Disaster Evacuation Planning Research Articles

Shelter location–allocation problem for disaster evacuation planning: A simulation optimization approach

Immediately after a major earthquake strikes, a segment of the people in the disaster region must evacuate to relief shelters. If the evacuation proceeds in an efficient and safe manner, many lives can potentially be saved as the effects of secondary factors, e.g., secondary collapses, stampedes, and aftershocks, can largely be mitigated, while at the same time the people taking refuge can quickly gain access to vital relief goods. Formulating the best possible protocols for post-earthquake evacuation is a crucial, yet highly challenging problem considering the profound uncertainty which is present in the post-disaster environment, including the location and degree of infrastructural damage, the number and location of people who need to evacuate, the behavior and psychology of evacuees, etc. In this research, we formulate a two-stage stochastic evacuation simulation model capable of credibly accounting for these uncertainties. We develop a solution methodology to solve the shelter location–allocation problem represented by the two-stage model, finding the optimal location of shelters to be open as the first stage solution and the optimal assignment of evacuees to shelters as the second stage solution to minimize the total expected cost. The cost-based objective function consists of the cost of opening shelters, a deprivation cost component, the cost of trapped evacuees, and the cost of shelters exceeding capacity. In developing this framework, we collaborate with the National Science and Technology Center for Disaster Reduction (NCDR) in utilizing GIS-based probabilistic models of road damage. We apply the proposed framework to run an extensive numerical study and present various valuable observations and insights which can be gained.

A reinforcement learning-based routing algorithm for large street networks

Evacuation planning and emergency routing systems are crucial in saving lives during disasters. Traditional emergency routing systems, despite their best efforts, often struggle to accurately capture the dynamic nature of flood conditions, road closures, and other real-time changes inherent in urban disaster logistics. This paper introduces the ReinforceRouting model, a novel approach to optimizing evacuation routes using reinforcement learning (RL). The model incorporates a unique RL environment that considers multiple criteria, such as traffic conditions, hazardous situations, and the availability of safe routes. The RL agent in this model learns optimal actions through interaction with the environment, receiving feedback in the form of rewards or penalties. The ReinforceRouting model excels in executing prompt and accurate route planning on large road networks, outperforming traditional RL algorithms and shortest-path-based algorithms. A higher safety score and episode reward of the model are demonstrated when compared to these classical methods. This innovative approach to disaster evacuation planning offers a promising avenue for enhancing the efficiency, safety, and reliability of emergency responses in dynamic urban environments.

Evacuation dilemmas of coastal households during cyclone Amphan and amidst the COVID-19 pandemic: a study of the Southwestern region of Bangladesh.

Cyclone Amphan battered the coastal communities in the southwestern part of Bangladesh in 2020 during the COVID-19 pandemic. These coastal communities were experiencing such a situation for the first time and faced the dilemma of whether to stay at home and embrace the cyclone or be exposed to the COVID-19 virus in the cyclone shelters by evacuating. This article intends to explore individuals’ decisions regarding whether to evacuate in response to cyclone Amphan and in light of the risks of the COVID-19 pandemic. Consequently, this study investigated evacuation behaviors among the households and explored the impacts of COVID-19 during the evacuation procedures. We conducted household surveys to collect primary information and undertook 378 samples for interviews at a precision level of 0.05 in fourteen villages. Despite the utmost effort of the government, the results demonstrated that 96.6% of people in the coastal area received a cyclone evacuation order before the cyclone’s landfall, and only 42% of people followed the evacuation order. The majority of households chose to stay at home because of fear of COVID-19 exposure in the crowded shelters. Although half of the evacuees were housed in cyclone shelters, COVID-19 preventive measures were apparently not set in place. Thus, this study will assist in crafting future government policies to enhance disaster evacuation plans by providing insights from the pandemic that can inform disaster management plans in the Global South.

RnR-SMART: Resilient smart city evacuation plan based on road network reconfiguration in outbreak response

• RnR framework is proposed for a road network reconfiguration method that can consider various disaster factors based on open source GIS data. • The proposed model presents a big data processing method for generating an evacuation plan from actual large-scale road network data. • It presents a disaster response system with various paths and safe routs for urban resilience. • Reconfigured road networks improve the efficiency of evacuation plans from raw data. As the frequency of disasters increases worldwide, resilience planning through disaster management has become critical. Disaster managers must make difficult decisions prioritizing various disaster evacuation routes with limited road resources. This study proposes a road network reconfiguration (RnR) framework for disaster evacuation planning. The proposed model proposes a method to reconfigure a road network that can consider various factors based on open-source geographical information systems data. The proposed model first presents a big data processing method for generating an evacuation plan from actual large-scale road network data. This method is adopted for effective routes for large objects. Second, the proposed framework derives routes by disaster risk and is not limited to the minimum route cost, ensuring an optimal safe route according to the degree of risk. As a result, the proposed RnR framework contributes to the resilience of cities by enabling decision-makers and executives in disaster management to design action plans to avoid city risks and conserve human resources.

