Average Evacuation Time Research Articles

Bilevel Traffic Evacuation Model and Algorithm Design for Large-Scale Activities

This paper establishes a bilevel planning model with one master and multiple slaves to solve traffic evacuation problems. The minimum evacuation network saturation and shortest evacuation time are used as the objective functions for the upper- and lower-level models, respectively. The optimizing conditions of this model are also analyzed. An improved particle swarm optimization (PSO) method is proposed by introducing an electromagnetism-like mechanism to solve the bilevel model and enhance its convergence efficiency. A case study is carried out using the Nanjing Olympic Sports Center. The results indicate that, for large-scale activities, the average evacuation time of the classic model is shorter but the road saturation distribution is more uneven. Thus, the overall evacuation efficiency of the network is not high. For induced emergencies, the evacuation time of the bilevel planning model is shortened. When the audience arrival rate is increased from 50% to 100%, the evacuation time is shortened from 22% to 35%, indicating that the optimization effect of the bilevel planning model is more effective compared to the classic model. Therefore, the model and algorithm presented in this paper can provide a theoretical basis for the traffic-induced evacuation decision making of large-scale activities.

Simulation-based route planning for pedestrian evacuation in metro stations: A case study

Abstract This paper develops a systematic simulation-based multi-attribute decision approach to route choice planning, in which uncertainties and dynamics underlying pedestrian behaviors during an evacuation are modeled given the complex interaction between pedestrians and the traffic is taken into account. Three factors, namely the length of evacuation route , time of evacuation process and density of pedestrian flow , are identified to have significant impacts on the efficiency of the evacuation process, especially at peak hours in a metro station. Two route planning strategies, as specified in Scenarios I and II, respectively, are proposed to simulate the pedestrian evacuation performance. Four key performance indicators (KPIs), namely average pedestrian density , a verage evacuation length , average evacuation time and average evacuation capacity , are put forward to assess the evacuation performance within different route planning strategies. The values of these KPIs on a metro station in the Wuhan metro system, China, are measured and compared in different scenarios. Results indicate that the performance of the evacuation efficiency can be significantly improved when the route planning strategy (that is specified in Scenario II) is implemented during the pedestrian evacuation. The developed approach can provide valuable theoretic and practical insight into a deep understanding of route planning strategies during the pedestrian evacuation, and thus, the improvement of safety and economic objectives can further be achieved in the design or re-design of metro evacuation systems.

Automatic evacuation guiding scheme based on implicit interactions between evacuees and their mobile nodes

When large-scale disasters occur, evacuees have to evacuate to safe places quickly. They, however, may not be able to afford to obtain sufficient information for their evacuations under such emergent situations. In this paper, we propose an automatic evacuation guiding scheme using evacuees’ mobile nodes, e.g., smart phones. The key idea to achieve automatic evacuation guiding is implicit interactions between evacuees and their mobile nodes. Each mobile node tries to navigate its evacuee by presenting an evacuation route. At the same time, it can also trace the actual evacuation route of the evacuee as the trajectory by measuring his/her positions periodically. The proposed scheme automatically estimates blocked road segments from the difference between the presented evacuation route and the actual evacuation route, and then recalculates the alternative evacuation route. In addition, evacuees also share such information among them through direct wireless communication with other mobile nodes and that with a server via remaining communication infrastructures. Through simulation experiments, we show that 1) the proposed scheme works well when the degree of damage is high and/or road segments are continuously blocked, 2) the average evacuation time can be improved even in small penetration ratio of the proposed system, and 3) the direct wireless communication can support many evacuations at almost the same level as the communication infrastructure when the number of evacuees becomes large.

Statistical fluctuations in pedestrian evacuation times and the effect of social contagion.

Mathematical models of pedestrian evacuation and the associated simulation software have become essential tools for the assessment of the safety of public facilities and buildings. While a variety of models is now available, their calibration and test against empirical data are generally restricted to global averaged quantities; the statistics compiled from the time series of individual escapes ("microscopic" statistics) measured in recent experiments are thus overlooked. In the same spirit, much research has primarily focused on the average global evacuation time, whereas the whole distribution of evacuation times over some set of realizations should matter. In the present paper we propose and discuss the validity of a simple relation between this distribution and the microscopic statistics, which is theoretically valid in the absence of correlations. To this purpose, we develop a minimal cellular automaton, with features that afford a semiquantitative reproduction of the experimental microscopic statistics. We then introduce a process of social contagion of impatient behavior in the model and show that the simple relation under test may dramatically fail at high contagion strengths, the latter being responsible for the emergence of strong correlations in the system. We conclude with comments on the potential practical relevance for safety science of calculations based on microscopic statistics.

