assimilation techniques, was applied to the in-house numerical simulation code for pedestrian flow. Two cases were studied in this study. One was the simplified one-directional experimental pedestrian flow. The other was the real pedestrian flow at the Kaaba in Mecca. First, numerical simulations were conducted using the empirical input parameter sets. Then, using the observation data, the EnKF estimated the appropriate input parameter sets. Finally, the numerical simulations using the estimated parameter sets were conducted.

The EnKF worked on the numerical simulations of pedestrian flow very effectively. In both cases: simplified experiment and real pedestrian flow, the EnKF estimated the proper input parameter sets which greatly improved the accuracy of the numerical simulation. The authors believe that the technique such as EnKF could also be used effectively in other fields of computational engineering where simulations and data have to be merged.

This technique can be used to improve both design and operational implementations of pedestrian and crowd dynamics predictions. It should be of high interest to command and control centers for large crowd events such as concerts, airports, train stations and pilgrimage centers.

To the authors’ knowledge, the data assimilation technique has not been applied to a numerical simulation of pedestrian flow, especially to the real pedestrian flow handling millions pedestrian such as the Mataf at the Kaaba. This study validated the capability and the usefulness of the data assimilation technique to numerical simulations for pedestrian flow.

The purpose of this study is to develop optimal evacuation plan to provide valuable theoretical and practical insight in the fire evacuation work of similar structures, by proposing a systematic simulation-based guided-evacuation agent-based model (GAM) and a three-stage mathematical evacuation model to investigate how to simulate, assess and improve the performance efficiency of the evacuation plan.

The authors first present the self-evacuation and guided-evacuation models to determine the optimal evacuation plan in ship chamber. Three key performance indicators are put forward to quantitatively assess the evacuation performance within the two fire scenarios. The evacuation model in tower is built to obtain the dividing points of the three different fire evacuation plans.

The study shows that the optimal evacuation plan determined by the GAM considering social relationships effectively relieves the congestion or collision of evacuees and improves the evacuation uniformity. The optimal evacuation plan not only solves the crush caused by congestion or collision of evacuees but also can greatly shorten the evacuation time for passenger ship fire.

This study establishes the GAM considering the interactive evacuee characteristics and the proportion of evacuees guided by the crew members to make the optimal evacuation plan more time-efficient. The self-evacuation process is simulated to assess the performance of the guided-evacuation strategies, which are used to verify the effectiveness and feasibility of the optimal evacuation plan in this research.

It has been witnessed that many incidents of crowd evacuation have resulted in catastrophic results, claiming lives of hundreds of people. Most of these incidents were a result of localized herding that eventually turned into global panic. Many crowd evacuation models have been proposed with different aspects of interests. The purpose of this paper is to attempt to bring together many of these aspects to study evacuation dynamics.

The proposed agent-based model, in a hypothetical physical environment, uses perception maps for routing decisions which are constructed from agents’ personal observations of the surroundings as well as information gathered through distant communication. Communication is governed by a trust model which measures the authenticity of the information being shared. Agents are of two types; emotional and rational. The trust model is combined with a game-theoretic model to resolve conflict of agents’ own type with that of types of agents in the neighborhood.

Evacuation dynamics in different environmental and exit strategies are evaluated on the basis of reduced herding and evacuation time. Using this integrated information sharing model, agents gain an overall view of the environment, sufficient to select the optimal path towards exits with respect to reduced herding and evacuation time.

The proposed model has been formulated and established using an agent-based simulation integrating important modeling aspects. The paper helps in understanding the interplay between technological and humanistic aspects in smart and pervasive environments.

Metro stations have become a crucial aspect of urban rail transportation, integrating facilities, equipment and pedestrians. Impractical physical layout designs and pedestrian psychology impact the effectiveness of an evacuation during a metro fire. Prior research on emergency evacuation has overlooked the complexity of metro stations and failed to adequately consider the physical heterogeneity of stations and pedestrian psychology. Therefore, this study aims to develop a comprehensive evacuation optimization strategy for metro stations by applying the concept of design for safety (DFS) to an emergency evacuation. This approach offers novel insights into the management of complex systems in metro stations during emergencies.

Physical and social factors affecting evacuations are identified. Moreover, the social force model (SFM) is modified by combining the fire dynamics model (FDM) and considering pedestrians' impatience and panic psychology. Based on the Nanjing South Metro Station, a multiagent-based simulation (MABS) model is developed. Finally, based on DFS, optimization strategies for metro stations are suggested.

The most effective evacuation occurs when the width of the stairs is 3 meters and the transfer corridor is 14 meters. Additionally, a luggage disposal area should be set up. The exit strategy of the fewest evacuees is better than the nearest-exit strategy, and the staff in the metro station should guide pedestrians correctly.

Previous studies rarely consider metro stations as sociotechnical systems or apply DFS to proactively reduce evacuation risks. This study provides a new perspective on the evacuation framework of metro stations, which can guide the designers and managers of metro stations.

Surveys of the public have been conducted to document and explain evacuation behaviour in a wide range of threatening events during the past half-century. Many of the behaviours are directly applicable to transportation modelling and management: whether people evacuate, when they depart, where they go, the routes they employ and the number of vehicles they use. Data have usually been collected by telephone interview or mailed questionnaires. Traditional survey methods should be supplemented by Internet surveys, traffic counts and GPS tracking. More real-time data collection should be employed to document a wider range of behaviours during a threat more accurately and to better understand the dynamics of evacuation decisions.

In mass gatherings, a large number of people gather at a single location. To ensure safety of these people, adequate crowd management strategies are essential. Specifically, in case of an emergency, efficient evacuation can save the lives of many people. This paper aims to develop various control strategies for efficient evacuation, including providing information of routes, changing the physical layout and controlling the behavior of evacuees.

Mathematical models have been developed for optimal decision-making and analysis of the effect of these control strategies during evacuation. A global search with Sequential Quadratic programming is used to increase the likelihood of obtaining the optimal solution to these models. Further, an illustrative evacuation example is presented to test the efficacy of the models.

The results of the illustrative example demonstrate that the models and their corresponding strategies can bring significant benefits for efficient evacuation.

The models developed can play a significant role in helping the security staff execute evacuation better at an operational level. The authors’ models can also have implications at the strategic level for the crowd manager.

Efficient strategies and optimal decision-making during evacuation can save lives of people. These models can develop efficient strategies that can save lives of people.

This paper fulfills need to study the effect of various control strategies on evacuation efficiency for a large area and its complete network.