How Do Cities Flow in an Emergency? Tracing Human Mobility Patterns during a Natural Disaster with Big Data and Geospatial Data Science

Understanding human movements in the face of natural disasters is critical for disaster evacuation planning, management, and relief. Despite the clear need for such work, these studies are rare in the literature due to the lack of available data measuring spatiotemporal mobility patterns during actual disasters. This study explores the spatiotemporal patterns of evacuation travels by leveraging users’ location information from millions of tweets posted in the hours prior and concurrent to Hurricane Matthew. Our analysis yields several practical insights, including the following: (1) We identified trajectories of Twitter users moving out of evacuation zones once the evacuation was ordered and then returning home after the hurricane passed. (2) Evacuation zone residents produced an unusually large number of tweets outside evacuation zones during the evacuation order period. (3) It took several days for the evacuees in both South Carolina and Georgia to leave their residential areas after the mandatory evacuation was ordered, but Georgia residents typically took more time to return home. (4) Evacuees are more likely to choose larger cities farther away as their destinations for safety instead of nearby small cities. (5) Human movements during the evacuation follow a log-normal distribution.

Agent-based discrete-event simulation model for no-notice natural disaster evacuation planning

Over the past century, natural disasters have been often large-scale and overwhelming catastrophes resulting in irreparable and uncontrollable damage. In order to decrease the average evacuation travel time and reduce casualties, as well as improve the medical care for vulnerable populations in natural disasters, it is worthwhile to look at strategic disaster evacuation planning. In this paper, an agent-based discrete-event simulation (ABDES) modeling framework based on an embedded GIS module is developed for making no-notice natural disaster evacuation planning and improving the evacuation strategy periodically by using the proposed simulation model. Furthermore, in order to examine the applicability and extensibility of the proposed integrated GIS-based ABDES modeling framework, we conduct the experiments using several practical scenarios based on the city of San Francisco in California. The proposed evacuation simulation modeling framework can offer decision-makers significant insight on the traffic assignment and the configuration of resources such as evacuation vehicles and relief facilities that are required to complete successfully an evacuation against the no-notice large-scale disasters.

Mapping family connectedness across space and time

Understanding the structure and evolution of family networks embedded in space and time is crucial for various fields such as disaster evacuation planning and provision of care to the elderly. Computation and visualization can potentially play a key role in analyzing and understanding such networks. Graph visualization methods are effective in discovering network patterns; however, they have inadequate capability in discovering spatial and temporal patterns of connections in a network especially when the network exists and changes across space and time. We introduce a measure of family connectedness that summarizes the dynamic relationships in a family network by taking into account the distance (how far individuals live apart), time (the duration of individuals’ coexistence within a neighborhood), and the relationship (kinship or kin proximity) between each pair of individuals. By mapping the family connectedness over a series of time intervals, the method facilitates the discovery of hot spots (hubs) where family connectedness is strong and the changing patterns of such spots across space and time. We demonstrate our approach using a data set of nine families from the US North. Our results highlight that family connectedness reflects changing demographic processes such as migration and population growth.