An efficient partially dedicated strategy for evacuation of a heterogeneous population

When a heterogeneous population evacuates from a high-rise building, residents who occupy a large area and move at a slow pace, such as people in wheelchairs, tend to block pathways and significantly affect the evacuation of other occupants. In this study, we propose a partially dedicated evacuation strategy, in which an evacuation path is dedicated to a high-speed subpopulation of people without disabilities while another route is dedicated to the remaining heterogeneous population to minimize the blocking effect. The key factor in this strategy is determining the exact proportion of people without disabilities at each floor to each route. We use a time-expanded network flow model and a simulation-based optimization approach to solve the problem systematically. Simulation experiments show that the proposed evacuation strategy can reduce the average evacuation time of the entire population by 10%. The proposed partially dedicated evacuation strategy can be applied to other problems.

Optimal facility–final exit assignment algorithm for building complex evacuation

In this research, a mathematical model is proposed to solve a facility–final exit assignment problem. In a facility–final exit assignment, “facility” means the sub-space of a building and “final exit” is the exit of the building to outside which applies to the overall building complex and not the facilities. Facilities are assigned to exits such that the average evacuation time of the last evacuee in a large building complex is minimized. This research proposes two mathematical models. The first one is a linear programming model that allows for the split of occupants in a facility so that they can evacuate through multiple exits. The second model is an integer programming model that constrains occupants in one facility to evacuate through a single exit. The proposed linear programming model is more realistic to simulate actual evacuation procedures when emergency events such as a fire or a chemical spill occur. In contrast, the proposed integer programming model is more suitable when the objective of the facility–final exit assignment is to train and guide occupants in building complex in pre-emergency environment assuming that we are under a certain disaster. A case study of a mega shopping mall in Korea indicates that the proposed optimal evacuation plan outperforms the facility–nearest exit assignment solution.

Modeling and simulation of a hospital evacuation before a forecasted flood

As high level emergencies can have serious consequences on hospital activities, an emergency management plan to face a crisis situation must be specified and assessed. Even though more and more research is devoted to this area, most studies are based on academic assumptions and the proposed improvement methods are difficult to apply in the real world. This paper deals with a hospital evacuation plan facing a flood based on a real life scenario. We modeled the evacuation process and identified its different activities. We then used SIMIO–a commercial simulation software–to translate our conceptual model into a dynamic model. Numerical experiments were conducted to determine the best way to assign the resources. We also propose two organizational improvements to the current, as-is, evacuation process. By simulating these changes, we were able to show that, if implemented together, they should be able to reduce the evacuation time by 1 h and 18 min, an improvement of 23.8% with respect to the current average evacuation time.

Modeling and simulation of pedestrian evacuation from a single-exit classroom based on experimental features

It is of fundamental importance to investigate the evacuation process from a room with obstacles. The typical case is the evacuation of students from a classroom. Based on evacuation experiments from a classroom, the essential features of evacuee are concluded. In the original floor field model, the dynamic floor field is introduced in order to reflect the interaction among pedestrians. A pedestrian may follow the virtual trace of another one in front. The static floor field does not consider the influence of pedestrians. In this paper, the original dynamic floor field is ignored. These desks and chairs are treated as impassable and passable static obstacles, respectively. The static and passible obstacles, such as chairs, lead to the delay of movement of pedestrians. Furthermore, pedestrians are regarded as movable obstacles. The effect of static obstacles on floor field does not change with time. However, the effect of movable obstacles on floor field is dynamic. Therefore, the whole floor field is updated dynamically according to the movement of crowd. Pedestrians may try to find another uncongested path or exit when they find the crowd in front. It provides a better description of the influence of downstream congestions on upstream crowd. The cellular automaton model based on the dynamic floor field is used to investigate the evacuation process in the case of four layouts and three exit widths. The spatial distributions of evacuation time in different conditions and also the average and maximum evacuation times are obtained. Numerical simulations reproduce the evacuation process observed in the experiment quite well. The evacuation time depends on arrangement of these desks and the exit width. For a given layout, the smaller exit leads to longer evacuation time. It is found that the evacuation time does not decrease monotonically with increasing the number of aisles, which depends on the width of aisle as well. When the aisle is not wide enough, the conflict of pedestrians from both sides reduces the efficiency of evacuation. It is helpful for coping with crowd evacuation with an aisle close to the exit side of the wall. The reasons of the differences between experimental and simulation results are also discussed in more detail.

