Narrow Results

In this paper, we present a computational modeling approach for the dynamics of human crowds, where the spreading of an emotion (specifically fear) has an influence on the pedestrians’ behavior. Our approach is based on the methods of the kinetic theory of active particles. The model allows us to weight between two competing behaviors depending on fear level: the search for less congested areas and the tendency to follow the stream unconsciously (herding). The fear level of each pedestrian influences their walking speed and is influenced by the fear levels of their neighbors. Numerically, we solve our pedestrian model with emotional contagion using an operator splitting scheme. We simulate evacuation scenarios involving two groups of interacting pedestrians to assess how domain geometry and the details of fear propagation impact evacuation dynamics. Further, we reproduce the evacuation dynamics of an experimental study involving distressed ants.

Evacuation modeling is a promising measure to support decision making in scenarios such as flooding, explosion, terrorist attack and other emergency incidents. Given the special attention to the terrorist attack, we build up an agent-based evacuation model in a railway station square under sarin terrorist attack to analyze such incident. Sarin dispersion process is described by Gaussian puff model. Due to sarin’s special properties of being colorless and odorless, we focus more on the modeling of agents’ perceiving and reasoning process and use a Belief, Desire, Intention (BDI) architecture to solve the problem. Another contribution of our work is that we put forward a path planning algorithm which not only take distance but also comfort and threat factors into consideration. A series of simulation experiments demonstrate the ability of the proposed model and examine some crucial factors in sarin terrorist attack evacuation. Though far from perfect, the proposed model could serve to support decision making.

The evacuation process under emergency is studied by means of experiments and simulations, focusing on the influence of the environment information. A revised cellular automaton model in which environment information is considered as "static information" (building structure, spatial distance, etc.) and "dynamic information" (sounds of fire alarm, etc.) is introduced. Two scenarios, including evacuation with and without visibility in a classroom, are studied to investigate the different influence of the two kinds of information on human behavior. The experimental and simulation results demonstrate that:

(1) to intensify the spatial distance information can reduce the evacuation time;

(2) the spatial distance is not the only decisive factor especially in evacuation without visibility because the sound information, which is ignorable in evacuation with visibility, is playing a more important role under this condition;

(3) the intensity of static information can reflect evacuees' familiarity of the environment;

(4) the model can reproduce the experiments well, and the simulation method is useful for further study of the crowd movement simulation.

Pedestrian flow both in normal and emergency situations (i.e. evacuation) has been widely studied by means of experiments as well as modeling methods. In this paper, an extended lattice-gas model is proposed to reproduce the pedestrian flow on multi-storey stairs during evacuations. Two-stage turning strategy is incorporated into the proposed model to simulate the 180${}^{\circ }$ turning behaviors of pedestrians on staircase mid-landings, and some movement characteristics such as walking preference and the probabilistic feature of turning are also considered in the extended model. The effectiveness of the model is demonstrated on different evacuation scenarios with different basic parameters. The results show that turning behavior indeed influences the pedestrian flow under the emergency situation (i.e. the drift force in the lattice-gas model is large) while walking preference has a clear negative effect on the pedestrian flow at the normal situations (i.e. the drift force in the lattice-gas model is small). In addition, the results indicate that the entrance period has more effect on the flow performance when compared with the entrance rate. The study may be useful for understanding the flow phase of pedestrians on stairs and developing efficient strategy for crowd management during evacuations.

In order to characterize the disturbance fluctuation of pedestrian flow caused by the disturbance during evacuation and the state change of pedestrian flow, this paper improves the social force model by introducing disturbance fluctuation force. First, a momentum equation is established to describe the change of pedestrian flow under the influence of disturbance fluctuation, and the mathematical expression of disturbance fluctuation force is given. Second, the evacuation processes of pedestrian flow with and without “queue jumpers” are simulated with the simulation experimental platform, and the key factors influencing the performance of the model are deeply studied through numerical analysis. The results showed that: when the expected velocity is the same, the bigger the angle between the cross-section position vector and the initial expected velocity is, the more serious the congestion occurs at the exit. In addition, when the crowd density is small, the larger the angle, the higher the evacuation efficiency and vice versa.