화재 시 재실자 행동의 상호 작용을 고려한 건물 피난 행태 분석

건축물에 있어 피난 계획은 프로젝트 전반에 걸쳐 고려되어야 할 매우 중요한 요소 중 하나이다. 기존 다양한 연구 및 실제 재난 사례등을 통해 피난의 중요성은 지속적으로 강조되어 왔으며, 사전 대비를 위한 다양한 노력들이 수행되어 왔다. 또한, 실제와 유사한 대응 훈련 준비의 어려움을 극복하고자 시뮬레이션을 통한 해결책 마련이 새로운 대안으로 떠올랐다. 그러나 피난 계획의 경우 시설물 뿐만 아니라 재실자의 특성 또한 신중히 고려되어야 한다. 현실과 가까운 피난 계획의 수립을 위해 본 연구에서는 인간 행태를 고려한 피난 과정을 분석한다. 기존 사회과학 이론에 기초하고 시스템 다이내믹스 모델링을 이용하여, 피난 초기부터 탈출까지 다양한 재실자 그룹의 특성으로 인해 발생하는 요인들을 포함하며, 이에 따른 의사결정, 행동의 변화 등의 분석한다. 이러한 모델을 통해 그룹 형성 및 재실자 간 상호 작용 등 긴급 상황에서 발생하는 인간 행태가 전체 피난 행태 및 결과에 미치는 영향을 파악하며, 향후 피난 시뮬레이터의 모듈로써의 활용 및 시설물 안전 관리자의 피난 계획 수립 시 의사결정의 기초자료를 제공할 것이라 예상된다. Evacuation process has been considered as one of the most important elements to be managed in public facilities. Although the importance is highlighted through numerous literatures, disaster evacuation planning, particularly fire accidents, faces a number of human behavior related limitations for a similar application to different types of facilities/occupants. To overcome the obstacles including complexity in human behaviors, a number of simulation techniques with limited consideration on human behaviors are utilized to predict foreseeable problems in evacuation process. Therefore, this research aims to propose system dynamics models incorporating human behaviors considering different types of occupants under disaster evacuation events. Analysis on emergent human behaviors such as group forming and interactions under urgent situation are conducted based on the main stream theories in social science field. The results suggest the influences of human behavior factors including cooperative intention, information sharing, and mobility change to evacuation behavior. The implications are expected to provide safety consideration at planning/designing phase of buildings and help facility safety managers for evacuation planning with more realistic management approaches.

Modeling Network Impact in Area Surrounding Activity Center Caused by Special Events

Although many traffic prediction models have been studied, much of the existing research considers traffic congestion primarily caused by construction and incidents. An effort to assess the impact of special events (ballgames, parades, conventions, etc.) in an urban area is needed. In this paper, a prototype model for traffic analysis under special events is proposed and tested. Unlike hydrodynamic modeling or the conventional microscopic approach by vehicle tracking, this model tries to decompose the overall system impact into the spatial effect of the special event network (SE network) and the temporal effect of the eventgenerated traffic. The model formulation is shown to possess a unique, physically meaningful solution to the underlying engineering problem. Using systemwide field data for model calibration, preliminary tests have shown encouraging results in predicting traffic impact on SE networks. Although further testing and improvement is needed, the proposed modeling approach has demonstrated its potential for extending to other applications such as disaster evacuation planning.

Disaster Evacuations

This quantitative study may be the first one to compare travelers' reactions to weather-related emergencies (e.g., earthquakes, hurricanes) with the responses of their professional hosts (e.g., hotel GMs, resort operators, campground managers). Telephone interviewers reached 603 people who had experienced such an emergency while traveling, 523 of whom also completed a follow-up questionnaire. Those responses were then compared to an existing data base of 185 managers' reactions to and preparations for public emergencies (including evacuation). For the most part, guests had a substantially different view of the managers' roles and responsibilities related to evacuations when compared to what steps and provisions the managers themselves felt obligated to provide. For example, one survey item asked about managers' disaster-evacuation planning. Almost two out of every three managers believed that preparations were adequate, while only half of the customers thought so. Another item addressed whether managers would call for an evacuation if not directly ordered to do so by local officials. Few customers (17 percent) believed that GMs would wait until forced to evacuate, yet more than a third of the managers agreed that that was their policy. Additional items show similar if less dramatic gaps between travelers' and managers' perceptions of what to do, and when, during an emergency. These include whether the hotel or resort is obligated to provide special services such as assistance for the disabled, road-evacuation directions, and food and water.

Disaster evacuations: tourist-business managers rarely act as customers expect

This quantitative study may be the first one to compare travelers' reactions to weather-related emergencies (e.g., earthquakes, hurricanes) with the responses of their professional hosts (e.g., hotel GMs, resort operators, campground managers). Telephone interviewers reached 603 people who had experienced such an emergency while traveling, 523 of whom also completed a follow-up questionnaire. Those responses were then compared to an existing data base of 185 managers' reactions to and preparations for public emergencies (including evacuation). For the most part, guests had a substantially different view of the managers' roles and responsibilities related to evacuations when compared to what steps and provisions the managers themselves felt obligated to provide. For example, one survey item asked about managers' disaster-evacuation planning. Almost two out of every three managers believed that preparations were adequate, while only half of the customers thought so. Another item addressed whether managers would call for an evacuation if not directly ordered to do so by local officials. Few customers (17 percent) believed that GMs would wait until forced to evacuate, yet more than a third of the managers agreed that that was their policy. Additional items show similar if less dramatic gaps between travelers' and managers' perceptions of what to do, and when, during an emergency. These include whether the hotel or resort is obligated to provide special services such as assistance for the disabled, road-evacuation directions, and food and water.