Estimating the effects of mental disorientation and physical fatigue in a semi-panic evacuation

Understanding the impossibility of replicating a real panic emergency situation and experimenting human objects in such artificially created dangerous situation, this paper focuses on the evacuation of a heterogeneous population including people with disabilities in a semi-panic simulated situation in which people tend to hurry more than those in non-panic evacuation but exhibit less urgency than those in a panic emergency. Ultimately, we intend to estimate and quantify the effects of mental disorientation and physical fatigue on the average evacuation times of six different disability groups and the entire group in a simulated environment of a 24-story building. According to our experiments, mental disorientation due to sudden emotion escalation from the recognition of unexpected dangers increases the average evacuation times up to 25 percent depending on the complexity of evacuation routes of the simulated buildings. In addition, accumulated physical fatigue of human beings during the evacuation process could also significantly delay the evacuation time. Most of all, the impact magnitudes of these two main factors vary depending on the types of disabilities of individuals, insinuating the needs of developing evacuation plans and strategies for each group.

A space–time efficiency model for optimizing intra-intersection vehicle–pedestrian evacuation movements

The effectiveness of an evacuation plan is a central concern of emergency management agencies. Methodologies for assessing and optimizing the space–time use efficiency of an evacuation plan have yet to be studied satisfactorily. To this end, this paper proposes an assessment metric and uses it for the optimization of evacuation plans. First, we define a space–time use efficiency metric on the basis of trajectories on road segments and intersections. The metric measures the usage of an evacuation network by supporting a trajectory-based analysis of the competing behaviors of vehicles and pedestrians in a hybrid pedestrian-vehicle simulation. Secondly, we present a two-tier hybrid multi-objective optimization algorithm to plan vehicle and pedestrian turning movement directions in an integrated road and building-interior network for the purpose of making decisions about evacuation plans. This algorithm has three objectives: (i) minimizing average evacuation time, (ii) minimizing the overall length traveled, and (iii) maximizing space–time use efficiency in the evacuation network. The stadium at the Wuhan Sports Centre in China and its adjacent road network were chosen as the study environment. A total of 23,362 evacuees and 1362 vehicles were assumed for the evacuation experiments. The analysis results suggest that intra-intersection evacuation flows can significantly influence the space–time use efficiency of a evacuation plan. The proposed space–time use efficiency evaluation approach provides a practical method of measuring the effectiveness of evacuation plans.

A GIS-Based Football Stadium Evacuation Model

El Departamento de Seguridad Doméstica de los EE.UU. (DHS) ha identificado estadios deportivos como parte de la infraestructura crítica de la nación y como potenciales blancos terroristas. Por lo tanto, la planificación y simulacros de evacuación han sido identificados como prácticas y estándares de seguridad en eventos atléticos. En este estudio, un modelo de macro-simulación basado en los Sistemas de Información Geográfica (SIG) fue desarrollado para calcular tiempo de evacuación para el estadio de fútbol de la Universidad del Sur de Mississippi, en el evento de una amenaza provocada por el ser humano. Aunque existen modelos de evacuación complejos, el propósito de este estudio fue el desarrollar un modelo prototipo basado en los SIG que pueda ser utilizado como herramienta de entrenamiento y de preparación antes de los juegos por el personal local de emergencias con acceso a programas de SIG, en vez de un modelo de evacuación costoso que requiere profesionales adiestrados. En cuanto al modelo, los tiempos de evacuación máximos y promedios para que todos los aficionados abandonen el estadio y se desplacen fuera del campus fue de 4.1 horas y 2.1 horas respectivamente.

Models of Pedestrian Evacuation based on Cellular Automata

We study two models of pedestrian evacuation based on cellular automata and intelligent agents. We use the static floor field approach and augment it with additional transition rules (random movement and preservation of personal space) in order to model various aspects of human behaviour. Through numerical simulations we investigate pedestrian evacuation from rooms with various geometries (e.g. empty room, classroom). Using heatmaps (density diagrams of pedestrians), average evacuation times, velocity and other parameters we study the eectiveness of evacuation and potential dangers pedestrians may encounter.

