No-notice Evacuation Research Articles

Planning evacuation orders under evacuee compliance uncertainty

In this study, we explore how short- and no-notice evacuation instructions may be designed by a risk-averse emergency management body, explicitly considering varying levels of evacuee compliance and responses to these instructions in the design. The population compliance rate, or its distribution, are unlikely to be known; even a small error in estimating either could lead to drastically worse outcomes. Our solution, which is based on the idea of hedging, determines optimal evacuation instructions in a range of possible scenarios. As part of the proposed solution algorithm, we utilize conditional-value-at-risk (CVaR) and stochastic optimization paradigms to demonstrate how and when compliance uncertainty is a critical input for improved evacuation instructions. Our findings show that in situations where compliance rates are low or highly uncertain, relying solely on highly risk-averse strategies is unlikely to deliver efficient outcomes in comparison to a naïve or no-information approach (where instructions are designed assuming 100% compliance). Although accounting for compliance uncertainty in designing evacuation instructions can be highly beneficial, the added benefits are realized beyond certain population compliance rate levels and uncertainty ranges. This work provides insights into how emergency managers can best overcome non-compliance to instruction, the benefits which are realized together with efforts to promote compliance (community education initiatives and improved communication mechanisms).

Modeling a Risk-Based Dynamic Bus Schedule Problem under No-Notice Evacuation Incorporated with Dynamics of Disaster, Supply, and Demand Conditions

Apart from private traffic, the evacuation of transit-dependent population is also an essential component of emergency preparedness, especially under no-notice evacuation scenarios with limit evacuation horizon. In literature, most bus-based evacuation models for no-notice evacuation are established under implicit assumptions of uniform evacuation horizon among different pick-up locations or fixed bus fleet in the evacuation area. These constraints will distance their models from real-world situations, where evacuation horizon is various due to spatial distribution of pick-up locations and fleet size of bus available for allocation will increase over time in no-notice evacuation. This research presents a risk-based bus schedule model which is differentiated from the vehicle routing problem (VRP) and bus evacuation problem (BEP) in literature, including the objective and the time-dependent parameters. A quantified definition of evacuation risk for pick-up location with concerns of disaster dynamics and time-varying supply-demand conditions is proposed in this paper as a criterion for bus allocation, also acting as a reflection of social equity to some extent. A notion of time-evolving disadvantageous evacuation units (DEU) is introduced to represent the pick-up locations selected for bus allocation with limited resource. The binary integer linear programming (BILP) named risk-based bus schedule model incorporated with DEU notion can provide a reference for resource allocation in stage of both evacuation planning and operation for transit-dependent population. The proposed model structure can effectively capture the changes of evacuation risk among pick-up locations over time to realize real-time bus schedule. Numerical experiments are conducted using the transportation network of the city of Xi’an, China, to test the performance of the model. The applicability and comparison of different bus evacuation models are also discussed in this paper. This research provides insights into dealing with disaster dynamics and time-varying supply conditions in realistic bus-based no-notice evacuation operations.

Impacts of information from various sources on the evacuation decision-making process during no-notice evacuations in campus environment

This article studies the impacts of disaster- and evacuation-related information from various information sources on university campus community members’ evacuation decision-making process during no-notice evacuations. These information sources include emergency notification system (ENS) on campus, people nearby, and social networking services (SNS). A survey is conducted to address these questions using participants recruited from the West Lafayette Campus of Purdue University (United States of America), including students, staff and faculty members. Descriptive statistics and structural equation model estimation results show that information from sources with higher perceived credibility has a larger impact on participants’ evacuation-related decisions compared to those with lower ones. The study suggests the importance of increasing the credibility and number of followers of the SNS account used by ENS to enable the use of SNS as a complementary low-cost solution to more effectively disseminate disaster- or/and evacuation-related information to ensure that people’s actions enhance their safety.