There often exist behaviors of moving against the main direction of evacuation in order to rescue or find the important missing people in real situations. However, the traditional social force model (SFM) often lacks consideration of such “counter flow”. Motivated by this, we improve the traditional SFM to study the counter flow and its influence on evacuation out of multi-exit rooms. We call the person to be rescued “superior” and the rescuers “subordinate”. Two different rescue situations are proposed: superior waiting in place (case 1) and superior moving towards the exit (case 2). The results show that the counter flow will always reduce the evacuation efficiency to a certain extent, and the evacuation efficiency of case 1 is lower than that of case 2. At the same time, for these two cases, increasing the number of rescuers increases the evacuation time. We also find that the existence of counter flow can enlarge the effect of “faster-is-slower”, while increasing the number of exports can significantly improve the rescue efficiency. We hope that this result can help to improve the efficiency of emergency evacuation with rescue.

The tsunami that hit the Andaman beach of Thailand on 26 December 2004 demonstrated the need for safe evacuation shelter for the public. However, there exists no guideline for designing such a shelter. In response to this need, the Department of Public Works and Town & Country Planning (DPT) funded a project to develop the guidelines for designing tsunami shelters. The results of the project have been published as a design manual for tsunami resistant shelter. In this paper, the design approaches for such tsunami shelters are described. The shelters are classified into two categories: (1) shelter in the area where large debris is unlikely and (2) shelter in the area where large debris is likely. In the former case, a static load of a certain magnitude representing small-to-medium debris is assumed to act at random points on the structure at the inundation depth. In the latter case, the work-energy principle is adopted to balance kinetic energy of large moving mass with the work done through energy-absorbing devices installed around the perimeter of the lower floors of the building. In both cases, the structure consists of a main inner structure and an outer protection structure. The function of the main structure is to provide usable spaces for evacuees, whereas the outer protection structure protects the inner structure from debris impact. The main structure is designed to be either elastic or with a low acceptable damage level. The structural framing of the main and the protection structures can be concrete or steel structures that are capable of resisting lateral forces. The major difference between the two types of building lie in the way the outer structure is connected to the inner one. In the first category, the connector is rigid so that both the inner and outer structures resist the load together. In the second category, energy-absorbing connectors are used to absorb the impact energy. The structure must, therefore, be analyzed using a nonlinear static approach. The design guidelines for both building types are described conceptually in this paper.

A multiplicity of situations can trigger off an evacuation of a room under panic conditions. For "normal" (with "normal" meaning absence of obstacles, perfect visibility, etc.) environmental conditions, the "faster is slower" effect dominates the dynamics of this process. It states that as the pedestrians desire to reach the exit increases, the clogging phenomena delays the time to get out of the room. But, environmental conditions are usually far from "normal." In this work, we consider that pedestrians have to find their way out under low visibility conditions. Some of them might switch to a herding-like behavior if they do not remember where the exit was. Others will just trust on their memory. Our investigation handles the herding and memory effects on the evacuation of a single exit room with no obstacles. We also include a section on how signaling devices affect the evacuation process. Unexpectedly, some low visibility situations may enhance the evacuation performance. This can be resumed as a second paradoxical result, since we demonstrated in an earlier investigation that "clever is not always better" G. A. Frank and C. O. Dorso, Physica A390, 2135 (2011).

Pedestrian heterogeneity is one of the important factors affecting evacuation efficiency in subway stations. This paper mainly studies the impact of pedestrian heterogeneity on evacuation based on simulations. With the help of Massmotion, the Qingdao Jinggangshan Road subway station is modeled. The social force model is used as the pedestrian dynamics model and the minimum cost model is used as the decision-making mechanism of pedestrian path selection. The models are verified by comparing the field data with the corresponding simulation data. Fully considering the impact of different pedestrian attributes on evacuation efficiency, pedestrians are divided into three categories with different speed levels and three categories with different body size levels. Simulation experiments are carried out by adjusting the proportional relationship of the number of pedestrians with different attributes. The simulation results indicate that the larger the proportion of fast pedestrians under the same number of evacuees, the higher the evacuation efficiency to a certain extent. The evacuation efficiency could be reduced accordingly with the increase in the proportion of pedestrians with large body sizes. When the pedestrian density is large, the impact of pedestrian heterogeneity on evacuation cannot be clearly reflected. Moreover, the quantitative fitting relationship between evacuation time and pedestrian quantity could be obtained. This paper provides a theoretical basis for the determination of evacuation strategy for the heterogeneous crowd.

