Download or read book A Hurricane Evacuation Computer Model for the US Virgin Islands written by Virgin Islands Territorial Emergency Management Agency and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hurricane Evacuation Study for the United States Virgin Islands written by Virgin Islands Territorial Emergency Management Agency and published by . This book was released on 1994 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Hurricane Evacuation Computer Model for the Cedar Key Region Florida written by Florida. Department of Community Affairs and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hurricane Evacuation Study for the United States Virgin Islands written by United States. Army. Corps of Engineers. Jacksonville District and published by . This book was released on 1994 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling Hurricane Evacuation Traffic written by Haoqiang Fu and published by . This book was released on 2006 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Little attention has been given to estimating dynamic travel demand in transportation planning in the past. However, when factors influencing travel are changing significantly over time - such as with an approaching hurricane - dynamic demand and the resulting variation in traffic flow on the network become important. In this study, dynamic travel demand models for hurricane evacuation were developed with two methodologies: survival analysis and sequential choice model. Using survival analysis, the time before evacuation from a pending hurricane is modeled with those that do not evacuate considered as censored observations. A Cox proportional hazards regression model with time-dependent variables and a Piecewise Exponential model were estimated. In the sequential choice model, the decision to evacuate in the face of an oncoming hurricane is considered as a series of binary choices over time. A sequential logit model and a sequential complementary log-log model were developed. Each model is capable of predicting the probability of a household evacuating at each time period before hurricane landfall as a function of the household's socio-economic characteristics, the characteristics of the hurricane (such as distance to the storm), and policy decisions (such as the issuing of evacuation orders). Three datasets were used in this study. They were data from southwest Louisiana collected following Hurricane Andrew, data from South Carolina collected following Hurricane Floyd, and stated preference survey data collected from the New Orleans area. Based on the analysis, the sequential logit model was found to be the best alternative for modeling dynamic travel demand for hurricane evacuation. The sequential logit model produces predictions which are superior to those of the current evacuation participation rate models with response curves. Transfer of the sequential logit model estimated on the Floyd data to the Andrew data demonstrated that the sequential logit model is capable of estimating dynamic travel demand in a different environment than the one in which it was estimated with reasonable accuracy. However, more study is required on the transferability of models of this type, as well as the development of procedures that would allow the updating of transferred model parameters to better reflect local evacuation behavior.
Download or read book Hurricane Evacuation Model written by Robert William Hopkins and published by . This book was released on 1976 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hurricane Evacuation Modeling written by Kun Yang and published by . This book was released on 2018 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation describes a new computational framework to support hurricane evacuation order decision-making. The integrated scenario-based evacuation (ISE) framework explicitly captures the dynamics, uncertainty, and human-nature system interactions that are fundamental to the challenge of hurricane evacuations but have not been fully captured in previous formal evacuation models. The ISE framework recommendations offer an advance in the state-of-the-art because they: (a) are based on integrated hazard assessment, (b) explicitly balance the aims of minimizing risk and minimizing travel time, (c) offer a well-hedged solution that is robust under the range of ways the hurricane may evolve, and (d) leverage the substantial value of increasing information (or decreasing degree of uncertainty) over the course of a hurricane event. ☐ The ISE framework was developed by an interdisciplinary research team. The contributions of this dissertation specifically are summarized as follows. First, this dissertation introduces scenario-based hazard trees, a new tool that describes the resolution over time of uncertainty in impacts of a hurricane. The primary input is a scenario ensemble, commonly developed as part of a hurricane forecast. Repeated application of a linear integer program transforms the ensemble into a tree. The hazard trees provide a new dynamic way to characterize how uncertainty changes during the course of a hurricane, potentially useful information for emergency managers. The scenario tree that is an intermediate product of the method is a required input for the multi-stage stochastic programming evacuation model in the ISE framework. ☐ Second, three full-scale case studies of the ISE framework are conducted for the eastern half of North Carolina and Hurricane Isabel (2003) with the aim of improving understanding and management of hurricane evacuations. The first case study demonstrates the major benefits of the ISE framework after calibrating and improving the first version of it. Results suggest the multi-stage stochastic plans can efficiently reduce risk for severe scenarios without increasing travel time for scenarios that cause little impact. Emergency managers can run the framework once to generate adaptive plans that are robust for all possible scenarios. ☐ The second case study compares various evacuation decision approaches, including deterministic, robust, adaptive, and repeated planning. It provides new knowledge in dealing with hurricane development uncertainty and hurricane forecast uncertainty. Results indicate that robust, adaptive, and repeated planning should improve the performance of evacuation plan by reducing both number of people at risk and unnecessary evacuation orders and travel time. The magnitude of benefits depends on characteristics of a particular hurricane. ☐ The third case study analyzes the impacts of incorporating inland flooding on evacuation order recommendations and performance of evacuation plans. Results provide insight into managing hurricane evacuation with inclusion of inland flooding. Inland flooding can bring travel risk to evacuees from coastal zones, and the risk may be even higher than their stay-at-home risk. Therefore, incorporation of inland flooding in evacuation order decision-making may influence order issuance and timing in coastal regions. In addition, evacuations from inland zones can efficiently reduce total risk without substantial increase in total travel time since inland zones are close to safety.
