This study proposed a concept and a method for building egress analysis. The works of this research include: develop procedures to analyze the egress system of a plan, propose methods and a program to identify target spaces in evacuation, present a dynamic blocking viewpoint of an egress system, dedicate a way to identify the threatening room of fire origin, and create an occupant evacuation model (ESM), whose functions are: to simulate the occupant evacuation in a building in the static and the dynamic blocking situations, to record the people changes at every compartment during evacuation, and to review the clearing times of different compartments.

Thesis (Ph. D.)--University of Massachusetts Amherst, 2009. / Includes bibliographical references (p. 266-272). Print copy also available.

No description available.

Yes / There is an agreement among European countries about the need to achieve efficient, effective and responsive evacuations as part of disaster management. Evacuations face uncertain and dynamic conditions, which often challenge the expectations at the planning stage. This research looks at the adoption of agility in evacuation operations. Managers involved in disaster operations in three countries were interviewed to identify current practices and needs during evacuations. This article looks at the potential of beneficiary engagement, staff and information, cooperation, and fitness for change to incorporate agile practices at each one of the stages of evacuation planning. The purpose is to provide an Agile Evacuation Operations (AEO) evidence-based framework to inform theory and practice. The analysis provided shows that along with current practices it is important to engage the beneficiaries more closely, empower and train the staff to react to unexpected conditions, and take advantage of local knowledge to enhance operations. / The data collection was funded with the support of the European Commission, Directorate-General Home Affairs.

In this research, the issue of evacuating people from large public facilities has been studied. The focus has mostly been on the evacuation of hospitals. For the hospital evacuation planner, it is necessary to know how long it would take to evacuate the premises. To approach this problem, the entire evacuation process has been modeled as a queuing situation using a simulation language called SLAM. The evacuation time is affected by many variables such as the number of elevators in the building, the number of ambulances available to transport patients, and the number of staff available to assist in moving patients. All these variables have been incorporated in the model as servers of the queuing process and the simulation is carried out. The model has been applied to a case study of the evacuation of the Medical College of Virginia Hospitals in Richmond, VA. The sensitivity of the model to different system parameters has been studied and the relationships have been plotted. / Master of Science

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 58-59).

Natural disasters are a part of the ecological system, so they are beyond human control. To reduce devastating effects, researchers in Emergency Management seek to understand the causes and cycles of natural disasters so that warning systems may be improved and better advice may be given to the general public about protecting themselves and their property. Emergency management is a relatively new discipline, so much research is still needed to understand the complex interaction of human activity and the natural environment. Therefore, this study was designed to explore the impact of the 2009 flood on the healthcare system in Fargo, North Dakota, and Moorhead, Minnesota, when many health facilities were evacuated. This research is unique because it examined the simultaneous evacuation of multiple healthcare facilities: two Fargo hospitals, all Fargo nursing homes, and the largest Moorhead nursing home. A qualitative approach was used: 27 in-depth interviews were conducted with leaders of the healthcare facilities and other involved parties (e.g., community officials, ambulance providers, public health personnel) to understand their decisions and actions as a record flood triggered evacuations. The researcher found that (1) the healthcare facilities had done minimal pre-planning and preparation for the flood, even though the area had been threatened by previous flooding, and (2) each facility wasted time and resources by working independently to arrange transportation and to locate alternative healthcare facilities to house their patients. The recommendation is made that healthcare facilities coordinate their efforts during natural disasters.