Use of Shared-Mobility Services to Accomplish Emergency Evacuation in Urban Areas via Reduction in Intermediate Trips—Case Study in Xi’an, China

Under no-notice evacuation scenarios with limited time horizons, the effectiveness of evacuation can be negatively impacted by intermediate trips that are made by family members and the identification of vulnerable populations. The emergence of shared-mobility companies, such as Uber and DiDi, can be considered as a potential means to address above-mentioned concerns. The proposed study explores the utility of shared-mobility services under emergency-evacuation scenarios and makes recommendations to relevant bodies that are based on the obtained and they are discussed herein. The study investigates attitudes of the public, experts, and drivers towards the use of shared-mobility resources during emergency evacuations based on a stated preference survey. Results of questionnaires, driver interviews, and face-to-face expert interviews have been analyzed to validate the feasibility and identify potential problems of leveraging shared-mobility services during evacuation response, especially in metropolitan areas wherein such services are already ubiquitous. Numerical simulations have been performed to quantify potential improvements in the total trip distance and number of evacuees after incorporating the use of shared mobility into emergency-response operations. However, despite the observed improvement in emergency efficiency, certain realistic roadblocks must be overcome. Realization of the proposed objective heavily depends on actionable policy recommendations, provided herein as a reference for the government, emergency management agencies, and shared-mobility companies.

Modeling Road Network Vulnerability for Evacuees and First Responders in No-Notice Evacuation

The concept of vulnerability has been employed to develop transport systems that sustain devastating disasters and ensure the efficient evacuation of neighborhoods. Existing studies of road network vulnerability overlook two important aspects of analysis: the no-notice evacuation and the different objectives of evacuees and first responders. First, a no-notice evacuation leaves limited time for proactive emergency planning; therefore, rescue strategies in this scenario rely heavily on real-time traffic information. Second, the goal of first responders in an evacuation is to move into an affected area immediately after a hazardous event unfolds, and the risk they face differs from that of evacuees. To this end, this paper develops a network-based model to evaluate vulnerability during a no-notice evacuation and applies it to a case study in Dublin, OH, USA. The model is suited to assessing network vulnerability in response to events with uncertainty and coordinating traffic control strategies in a no-notice evacuation. This study can become a valuable complement to the methodological conceptualization of vulnerability and can provide insights into developing comprehensive emergency management plans.

A Case Study on the Impacts of Connected Vehicle Technology on No-Notice Evacuation Clearance Time

No-notice evacuations of metropolitan areas can place significant demands on transportation infrastructure. Connected vehicle (CV) technology, with real-time vehicle to vehicle and vehicle to infrastructure communications, can help emergency managers to develop efficient and cost-effective traffic management plans for such events. The objectives of this research were to evaluate the impacts of CVs on no-notice evacuations using a case study of a downtown metropolitan area. The microsimulation software VISSIM was used to model the roadway network and the evacuation traffic. The model was built, calibrated, and validated for studying the performance of traffic during the evacuation. The researchers evaluated system performance with different CV penetration rates (from 0 to 30 percent CVs) and measured average speed, average delays, and total delays. The findings suggest significant reductions in total delays when CVs reached a penetration rate of 30 percent, albeit increases in delays during the beginning of the evacuation. Additionally, the benefits could be greater for evacuations that last longer and with higher proportions of CVs in the vehicle stream.

Development and implementation of algorithms for vehicle routing during a no-notice evacuation

AbstractThis article develops and implements time-dependent shortest path and assignment algorithms for vehicle routing and assignment during a no-notice evacuation. A time-dependent shortest path algorithm with arc labeling is designed to improve computer storage space efficiency. Visual Basic for Application (VBA) is used to improve time efficiency of both shortest path and assignment algorithms. Performance of the algorithms is analyzed and compared through implementation in VBA and the General Algebraic Modeling System (GAMS). Since VBA seamlessly integrates with Microsoft Excel and enables efficient data manipulation, the algorithms implemented in VBA are more efficient and obtain optimal solutions faster than those implemented in the GAMS. The shortest path algorithm with arc labeling implemented in VBA may be used for real-time vehicle routing for large road networks during no-notice evacuations.

Bus Routing in the No-notice Network Emergency Evacuation for Transit Dependent Residents

Bus Routing in the No-notice Network Emergency Evacuation for Transit Dependent Residents

Evacuation of the ICU: Care of the Critically Ill and Injured During Pandemics and Disasters: CHEST Consensus Statement