Disaster planning and response by tourist business executives

The tourist industry represents a disaster vulnerability of catastrophic potential. Disaster evacuation planning is one strategy for mitigating this vulnerability. Based on intensive interviews with executives responsible for 185 tourist businesses, this article reports the first empirical data base for answering five questions: (1) What factors stimulated their disaster evacuation planning? (2) What model patterns described the planning processes used? (3) How much planning had been done? (4) What modal patterns described their disaster evacuation decision-making process? (5) What are the lessons? The key conclusion is that the tourist industry must respond proactively to a rapidly expanding vulnerability through both internal firm-specific disaster planning initiatives and partnerships to ensure adequate levels of community response capacity. Failure to do so will keep an expanding tourist population at risk. This, in turn, threatens future customer relations that may place such businesses in jeopardy.

The cell transmission model, part II: Network traffic

This article shows how the evolution of multi-commodity traffic flows over complex networks can be predicted over time, based on a simple macroscopic computer representation of traffic flow that is consistent with the kinematic wave theory under all traffic conditions. The method does not use ad hoc procedures to treat special situations. After a brief review of the basic model for one link, the article describes how three-legged junctions can be modeled. It then introduces a numerical procedure for networks, assuming that a time-varying origin-destination (O-D) table is given and that the proportion of turns at every junction is known. These assumptions are reasonable for numerical analysis of disaster evacuation plans. The results are then extended to the case where, instead of the turning proportions, the best routes to each destination from every junction are known at all times. For technical reasons explained in the text, the procedure is more complicated in this case, requiring more computer memory and more time for execution. The effort is estimated to be about an order of magnitude greater than for the static traffic assignment problem on a network of the same size. The procedure is ideally suited for parallel computing. It is hoped that the results in the article will lead to more realistic models of freeway flow, disaster evacuations and dynamic traffic assignment for the evening commute.

Disaster Responses within the Tourist Industry

Reflecting a series of converging international trends, the tourist industry represents a vulnerability of catastrophic potential. Interview and questionnaire data obtained from 185 owners or managers in nine U.S.A. communities, provide answers to five questions: (1) What is the extent of disaster evacuation planning? (2) What factors account for the variations in this planning? (3) What behavioral patterns occur during actual evacuations? (4) What factors account for these pattern variations? and (5) What are the policy implications of these behavioral assessments? While many larger firms managed by more professional staff have completed extensive disaster evacuation planning, the overall record in very spotty. Hence, major initiatives both within the industry, and by emergency managers at all levels of government, are needed to reduce this rapidly expanding vulnerability.

Variations in Disaster Evacuation Behavior: Public Responses Versus Private Sector Executive Decision‐Making Processes

Data obtained from 65 executives working for tourism firms in three sample communities permitted comparison with the public warning response literature regarding three topics: disaster evacuation planning, initial warning responses, and disaster evacuation behavior. Disaster evacuation planning was reported by nearly all of these business executives, although it was highly variable in content, completeness, and formality. Managerial responses to post-disaster warnings paralleled the type of complex social processes that have been documented within the public response literature, except that warning sources and confirmation behavior were significantly affected by contact with authorities. Five key areas of difference were discovered in disaster evacuation behavior pertaining to: influence of planning, firm versus family priorities, shelter selection, looting concerns, and media contacts.

Anticipating Organizational Evacuations: Disaster Planning by Managers of Tourist-Oriented Private Firms

Every year thousands of people temporarily relocate prior to the threat of major disasters. Social science research has been applied to enhance the effectiveness of multiorganizational warning systems. Much remains unknown, however. This paper presents findings from the first major study of disaster evacuation planning and decision making behavior by business executives responsible far tourist oriented firms. Two questions are explored: (1) What is the extent of disaster evacuation planning? and (2) What factors account for the variation in these planning initiatives? Data were collected in three communities with large tourist industries through interviews with 65 owners or managers of tourist oriented firms. While a limited degree of planning has occurred, the overall portrait indicated serious shortfalls. Although individual and community characteristics were relevant, organizational qualities accounted for most of the variation in disaster evacuation planning.