No-notice incidents occur with no advance notice of time and place. Family members may be separated when a no-notice incident strikes during the daytime. They may seek to gather the household members first and evacuate as a unit, and parents may head in the "wrong" direction to pick up their children from schools/daycare centers. Many previous studies have acknowledged that such behavior exists but few, if any, have examined it in-depth. Additionally, this behavior has rarely been integrated with transportation simulation models of evacuation conditions. As shown through this work, such omissions generate overly optimistic network performance. Acknowledging the behavior also leads to potential network improvements by moving dependents (people being picked up by other household members) to more accessible locations. This study investigated no-notice evacuation household gathering behavior based on 315 interviews conducted in the Chicago metropolitan area, in which interviewees were asked about their evacuation and logistic decisions. The study analyzed household pick-up and gathering behavior from the interviews, developed models to represent the behavior, and integrated the household behavior models with network simulation modeling to examine the effects of household behaviors on network evacuation performance. Logistic regression models were built to predict the probability that parents retrieve children from school in normal and emergency situations. Gender, car availability, and travel distance (between parents and children) were the main influencing factors to determining child-chauffeuring travel behavior, where gender difference appeared to be most prominent. Women are more responsible for picking up children from school than men, and both women and men are more likely to pick up children under emergency conditions compared to a normal situation. A complex model to integrating human behavior analysis and network assignment modeling was presented in this study. The model follows the traditional four step urban transportation planning process and 1) estimates household gathering chains in an evacuation using a discrete choice (Logit) model and sequences chains following the principle of "nearest first", 2) assigns directions of destinations ensuring the least travel time to safe zones from the last stop within the hot zones, 3) applies decision tree based mode choice models to determine the mode used for evacuation, and 4) uses a dynamic assignment method to assign time-varying demand to the network. The whole framework was tested in the Chicago metropolitan region for two hypothetical incidents, one causing a 5-mile evacuation radius and the other a 25-mile radius evacuation. The results showed that considering household gathering behavior will reduce proportions of evacuees who reach safe zones by a certain time period, while not necessarily deteriorating overall network traffic performance. To facilitate the chain-based evacuations, a relocation model is proposed by moving carless dependents of facilities (such as schools and daycare centers) to more accessible locations for pickup; a linear integer program is presented to determine optimal sites. The optimization model uses estimated travel time obtained from a micro-simulation model and a procedure is presented to iterate between the two models (optimization and simulation). The methodology was applied to a sample network based on Chicago Heights, Illinois. The sample application involved four facilities with 780 dependents and three safe time thresholds, i.e., 30, 45 and 60 minutes. The sample application tested two scenarios - no mode shift and mode shift from car to bus - and introduced average speed and the number of successful evacuations of dependents to evaluate the performance of a relocation strategy. The safe evacuation time threshold was quite important for the relocation strategy; when it is adequate, relocating dependents benefits both those picking up dependents and the other vehicles in the network. This dissertation contributes to the fields of evacuation modeling and transportation engineering, in general. This study investigates child pick-up, spouse gathering, and home gathering behavior during hypothetical incidents, and identifies characteristics associated with household decision makers that influence this behavior. The study also presents a model to integrate the behavior with road network simulation modeling; the combined model could be used to investigate the effects of gathering behavior on network traffic performance and identify potential spatial and temporal bottlenecks. Finally, this work explored a strategy to facilitate household pick up chains by relocating facility dependents to more accessible site. The study can support any city evacuation plan development. / Ph. D.

The very high travel demands associated with hurricane evacuations require some strategies, such as contraflow sections, to be included in hurricane evacuation plans. However, the response or reaction of the evacuees to these strategies has not been given much attention in the past. This study concentrated on one particular strategy, contraflow segments, and investigated evacuees' willingness to use them through an animated survey. Usable data was collected from 821 respondents. The first part of the study dealt with six factors (service availability, police presence, exit location, entry congestion, availability of multiple entries, and limited choice) which were studied independently and compared against individual background characteristics. The distribution of the responses from the survey indicated that the presence of multiple entries or the availability of information about services increased the likelihood of evacuees switching to contraflow lanes, while the presence of police personnel for instance did not greatly alter the decision. Other factors like entry congestion or exits well before or well after initially desired ones decreased the willingness to use contraflow lanes. In the case where contraflow lanes were the only option on the main evacuation route (without the regular lane alternative), evacuees were willing to take detours to avoid the use of contraflow facilities. However, the effects of the above listed factors were associated with the background characteristics of the evacuees as the odds ratios in this study indicated. Previous contraflow or reverse lane experience for instance attenuated the effect of entry congestion on avoiding contraflow lanes. Contraflow experience on the other hand increased the likelihood of using the first entry when two entries were available and increased the willingness to switch to contraflow lanes when information about services was provided. Also, evacuation experience, presence of passengers affecting stops, and having dependents in the family improved the willingness to use contraflow lanes given information about services. Other characteristics like living in a hurricane prone area increased the inclination to use contraflow in the presence of police personnel and having passengers affecting destination choice increased the willingness to detour and avoid contraflow when regular lanes were not part of the main evacuation route from the respondent's origin. The second part of the study dealt with congestion and information about congestion levels along the regular and contraflow lanes. Different combinations of levels of congestion and information were presented to the respondents in the animated part of the survey. Respondents indicated their preference for contraflow or regular lanes in these scenarios. This data was used to develop a conditional logit model which predicted choice based on the presented options. Evacuees demonstrated an overall willingness to switch to contraflow lanes when these lanes were less congested than the regular lanes. However, with similar congestion levels on the regular and contraflow lanes, willingness to switch to contraflow lanes decreased as congestion levels increased. Information about upcoming congestion influenced evacuees' route choice decisions. Information motivated switching to contraflow lanes when conveying better downstream conditions along these lanes. Overall, evacuees demonstrated a willingness to benefit from any congestion improvement offered by contraflow lanes as opposed to assumptions in the literature claiming underutilization of these segments due to drivers' discomfort and unfamiliarity. / Master of Science