Download or read book Computer Simulation of Evacuation Plans for Hurricane flood Emergencies written by Antoine G. Hobeika and published by . This book was released on 1985 with total page 3 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling Hurricane Evacuation Traffic written by Chester G. Wilmot and published by . This book was released on 2006 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: The test was conducted by estimating the models on a portion of evacuation data from South Carolina following Hurricane Floyd, and then observing how well the models reproduced destination choice at the county level on the remaining data. The tests showed the models predicted destination choice on the remaining data with similar accuracy. The Gravity Model predicted evacuation to friends or relatives in 110 different counties with an average error of 1.55 evacuations over all destinations, while the corresponding error for the IOM was 1.64. For evacuation to hotels or motels in 70 different counties, the Gravity Model gave an average error of 1.48 evacuations and the IOM an average error of 1.50. However, when the IOM was modified to make the sequencing of opportunities sensitive to the direction of evacuation relative to the path of the storm, the modified IOM performed slightly better than the Gravity Model with average errors of 1.55 and 1.43 evacuations to friends and relatives, and motels and hotels, respectively. The transferability of the Gravity Model for evacuations to friends and relatives was also tested in this study by applying the model estimated on the Hurricane Floyd data in South Carolina to data from Hurricane Andrew in Louisiana. Transferability was tested by comparing the trip length frequency distributions from the two data sets, the similarity of friction factors from models estimated on each data set, and the ratio of the Root-Mean Square-Error (RMSE) of destination predictions of a locally-estimated model to a transferred model on the Andrew data. No significant statistical difference was found between the trip length frequency diagrams or the sets of friction factors at the 95 percent level of significance. The ratio of RMSEs on the Andrew data was 0.67, indicating that the average error of a locally-estimated model was 67 percent that of the transferred model.
Download or read book Modeling Destination Choice in Hurricane Evacuation with an Intervening Opportunity Model written by Bin Chen and published by . This book was released on 2005 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hurricane Evacuation written by Vinayak V. Dixit and published by . This book was released on 2008 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Development of a Large scale Traffic Simulation Model for Hurricane Evacuation written by Siddharth Sharma and published by . This book was released on 2008 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Hurricanes are one of the most catastrophic events resulting in severe consequences including loss of life and property damage. Emergency management teams play a huge role in safeguarding the lives of people in endangered areas by evacuating them to safer locations as efficiently as possible. This study was undertaken to evaluate the traffic control plan (TCP), for the Hampton Roads region of Virginia, and the performance of the designated evacuation routes using large-scale traffic simulation models. Road network was coded in a state-of the- art microscopic simulation program, VISSIM. The emergency evacuation plan for the study area was evaluated by simulating the various evacuation scenarios as described in the abbreviated transportation model (ATM) for Hampton Roads region. The study area comprised of the following nine evacuation areas - cities of Virginia Beach, Norfolk, Chesapeake, Portsmouth, Suffolk, Hampton, Newport News, Poquoson, and York. The following objectives were achieved in this research - 1) estimated the traffic performance of evacuation routes and other major arterial streets, 2) located the major bottlenecks, congestion, or other operational difficulties in the areas covered by the network, 3) estimated the total network evacuation time, 4) conducted what-if scenarios (e.g., incident occurrences), and 5) recommended amendments to the TCP to improve the traffic performance.