Understanding the timing requirements for evacuation of people has focused primarily on independent pedestrians rather than pedestrians emotionally connected. However, the main statistical effects observed in crowds, the so-called “faster is slower”, “clever is not always better” and the “low visibility enhancement”, cannot explain the overall behavior of a crowd during an evacuation process when correlated pedestrians due to, for example feelings, are present. Our research addresses this issue and examines the statistical behavior of a mixture of individuals and couples during a (panic) escaping process. We found that the attractive feeling among couples plays an important role in the time delays during the evacuation of a single exit room.

We have proposed a new evacuation model based on discrete time loss queuing method in order to effectively depict the queuing of pedestrians in an indoor space and its effect over evacuation performance. In this model, the calculation formula of pedestrian movement probability is given first based on field value and average queuing time; the average queuing time is depicted with the discrete time loss queuing method and the adopted evacuation strategy is set forth through defining cellular evolution process. Moreover, with the use of the established simulation platform for experiment, we have made a deep study of relations of parameters such as evacuation time, pedestrian density, exit number and average queuing time to obtain the pedestrian flow characteristic more in line with the reality. The result has shown that there is a great change in the evacuated population in the change of crowded state at the exit, and in the background of high population density, it is beneficial for reducing queuing time to prefer faraway exit to overcrowded exit for evacuation.

To address efficiency and security problem of pedestrian evacuation in indoor space, a cellular automaton evacuation model is proposed based on the random fuzzy minimum spanning tree. First, based on field, crowding coefficient and available path capacity, the model defines the calculation formula of pedestrian movement probability and provides detailed evacuation optimization method and its evolution process. At last, we use the established simulation platform to make computer experiments, analyzing the relation of evacuation time, exit flow rate, exit crowding coefficient and available path capacity in order to obtain more realistic pedestrian flow characteristics. The result has shown that the model has good adaptability.

An event logic graph is a kind of knowledge mapping technology for knowledge inference and simulation analysis, which takes events as the core and portrays the hierarchical system and logical evolution pattern between events. In order to apply it to further improve the accuracy of related studies, such as pedestrian flow evacuation, simulation model optimization and risk prediction. In this paper, we use social network resources, media resources and journal database resources to build our corpus and adopt the explicit event relationship extraction method based on syntactic dependency and the implicit event relationship extraction method based on BERT+Bi-LSTM+Attention+Softmax for the characteristics of explicit event relationship and implicit event relationship, respectively. This paper constructs a pedestrian flow evacuation matter mapping for three typical scenarios and discusses its application path. It is found that once a sound knowledge base of logical reasoning and event logic graph is established, both research on optimization of pedestrian flow evacuation simulation models and research on identification and assessment of pedestrian flow evacuation safety risks will receive excellent support.

We present modeling strategies that describe the motion and interaction of groups of pedestrians in obscured spaces. We start off with an approach based on balance equations in terms of measures and then we exploit the descriptive power of a probabilistic cellular automaton model.

Based on a variation of the simple symmetric random walk on the square lattice, we test the interplay between population size and an interpersonal attraction parameter for the evacuation of confined and darkened spaces. We argue that information overload and coordination costs associated with information processing in small groups are two key processes that influence the evacuation rate. Our results show that substantial computational resources are necessary to compensate for incomplete information — the more individuals in (information processing) groups the higher the exit rate for low population size. For simple social systems, it is likely that the individual representations are not redundant and large group sizes ensure that this non-redundant information is actually available to a substantial number of individuals. For complex social systems, information redundancy makes information evaluation and transfer inefficient and, as such, group size becomes a drawback rather than a benefit. The effect of group sizes on outgoing fluxes, evacuation times and wall effects is carefully studied with a Monte Carlo framework accounting also for the presence of an internal obstacle.