A Flow-Dependent Secondary-Shortest Path Algorithm for Naval Ship Evacuation

In this paper, we introduce a secondary evacuation planning problem which is solved by computing flow-dependent shortest path through a known shortest time escape route on a ship. Given a primary escape route, our secondary evacuation planning problem consists in finding the second-shortest escape route, based on the cabin network rebuilding. We suggest a new model for flow-dependent network where the travel time of each link depends on the flow speed and the flow speed depends on the total number of evacuees traversing the link. The model focused on the average evacuation time to travel through the ordered sequence of consecutive arcs by each group, and we proposed a heuristic algorithm to produce sub-optimal secondary evacuation plan. A numerical example is given at last. Results showing that our algorithm can effective supply the flow-dependent network k-shortest path need in reasonable computation times.

운항실습선 승선자의 분포특성에 따른 대피시간 비교

본 연구는 운항실습선을 대상으로 선내 승선자의 군집유형에 따른 피난 시간과 특성을 시뮬레이션에 의해 비교한 것으로, 크루즈선 승객은 승선 시 다양한 선내 활동이 가능하다는 관점에서 출발하였다. 그리고 승선자와의 인터뷰를 통해 승선 시 행동 유형을 군집유형 A(지정선실 내 재실), 군집유형 B(모든 승조원이 정상활동 공간에 위치), 군집유형 C(모든 승조원이 소속 식당에 위치)의 3가지로 분류하여 비교 평가하였다. 연구의 성과를 정리하면 다음과 같다. 군집유형 B는 피난시간이 다른 유형에 비해 가장 빨랐고 피난 정체구간도 짧았다. 군집유형 C의 경우 승조원이 특정공간에 집중적으로 분포함에 따라 피난과정에서 Upper deck가 병목 구간으로 작용하였고 피난시간이 오래 걸렸다. 이상과 같은 결과로부터 동일한 선박 내에서도 화재 등의 재난 발생 시 선내 재실자의 분포특성에 맞는 피난 관리 및 대응책이 필요함을 알 수 있었다. This study simulates and compares the evacuation time and characteristics according to the living patterns on board a training ship which was launched in Dec. 2005, on the viewpoint of the various activities being possible on board a cruise ship. Based on interviews with personnels on board, 3 living patterns are set as representative living conditions; Pattern A(all personnels are positioned at their cabins), Pattern B(all personnels are positioned at lecture rooms, offices or else), Pattern C(all personnels are positioned at restaurant or cafeteria). The simulation results show that Pattern B is comparatively ideal because the evacuation time is short and there is less delay of personnels' movement on each deck. On the contrary, Pattern C is evaluated as the worst because the average evacuation time took more than 360 seconds and the bottle-neck happened at Upper deck. As a result, this study proposes the needs of various countermeasures against the fire and/or disaster, considering the various living patterns on cruiser(s) and/or passenger ship(s).

CELLULAR AUTOMATA MODELS OF EVACUATION ON STAIRCASE-LIKE GEOMETRIES

In this work, the authors study two models of pedestrians' movement. The models are based on cellular automata with static floor fields and additional transition rules — namely random movement and a form of pressure. The authors investigate, through numerical simulations, the process of evacuation on staircase-like geometries similar to the ones in multiple-floor buildings. Average evacuation time, average number of moving pedestrians and density diagrams are used to determine the critical properties of the models. Both models exhibit rapid changes in their behaviour when control parameters are beyond certain critical values.

Simplified Evacuation Planning Model on Naval Ship

In light of the growth in the numbers of maritime disasters during recent years, there is a growing interest in the evacuation of passengers and crew at sea, as documented in recent discussions at the Marine Safety Committee of the IMO. NATO has also developed analogous regulations as part of its Naval Ship Code. In this paper we propose a simplified evacuation model based on the shortest emergency evacuation time for emergency evacuation of a naval ship, which using the theory of mixed-integer linear program to solve navy ship evacuation problem. This evacuation planning model focused on the average evacuation time to travel through the ordered sequence of consecutive arcs by each group. In addition, the model revealed the amount of flow per time unit through the door. Secondly, we proposed a heuristic algorithm to produce sub-optimal evacuation plan. A numerical example is given at last. Results show that the model based on the theory of the mixed-integer linear program can provide more available evacuation solution for naval ship evacuation process.

