Article
Economics
Tarun Rambha, Linda K. Nozick, Rachel Davidson
Summary: The study focuses on predicting household evacuation choices during hurricanes, considering socio-demographic factors and hurricane characteristics. It uses a dynamic discrete choice framework to model households' decisions to evacuate or wait before landfall. The research estimates model parameters using a nested algorithm and real case study data.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Green & Sustainable Science & Technology
Ding Wang, Kaan Ozbay, Zilin Bian
Summary: The study discusses how to leverage ride-sourcing companies as additional resources in evacuation planning, balancing evacuation demand and driver supply through pricing mechanisms, and considering subsidies for low-income and vulnerable individuals. A case study in New York City has demonstrated the feasibility of this approach and the applicability of subsidies.
Article
Computer Science, Information Systems
Yan Yang, Sara Metcalf, Liang Mao
Summary: This article introduces a novel agent-based model that integrates social-spatial networks to study hurricane evacuation in the Florida Keys, USA. The simulation results show that adding public transportation capacity significantly reduces traffic load and evacuation time, providing a practical, accessible, and equitable route to safety for low mobility populations.
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
(2021)
Article
Transportation Science & Technology
Kamol Chandra Roy, Samiul Hasan, Aron Culotta, Naveen Eluru
Summary: Efficient traffic operations during evacuation reduce time and stress, while real-time information and machine learning approaches can help predict demand up to 24 hours in advance during evacuations. The proposed LSTM-NN model can significantly benefit future evacuation traffic management.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Environmental Studies
Kairui Feng, Ning Lin
Summary: Hurricane Irma in 2017 caused the largest evacuation in Florida's history, with reconstructed data showing varying evacuation rates for different cities and peak traffic flow leading to statewide congestion. The research provides an important foundation for understanding evacuation demand and developing evacuation management policies.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2021)
Article
Chemistry, Multidisciplinary
Ruijie Bian, Pamela Murray-Tuite, Joseph Trainor, Praveen Edara, Konstantinos Triantis
Summary: This study modeled households' responses to a phased evacuation order and found that about 66% of the evacuees would comply with it. Risk perception became non-significant in explaining their compliance behavior, while stakeholder and evacuation perceptions played a more important role. People who evacuate to friends/relatives' homes or bring more vehicles are less likely to follow phased evacuation orders, while those with longer travel delay expectations are more likely to comply.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Civil
Michael K. Lindell, John H. Sorensen, Earl J. Baker, William P. Lehman
Summary: The data shows that as a hurricane approaches, more households monitor local news media for updates on the risky areas. The data from hurricane studies are consistent with other slow-onset hazard situations, but there is a lack of warning diffusion data for hurricanes with late intensification or track changes.
NATURAL HAZARDS REVIEW
(2021)
Article
Public, Environmental & Occupational Health
Pamela Murray-Tuite, Y. Gurt Ge, Christopher Zobel, Roshanak Nateghi, Haizhong Wang
Summary: In interdisciplinary research on hurricanes, alignment of decision-making agents, time, and space is crucial. Sociobehavioral science, transportation engineering, power systems engineering, and decision support systems play important roles in this context. Resolving differences in decision-making agents and data collection frequency is essential for the success of interdisciplinary teams in protective-action-related disaster research.
Article
Environmental Studies
Kairui Feng, Ning Lin
Summary: Hurricane evacuation modeling is challenging due to limited evacuation data and the complexity of human decision-making and travel behavior. However, we have built a system that can rapidly predict hurricane evacuation traffic flow by integrating hurricane forecasting, evacuation orders, road network, and population information. We have evaluated and calibrated the model using traffic observations from Hurricane Irma, and it skillfully captures spatial and temporal evacuation features, which can be applied to support evacuation management. Our analysis also suggests that minor adjustments to evacuation orders can significantly alleviate traffic congestion during hurricanes.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Transportation Science & Technology
Kamol Chandra Roy, Samiul Hasan
Summary: This study introduces a method to infer individual evacuation behavior from social media data. By utilizing an input output Hidden Markov Model, real-time prediction of evacuation behavior during hurricanes can be made, providing a more timely and efficient approach compared to traditional surveys.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Engineering, Civil
Ruijie Bian, Pamela Murray-Tuite, Praveen Edara, Konstantinos Triantis
Summary: Households have access to real-time travel information, but the impact of predeparture information on travel delays on households' evacuation plans is still unknown. Research shows that changing departure time is the most preferred adaptation for households. When facing travel delays, households are more likely to evacuate earlier or change routes or destinations.
NATURAL HAZARDS REVIEW
(2022)
Article
Computer Science, Information Systems
Mahyar Ghorbanzadeh, Linoj Vijayan, Jieya Yang, Eren Erman Ozguven, Wenrui Huang, Mengdi Ma
Summary: Hurricane Irma in 2017 posed challenges to the evacuation process in South Florida due to its unpredictability. This study developed a methodology integrating evacuation and storm surge modeling, showing that approximately three days are needed to safely evacuate the population in the study area. Integrated simulations before the hurricane hit the state could provide crucial information for decision-making on evacuation in hurricane-prone areas.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2021)
Article
Engineering, Civil
Wenrui Huang, Kai Yin, Mahyar Ghorbanzadeh, Eren Ozguven, Sudong Xu, Linoj Vijayan
Summary: Through a case study of Hurricane Irma, this study conducted an integrated storm surge modeling and traffic analysis. Results showed that storm surges and strong winds mainly affected coastal counties in southwest Florida, and over-evacuation was found to be due to the uncertainty of the hurricane path.
FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING
(2021)
Article
Geosciences, Multidisciplinary
Austin Harris, Paul Roebber, Rebecca Morss
Summary: Hurricane evacuations are complex and challenging due to interacting physical-social factors and uncertainties. A modeling framework called FLEE has been introduced to investigate the dynamics of the hurricane forecast-evacuation system, which includes models of the natural hazard, human system, built environment, and connections between systems. This framework can assist researchers and practitioners in hazard risk management, meteorology, and related fields to mitigate hurricane losses.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Biochemistry & Molecular Biology
Abdeljalil Chougradi, Francois Zaviska, Ahmed Abed, Jerome Harmand, Jamal-Eddine Jellal, Marc Heran
Summary: The study introduces a mathematical modeling method for batch reverse osmosis technology, confirming its energy efficiency compared to continuous reverse osmosis, especially at higher recovery ratios. The research also found that the batch reverse osmosis process does not have to operate under constant flux, and the efficiency of salinity, pumps, and energy recovery devices directly impact energy demand.