The challenge of protecting communities in tsunami-prone populated small islands is difficult to meet. Likewise, the islands are often found with a lack of disaster mitigation infrastructure. A tsunami that occurred around the Mentawai Islands of Indonesia on October 25, 2010, causing around 500 dead, is the inspiration for this paper. This study was aimed at elaborating practices in protecting communities of small islands from tsunamis by incorporating information about the estimated time of arrival of a tsunami into the islands mitigation measures. A field survey to obtain the impacts of the tsunami on the number of casualties and damages was conducted in February 2011 around the Mentawai Islands. In the survey, a set of questionnaires were distributed in the Mentawai Islands to investigate the small island residents' responses just after the shock from the tsunami waves. This study was also followed by numerical simulations to obtain tsunami wave Estimated Time of Arrival (ETA) for the Mentawai islands. Numerical simulations were conducted using Delft3D software coupled with Tsunami toolkit. This research found that the ETAs for the Mentawai Islands range between 9–20 min. With the existing tsunami early warning system in Indonesia, the ETAs are quite short. Comparing the Simulated ETAs to the findings from the Mentawai Islands tsunami survey led to the recommendation that the best way to increase the community's preparedness for a tsunami would be by managing village-based spatial planning. Such spatial planning may include relocating the residents far away from the coastal area. This would enable the community to have more time to evacuate should a tsunami threat occur.

In current tsunami prevention and mitigation, evacuation is the most important method of saving people’s lives. Tsunami evacuation is analyzed for a given travel time and a specific inundation area. Before evacuation analysis, the tsunami inundation and tsunami travel time are first calculated by numerical modeling. This paper analyzes the tsunami evacuation of Haimen Town, Jiaojiang District, Taizhou City, China, under the hypothesis of a magnitude 9.0 earthquake scenario in the Ryukyu Trench. The Cornell multi-grid coupled tsunami (COMCOT) model and Tsunami Travel Time (TTT) model are used to calculate the tsunami inundation and tsunami travel time, respectively. GIS techniques are used to solve the evacuation problem. Both horizontal and vertical evacuations are adopted based on the Chinese community characteristics, disaster prevention facilities, land use, and other practical conditions. A cost raster is used to analyze the arrival cost of each grid in the study area. The location allocation and cost allocation methods are used to solve shelter selection and coverage problems, respectively. The network analyst is applied to provide evacuation routes for each community. The evacuation analysis results can provide a scientific reference for the development of tsunami evacuation plans.

Tsunami is one of the world’s most dangerous marine disaster. In this paper, freely available remote sensing data are applied to study the hazard, vulnerability, and evacuation in the event that a tsunami strikes the district of Tianya in the city of Sanya. Tsunami inundation is calculated using a tsunami numerical model, and the tsunami vulnerability and evacuation in the inundation area are analyzed. Aster Global Digital Elevation Model elevation data are applied to provide input data for the tsunami numerical model and thus obtain tsunami inundation areas, while they are also used to study the surface slope for evacuation. Landsat satellite imagery is used to analyze land–water borders and land cover in both hazard assessment and evacuation analysis. Visible Infrared Imaging Radiometer Suite nighttime lights data provide information of the socioeconomic activity for vulnerability analysis. The analysis results show that the remote sensing data is suitable for tsunami assessment and evacuation analysis of China’s county-level region. We can get a general understanding about tsunami vulnerability and evacuation situation. One kind of remote sensing data can accomplish several tasks, avoiding the error caused by different source data. Remote sensing can play an important role in tsunami assessment.

The handling of certain quantities of hazardous materials (toxic, flammable and/or explosive) can potentially create major accidents endangering the public and worker’s health, as well as the environment. Emergency response planning consists in assessing protective actions (evacuation, building protection of various degrees) for each and every area section around a hazardous facility. This chapter presents a methodology for the optimization of the response to an emergency situation around chemical plants processing hazardous substances (e.g. oil refineries, pesticide plants) by taking into account multiple criteria. A Multi-Objective Evolutionary Algorithm for the determination of the efficient set of solutions is presented.