An integrated human decision making model for evacuation scenarios under a BDI framework

An integrated Belief-Desire-Intention (BDI) modeling framework is proposed for human decision making and planning for evacuation scenarios, whose submodules are based on a Bayesian Belief Network (BBN), Decision-Field-Theory (DFT), and a Probabilistic Depth-First Search (PDFS) technique. A key novelty of the proposed model is its ability to represent both the human decision-making and decision-planning functions in a unified framework. To mimic realistic human behaviors, attributes of the BDI framework are reverse-engineered from human-in-the-loop experiments conducted in the Cave Automatic Virtual Environment (CAVE). The proposed modeling framework is demonstrated for a human's evacuation behaviors in response to a terrorist bomb attack. The simulated environment and agents (models of humans) conforming to the proposed BDI framework are implemented in AnyLogic® agent-based simulation software, where each agent calls external Netica BBN software to perform its perceptual processing function and Soar software to perform its real-time planning and decision-execution functions. The constructed simulation has been used to test the impact of several factors (e.g., demographics, number of police officers, information sharing via speakers) on evacuation performance (e.g., average evacuation time, percentage of casualties).

Managing Large-Scale Multimodal Emergency Evacuations

This article presents the development of a novel framework that optimizes the evacuation of large cities using multiple modes including vehicular traffic, rapid transit, and mass-transit shuttle buses. A large-scale evacuation model is developed for the evacuation of the City of Toronto in case of emergency. A demand estimation model is first designed to accurately quantify the evacuation demand by mode (drivers vs. transit users), over time of the day when the crisis begins, and over space (location). The output of the demand estimation model is then fed into two optimization platforms: (1) an optimal spatio-temporal evacuation (OSTE) model that synergizes evacuation scheduling, route choice, and destination choice for vehicular traffic and (2) a model based on a new variant of the vehicle routing problem to optimize the routing and scheduling of mass-transit vehicles. The study concluded that OSTE can clear the City of Toronto 4 times faster than the do-nothing strategy. The OSTE average automobile evacuation time for the 1.21 million people using their cars is close to 2 h. The optimization of the routing and scheduling of the readily available Toronto Transit Commission fleet (4 Rapid Transit lines and 1320 transit buses used as shuttles) can efficiently evacuate the transit-dependent population (1.34 million) within 2 h.

Transit-Based Emergency Evacuation Simulation Modeling

Several recent mass evacuations, including those in advance of Hurricane Katrina in New Orleans and Hurricane Rita in Houston, have demonstrated the effects of limited planning for carless populations. The lack of planning left a significant portion of the mobility-limited population of both these cities unable to flee in advance of the storms. Since 2005, however, both of these cities (as well as others across the United States) have developed transit-assisted mass evacuation plans at various levels of detail. Because these plans are relatively recent and do not have a history of experience on which to base their performance, it is difficult to know how well, or even if, they will work. This article describes one of the first attempts to systematically model and simulate transit-based evacuation strategies. In it, the development of and the results gained from an application of the TRansportation ANalysis and SIMulation System (TRANSIMS) agent-based transportation simulation system to model assisted evacuation plans of New Orleans are described. In the research, average travel time and total evacuation time were used to compare the results of a range of conditions over a two-day evacuation period, including two alternative transit evacuation routing plans and four alternative network loading scenarios. Among the general findings of the research was that the most effective scenarios of transit-based evacuation were those that were carried out during time periods during which the auto-based evacuation was in its “lull” (nonpeak/overnight) periods. These conditions resulted in up to a 10% reduction in overall travel time and up to 45% reduction in the total evacuation time when compared to peak evacuation conditions. It was also found that routing buses to alternate arterial routes reduced the overall travel time by up to 52% and the total evacuation time by up to 14%.

Dynamic evacuation routes for personnel on a naval ship

AbstractWe propose a dynamic escape route system for emergency evacuation of a naval ship. The system employs signals that adapt to the causative contingency and the crew's physical distribution about the ship. A mixed‐integer nonlinear programming model, with underlying network structure, optimizes the evacuation process. The network's nodes represent compartments, closures (e.g., doors and hatches) and intersections, while arcs represent various types of passageways. The objective function integrates two potentially conflicting factors: average evacuation time and the watertight and airtight integrity of the ship after evacuation. A heuristic solves the model approximately using a sequence of mixed‐integer linear approximating problems. Using data for a Spanish frigate, with standard static routes specified by the ship's designers, computational tests show that the dynamic system can reduce average evacuation times, nearly 23%, and can improve a combined measure of ship integrity by up to 50%. In addition, plausible design changes to the frigate yield further, substantial improvements. Published 2008 Wiley Periodicals, Inc. Naval Research Logistics 2008