Despite the high risk for patient harm during unanticipated ICU evacuations, critical care providers receive little to no training on how to perform safe and effective ICU evacuations. We reviewed the pertinent published literature and offer suggestions for the critical care provider regarding ICU evacuation. The suggestions in this article are important for all who are involved in pandemics or disasters with multiple critically ill or injured patients, including front-line clinicians, hospital administrators, and public health or government officials. The Evacuation and Mobilization topic panel used the American College of Chest Physicians (CHEST) Guidelines Oversight Committee's methodology to develop seven key questions for which specific literature searches were conducted to identify studies upon which evidence-based recommendations could be made. No studies of sufficient quality were identified. Therefore, the panel developed expert opinion-based suggestions using a modified Delphi process. Based on current best evidence, we provide 13 suggestions outlining a systematic approach to prepare for and execute an effective ICU evacuation during a disaster. Interhospital and intrahospital collaboration and functional ICU communication are critical for success. Pre-event planning and preparation are required for a no-notice evacuation. A Critical Care Team Leader must be designated within the Hospital Incident Command System. A three-stage ICU Evacuation Timeline, including (1) no immediate threat, (2) evacuation threat, and (3) evacuation implementation, should be used. Detailed suggestions on ICU evacuation, including regional planning, evacuation drills, patient transport preparation and equipment, patient prioritization and distribution for evacuation, patient information and tracking, and federal and international evacuation assistance systems, are also provided. Successful ICU evacuation during a disaster requires active preparation, participation, communication, and leadership by critical care providers. Critical care providers have a professional obligation to become better educated, prepared, and engaged with the processes of ICU evacuation to provide a safe continuum of critical care during a disaster.

Modeling and Assessment of Crossing Elimination for No-Notice Evacuations

Crossing elimination is a relatively recent strategy that emergency managers and departments of transportation may consider during no-notice evacuations. In this strategy, certain intersection movements that may be permissible under normal operating conditions are prohibited so that arterial traffic flow will increase. A few previous studies examined this strategy with contraflow operations. However, the benefits of crossing elimination alone remain unclear. An assessment of the effects of intersection crossing elimination during evacuations helps fill this knowledge gap. A simulation–optimization model was developed to determine the near-optimal configuration of intersection movements from a set of pre-specified possible configurations for intersections in a given area. At the optimization level, the total travel time of evacuees was minimized, and at the lower level, all traffic was assigned to the network with DYNUST traffic assignment simulation software. A simulated annealing heuristic was used to solve the optimization problem. The entire method was applied to a real network to assess the impact of crossing elimination. Three scenarios were developed with combinations of evacuee destination and departure time distributions. Results for these scenarios indicated that total evacuee travel time was improved by about 3% to 5% (9,700 to 11,200 h for about 300,000 evacuees). The availability of through movements and the elimination of merging points were the two factors influencing the selection of modified configurations for intersection movement.

Wildfire Evacuation Scenario in Colorado

In late 2010, the City of Colorado Springs and the Pikes Peak Area Council of Governments in Colorado completed a cooperative wildfire evacuation planning process. The process was supported by the simulation of wildfire evacuation scenarios with an adaptation of the Council of Governments’ four-step travel model. The adapted model was used to assess times to evacuate, identify choke points, and develop traffic control plans for identified at-risk neighborhoods. Evacuation simulations used a worst-case scenario in which the wildfire event took place during the p.m. peak traffic hour, and affected households were included in both background commuter traffic and neighborhood evacuation traffic. Link-based hourly volume-to-capacity ratios were used as a metric to estimate times to evacuate and to identify egress bottlenecks. Route closures, route restrictions, no-entry restrictions, and contraflow operations were evaluated as measures for inclusion in neighborhood-level traffic control plans. On Tuesday, June 26, 2012, the simulated worst case became reality. More than 34,000 persons were evacuated during the event, including 26,000 during the 6-h period between 15:30 and 21:30. Before the wildfire was fully contained, 18,247 acres had burned, 347 homes and other structures had been destroyed, and two people had died. That the no-notice, mandatory evacuation was as successful as it was can be attributed to extensive advance planning, the accuracy of modeled evacuation simulations, and the effectiveness of the final traffic control plans. This study examined how the model results were borne out by actual experience. Recommendations to improve no-notice evacuation planning from the perspective of lessons learned are presented.

Assumptions and Processes for the Development of No-Notice Evacuation Scenarios for Transportation Simulations

Emergency management agencies and departments of transportation benefit from transportation simulation support when developing their emergency response or evacuation plans. No-notice events are increasingly becoming part of these plans. Few, if any, studies have shown how to operationalize general no-notice evacuation considerations. To fill this gap, this article describes essential features and reasonable assumptions that should be considered in the development of no-notice evacuation scenarios for use in conjunction with transportation simulation models. Although the information presented here centers on a specific location and disaster, the concepts may be generalized and adapted for use in other locations and hazards and are of value to both practitioners as well as researchers seeking to develop similar models.