Download or read book Hurricane Evacuation Modeling written by Lei Fang (Engineer) and published by . This book was released on 2013 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hurricane evacuation has attracted renewed emphasis since hurricane Katrina in 2005. Every coastal state is establishing their evacuation guidelines and searching new methods to improve evacuations. In this dissertation, first, hurricane evacuation of the Hampton Roads region of Virginia is investigated using large-scale regional mesoscopic traffic simulation models. Fourteen evacuation scenarios consisting of various combinations of storm categories and traffic control strategies are evaluated. The evaluation of scenarios provided information on the clearance time, average travel times, bottleneck locations, and congestion durations. The major findings from scenario evaluations include: (1) The differences in participation rates (100% versus 70%) did not impact the clearance times in a Category 1 storm evacuation, but have significant impact in a Category 3 storm evacuation, (2) The status (open or close) of a critical tunnel crossing, the Monitor-Merrimac Memorial Bridge-Tunnel did not have impact on the evacuation performance in Category 1 and 2 storm. However, opening the tunnel would improve the performance in a Category 3 storm, (3) The clearance times derived from simulations can be used to determine when to issue evacuation orders for various storm intensities, and (4) The bottleneck locations and durations identified for each evacuation scenario can be used to allocate the limited traffic monitoring equipment during an evacuation. The second focus of this dissertation is to investigate the impact of assumptions made regarding evacuee route choice on evacuation performance estimates. In the hurricane evacuation literature, very few studies have documented the realistic route choice behavior of evacuees during a hurricane. Due to this lack of realistic route choice behavior data, modelers make assumptions about the route choice behavior and traffic assignment. User-equilibrium traffic assignment has been extensively used in past evacuation studies. In this dissertation, realistic route choice behavior was determined by evaluating findings of a few published studies. The impact of route choice behavior on evacuation performance, especially travel times, is then investigated using the regional simulation model of the Hampton Roads region. The analysis found that the user-equilibrium traffic assignment significantly underestimates the travel times during an evacuation. The extent of underestimation of evacuation travel times depends on the total evacuation demand (a function of storm intensity), and the percent of evacuees willing to use en-route information to seek alternate routes when facing congestion. For the three en-route percentages reported in the literature i.e., 30%, 50%, and 70%, the UE travel times were 58%, 42%, and 33% lower than actual travel times realized in a Category 1; 94%, 71%, and 57% lower in a Category 2; and 90%, 69%, and 54% lower in a Category 3 evacuation. These findings illustrate the need to collect real-world data on evacuee route choice in order to build accurate evacuation models. The third focus of dissertation is to propose a procedure to assess the benefit of adding additional intermediate crossovers on a contra flow facility. Contra flow operation in which the direction of traffic on one or more travel lanes is reversed in order to increase the capacity of a road network is becoming a critical component of the evacuation plans of coastal states. Several coastal states have a contra flow plan in place for evacuation, however only a few states have intermediate crossovers between the origin and termination points. The impact of intermediate crossovers on network performance has not been well investigated in previous research. This dissertation investigates the benefits of having intermediate crossovers between regular and contra flow lanes. Based on the investigation, it can be concluded that adding intermediate crossovers did improve network performance for medium and high evacuation demand situations. Adding intermediate crossovers for low demand situations did not improve the network performance and thus any considerations for intermediate crossovers for the low demand evacuations must be based solely on providing access to road-side services (gas, food, and others). For high and medium demand situations and for the road network studied in this section, a 28% improvement in the average travel time was observed by deploying four intermediate crossovers out of the 44 potential crossover locations. The iterative elimination procedure proposed in this dissertation is the first attempt in the literature to provide a systematic approach to determine the critical intermediate crossover locations within reasonable computation times.
Download or read book Development of a Time dependent Hurricane Evacuation Model for the New Orleans Area written by Chester G. Wilmot and published by . This book was released on 2013 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Modeling Decision Making Related to Incident Delays During Hurricane Evacuations written by Robert Michael Robinson and published by . This book was released on 2010 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Islands Task Force Report written by Interagency Coordinating Committee on Hurricanes and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evacuate Or Not written by Adithya Raam Sankar and published by . This book was released on 2019 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent hurricanes in the Atlantic region of southern United States triggered a series of evacuation orders in the coastal cities of Florida, Texas and Georgia. While some of these were voluntary evacuations, most of them were mandatory orders that the residents had to follow. In spite of the government asking people to vacate their homes for their own safety, many did not evacuate. Various reasons motivate individuals to choose to stay or vacate. We aim to understand the factors involved in this decision-making process and model these in a partially observable Markov decision process, which predicts whether a person will evacuate or not given his or her current situation. We consider the features of the particular hurricane, the situation that the individual is experiencing, and demographic factors that influence the decision making of individuals. The model is represented as a dynamic influence diagram and evaluated on data collected through a comprehensive survey of hurricane-impacted individuals. We also propose an improvised method of k-means clustering for tweets that considers the context of the text rather than just the cosine similarity.