The numerous man-made disasters and natural catastrophes that menace major communities accentuate the need for proper planning for emergency evacuation. Transportation networks in cities evolve over long time spans in tandem with population growth and evolution of travel patterns. In emergencies, travel demand and travel patterns drastically change from the usual everyday volumes and patterns. Given that most US and Canadian cities are already congested and operating near capacity during peak periods, network performance can severely deteriorate if drastic changes in Origin-Destination (O-D) demand patterns occur during or after a disaster. Also, loss of capacity due to the disaster and associated incidents can further complicate the matter. Therefore, the primary goal when a disaster or hazardous event occurs is to coordinate, control, and possibly optimize the utilization of the existing transportation network capacity. Emergency operation management centres face multi-faceted challenges in anticipating evacuation flows and providing proactive actions to guide and coordinate the public towards safe shelters. Numerous studies have contributed to developing and testing strategies that have the potential to mitigate the consequences of emergency situations. They primarily investigate the effect of some proposed strategies that have the potential of improving the performance of the evacuation process with modelling and optimization techniques. However, most of these studies are inherently restricted to evacuating automobile traffic using a certain strategy without considering other modes of transportation. Moreover, little emphasis is given to studying the interaction between the various strategies that could be potentially synergized to expedite the evacuation process. Also, the absence of an accurate representation of the spatial and temporal distribution of the population and the failure to identify the available modes and populations that are captive to certain modes contribute to the absence of multimodal evacuation procedures. Incorporating multiple modes into emergency evacuation has the potential to expedite the evacuation process and is essential to assuring the effective evacuation of transit-captive and special-needs populations . This dissertation presents a novel multimodal optimization framework that combines vehicular traffic and mass transit for emergency evacuation. A multi-objective approach is used to optimize the multimodal evacuation problem. For automobile evacuees, an Optimal Spatio-Temporal Evacuation (OSTE) framework is presented for generating optimal demand scheduling, destination choices and route choices, simultaneously. OSTE implements Dynamic Traffic Assignment (DTA) techniques coupled with parallel distributed genetic optimization to guarantee a near global optimal solution. For transit evacuees, a Multi-Depots, Time Constrained, Pick-up and Delivery Vehicle Routing Problem (MDTCPD-VRP) framework is presented to model the use of public transit vehicles in evacuation situations. The MDTCPD-VRP implements constraint programming and local search techniques to optimize certain objective functions and satisfy a set of constraints. The OSTE and MDTCPD-VRP platforms are integrated into one framework to replicate the impact of congestion caused by traffic on transit vehicle travel times. A proof-of-concept prototype has been tested; it investigates the optimization of a multimodal evacuation of a portion of the Toronto Waterfront area. It also assesses the impact of multiple objective functions on emergency evacuation while attempting to achieve an equilibrium state between transit modes and vehicular traffic. Then, a large-scale application, including a demand estimation model from a regional travel survey, is conducted for the evacuation of the entire City of Toronto. This framework addresses many limitations of existing evacuation planning models by: 1) synergizing multiple evacuation strategies; 2) utilizing robust optimization and solution algorithms that can tackle such multi-dimensional non deterministic problem; 3) estimating the spatial and temporal distribution of evacuation demand; 4) identifying the transit-dependent population; 5) integrating multiple modes in emergency evacuation. The framework presents a significant step forward in emergency evacuation optimization.