No-Notice Evacuation Management

To promote smoother freeway traffic flow during evacuations, ramps may be closed and thus reduce the number of merging and related speed reduction points. Deciding which ramps to close can be treated as an optimization problem in which the decision variables are integers that indicate whether the ramp is open or closed. This paper examines the problem under multiple demand and budget scenarios for no-notice evacuations. Through the optimization formulation and solution method, optimized closure plans are developed for each scenario and compared with the do-nothing case, and an existing plan is developed with professional judgment. The optimized plans outperform the others in the evacuees' total travel time but are sometimes associated with decreases in overall network throughput. Three ramp closures, consistent across the scenarios, are explored as a reduced closure plan, and evacuee benefits are identified for all of the scenarios over the do-nothing option except in the most congested background traffic scenario. However, even in the most congested case, the three-ramp closure plan improved evacuees' travel times over the plan developed without analytical and simulation support. Although the exact optimized ramp closure plan varies across scenarios and budgets, overlap of the plans can help generate a smaller closure plan that provides benefits over plans that are strictly judgment based and over the do-nothing option in less congested cases.

Household No-Notice Evacuation Logistics: How Well Do Households Optimize?

In no-notice events, adults must decide whether and how to gather household dependents. This article examines how effectively households plan their evacuation logistics for a daytime event in a multimodal network and how these plans match the outcomes of a nonlinear integer optimization approach that simultaneously determines optimal meeting locations, final destinations, and family member pickup assignment and sequencing. The model outcomes are compared to information from 59 in-depth interviews. Households largely assign emergency-gathering activities to the parent normally responsible for child-related travel and prefer to meet at home; these decisions are optimal only in some cases. The authors also identify the sensitivity of the optimized logistics to the time adults spend at pickup locations gathering their dependents and “break-even” points where a combination of walking and trains become competitive with personal vehicles. For some households, the additional travel time to make these modes competitive is fewer than 2 h, which is not necessarily an unexpected delay during evacuations. Thus, emergency management agencies should continue to include transit agencies in their planning process and ensure that employees are available to provide services for cases where severe congestion is encountered, and not just for socioeconomically vulnerable populations.

An aggregate approach to model evacuee behavior for no-notice evacuation operations

This study proposes an aggregate approach to model evacuee behavior in the context of no-notice evacuation operations. It develops aggregate behavior models for evacuation decision and evacuation route choice to support information-based control for the real-time stage-based routing of individuals in the affected areas. The models employ the mixed logit structure to account for the heterogeneity across the evacuees. In addition, due to the subjectivity involved in the perception and interpretation of the ambient situation and the information received, relevant fuzzy logic variables are incorporated within the mixed logit structure to capture these characteristics. Evacuation can entail emergent behavioral processes as the problem is characterized by a potential threat from the extreme event, time pressure, and herding mentality. Simulation experiments are conducted for a hypothetical terror attack to analyze the models’ ability to capture the evacuation-related behavior at an aggregate level. The results illustrate the value of using a mixed logit structure when heterogeneity is pronounced. They further highlight the benefits of incorporating fuzzy logic to enhance the prediction accuracy in the presence of subjective and linguistic elements in the problem.

Internet-based stated response survey for no-notice emergency evacuations

Large-scale evacuations from major cities during no-notice events - such as chemical or radiological attacks, hazardous material spills, or earthquakes - have an obvious impact on large regions rather than on just the directly affected area. The scope of the impact includes the accommodation of emergency evacuation traffic throughout a very large area and the planning of resources to respond appropriately to the needs of the affected population. Compared to events with advance notice, such as evacuations based on hurricanes approaching an affected area, the response to no-notice events relies exclusively on pre-planning and general regional emergency preparedness. In this paper we present the design, methodology and results of a survey which was conducted in order to obtain empirical data on individuals' responses to no-notice evacuation which can be used to calibrate an evacuee behavior model for planning purposes. The results of the survey show that people are more likely to evacuate if they see others evacuating and whether the evacuation ordered or recommended making little difference. When the event risk is moderate evacuees are more likely to evacuate to a shelter than when the risk is high, in this case people are more likely to evacuate to friends or family house and hotels. The area covered in the sample mostly includes the Chicago Metropolitan Area. However, we argue that the regional differences in the response to a no-notice evacuation are likely to be negligible, in contrast to advanced-notice evacuations where conditioning may occur. Thus, the results of the survey could be applicable nation-wide.

Analysis of child pick-up during daily routines and for daytime no-notice evacuations

In a no-notice disaster (e.g., nuclear explosion, terrorist attack, or hazardous materials release), an evacuation may start immediately after the disaster strikes. When a no-notice evacuation occurs during the daytime, household members are scattered throughout the regional network, and some family members (e.g., children) may need to be picked up. This household pick-up and gathering behavior was seldom investigated in previous work due to insufficient data; this gap in our understanding about who within families handles child-gathering is addressed here. Three hundred fifteen interviews were conducted in the Chicago metropolitan area to ascertain how respondents planned their response to hypothetical no-notice emergency evacuation orders. This paper presents the influencing factors that affect household pick-up and gathering behavior/expectations and the logistic regression models developed to predict the probability that parents pick up a child in three situations: a normal weekday and two hypothetical emergency scenarios. The results showed that both mothers and fathers were more likely to pick up a child under emergency conditions than they were on a normal weekday. For a normal weekday, increasing the distance between parents and children decreased the probability of parents picking up children; in other words, the farther parents are from their children, the less likely they will pick them up. In an emergency, effects of distance on pick-up behavior were significant for women, but not significant for men; that is, increasing the distance between parents and children decreased the probability that mothers pick up a child, but had a less significant effect on the fathers’ probability. Another significant factor affecting child pick-up behavior/expectations was household income when controlling for distance. The results of this study confirm that parents expect to gather children under emergency conditions, which needs to be accounted for in evacuation planning; failure to do so could cause difficulties in executing the pick-ups, lead to considerable queuing and rerouting, and extend the time citizens are exposed to high levels of risk.

Critical Intersection Signal Optimization During Urban Evacuation Utilizing Dynamic Programming

Despite advancements in the field of traffic planning and operations, many major cities still rely on pretimed signal settings. With only pretimed signal control strategies, the secondary effects of a terror attack are magnified by slow evacuation times resulting in further loss of life. However, the cost of implementing new infrastructure based solely on the chance of a no-notice evacuation is not something that city planners are willing to do. The purpose of the research is to define a cost-effective methodology to develop pretimed signal control strategies to assist evacuations in urban areas. To that end, a dynamic programming methodology was developed to assist critical intersections in urban corridors. To test this methodology, a microscopic traffic-simulation environment was created for a case study of a 10 intersection evacuation corridor in Washington, DC. Using the proposed methodology to optimizing signal splits of a critical intersection within an evacuation corridor, evacuation clearance time was reduced by approximately 1 h. Furthermore, this formulation can be used to develop pretimed signal control settings for evacuation scenarios. Results showed that peak-hour signal timings are not sufficient in the case of an emergency, and signal timing plans must be tailored for emergency evacuation.

Relocating Children in Daytime No-Notice Evacuations

Under no-notice conditions in which family members are collecting dependents, the geographic location and the characteristics (e.g., the number of entrances and exits) of the pickup points become factors crucial to efficient evacuation. This paper presents a linear integer mathematical program for facilities to relocate dependents who need to be picked up in an optimal manner. The program is iterated with a traffic simulation model to obtain an optimal set of locations to which dependents are relocated, on the basis of anticipated travel times. The entire methodology is applied to a sample network based on the Chicago Heights, Illinois, network with three safety time thresholds. The results indicated that the safe evacuation time threshold is important to the relocation strategy. When the safe evacuation time threshold is adequate, the relocation of dependents increases the number of successful evacuees and increases the average travel speed of the network; it also significantly benefits those who rely on public transit to evacuate because new sites are closer to bus stops and walking times to those stops are reduced. Application of the proposed methodology can assist local decision makers with taking effective measures during no-notice evacuations, and the relocation sites could be part of local evacuation management plans.

Optimizing the use of public transit system during no-notice evacuation of urban areas

This paper proposes a methodology that can be used to design plans for evacuating transit-dependent citizens during no-notice disasters. A mixed-integer linear program is proposed to model the problem of finding optimal evacuation routes. The objective of the problem is to minimize the total evacuation time and the number of casualties, simultaneously. A traffic simulation package is used to explicitly incorporate the traffic flow dynamics into our model in order to generate solutions which are consistent with the dynamics of traffic network. Due to the long running time of CPLEX, a Tabu search algorithm is designed that finds evacuation routes for transit vehicles. Computational experiments demonstrate that the solutions found are of high-quality. Numerical experiments are conducted using the transportation network of the city of Forth Worth, TX to illustrate the modeling procedure and solution approach.