Estimating road network accessibility during a hurricane evacuation: A case study of hurricane Irma in Florida

Zhu, Yi-Jie; Hu, Yujie; Collins, Jennifer

doi:10.1016/j.trd.2020.102334

Cited by 41 publications

(19 citation statements)

References 38 publications

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“…Similar spatial patterns were observed for Hurricane Sandy, although volumes were lower than for Hurricane Irene (28). Investigations into the evacuation of Hurricane Irma have attempted to illustrate and quantify congestion caused by the evacuation (29,30) and identify roadway bottlenecks (31) as well as road network accessibility (32). Irma has also served as a case study to investigate evacuation decision making (13,33) and to analyze the operational and safety impacts of emergency shoulder use (34).…”

Section: Literature Reviewmentioning

confidence: 70%

Methodology to Quantify Statewide Evacuations

Parr

Acevedo

Murray‐Tuite

et al. 2021

Transportation Research Record: Journal of the Transportation R

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Mass evacuations, particularly those at a statewide level, are among the largest single-event highway traffic events. They can last several days, cover thousands of miles of roadway, and include hundreds of thousands of people and vehicles. Often, evacuations are criticized for their inefficiency and poor management. Despite the critical importance and the potential impact on lives and safety, there are no recognized methods systematically to quantify traffic characteristics at statewide scales. This paper documents the development and application of an analytical method to measure statewide mass evacuations. The proposed approach sought to be both practical and cost-effective. The research methods are based on simple, yet widely available, and easily understood traffic count datasets that support both qualitative and quantitative analyses. By spatially and temporally arranging sensor-based statewide traffic volume data from the hurricane Irma (2017) and Michael (2018) evacuations, these methods are applied to describe and answer several key questions about statewide mass evacuations. The methods developed in this research are able to estimate the start and end of the auto-based evacuation, the loading and peaking characteristics of traffic, the total number of vehicles involved in the evacuation, and the effective start and end time of the auto-based reentry. Among the key findings of this work were that the hurricane Irma and Michael evacuations began several days before landfall, peaking two to three days before the storm. It is expected that state departments of transportation and emergency management officials can apply similar methods to assess and better plan future evacuations.

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Section: Literature Reviewmentioning

confidence: 70%

Methodology to Quantify Statewide Evacuations

Parr

Acevedo

Murray‐Tuite

et al. 2021

Transportation Research Record: Journal of the Transportation R

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“…While thousands of residents moved to the west to flee from the hurricane, the unexpected path change of Irma made them go back. This quick mobilization also resulted in heavy traffic congestion and bottleneck along several major highways across Florida [10]. Figure 1a-d obtained from the National Hurricane Center (NHC) and NOAA present Hurricane Irma's track on 6 September 2017, 7 September 2017, 8 September 2017, and 10 September 2017, at 8 a.m., respectively [60].…”

Section: Study Area and Hurricane Irmamentioning

confidence: 99%

“…However, heavy gridlocks along these major highways increased the travel times for evacuees. In addition, fuel shortages due to a high number of vehicles on major roadways and evacuation routes intensified the risk of life losses during the evacuation process [10,11].…”

Section: Introductionmentioning

confidence: 99%

Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

Ghorbanzadeh

Vijayan

Yang

et al. 2021

IJGI

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Hurricane Irma, in 2017, made an unusual landfall in South Florida and the unpredictability of the hurricane’s path challenged the evacuation process seriously and left many evacuees clueless. It was likely to hit Southeast Florida but suddenly shifted its path to the west coast of the peninsula, where the evacuation process had to change immediately without any time for individual decision-making. As such, this study aimed to develop a methodology to integrate evacuation and storm surge modeling with a case study analysis of Irma hitting Southeast Florida. For this purpose, a coupled storm surge and wave finite element model (ADCIRC+SWAN) was used to determine the inundation zones and roadways with higher inundation risk in Broward, Miami-Dade, and Palm Beach counties in Southeast Florida. This was fed into the evacuation modeling to estimate the regional clearance times and shelter availability in the selected counties. Findings show that it takes approximately three days to safely evacuate the populations in the study area. Modeling such integrated simulations before the hurricane hit the state could provide the information people in hurricane-prone areas need to decide to evacuate or not before the mandatory evacuation order is given.

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“…Between 1980 and 2019, the National Oceanic and Atmospheric Administration (NOAA) estimated the damage associated with weatherand climate-related disasters totaled $1.75 trillion in the United States (3). The State of Florida, which is surrounded by subtropical waters from three sides because of its unique geography, is one of the southern states that is significantly vulnerable to hurricanes (4,5). Many Floridians have to evacuate to safer locations under mandatory or voluntary evacuation orders before these hurricanes hit.…”

mentioning

confidence: 99%

“…Many drove north along major evacuation routes such as I-95 and I-75 to flee the storm. However, traffic jams and fuel shortages slowed them down and thousands of motorists were gridlocked along these routes for hours; this increased the loss of life risk, especially among vulnerable roadway users such as seniors (4,11).…”

mentioning

confidence: 99%

Spatiotemporal Analysis of Highway Traffic Patterns in Hurricane Irma Evacuation

Ghorbanzadeh

Burns

Vijayan

et al. 2021

Transportation Research Record: Journal of the Transportation R

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The State of Florida is significantly vulnerable to catastrophic hurricanes that cause widespread infrastructural damage and claim lives annually. In 2017, Hurricane Irma, a Category 4 hurricane, took on the entirety of Florida, causing the state’s largest evacuation ever as 7 million residents fled the hurricane. Floridians fleeing the hurricane faced the unique challenge of where to go, since Irma made an unusual landfall from the south, enveloping the entire state, forcing evacuees to drive farther north, and creating traffic jams along Florida’s evacuation routes that were worse than during any other hurricane in Florida's history. This study aimed to assess the spatiotemporal traffic impacts of Irma on Florida’s major highways based on real-time traffic data before, during, and after the hurricane made landfall. First, we conducted a time-series-based analysis to evaluate the temporal evacuation patterns of this large-scale evacuation. Second, we developed a metric, namely the congestion index (CI), to assess the spatiotemporal evacuation patterns on I-95, I-75, I-10, I-4, and turnpike (SR-91) highways with a focus on both evacuation and returning traffic. Third, we employed a geographic information system-based analysis to visually illustrate the CI values of corresponding highway sections with respect to different dates and times. Findings clearly showed that imperfect forecasts and the uncertainty surrounding Irma’s predicted path resulted in high levels of congestion and severe delays on Florida’s major evacuation routes.

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Estimating road network accessibility during a hurricane evacuation: A case study of hurricane Irma in Florida

Cited by 41 publications

References 38 publications

Methodology to Quantify Statewide Evacuations

Methodology to Quantify Statewide Evacuations

Integrating Evacuation and Storm Surge Modeling Considering Potential Hurricane Tracks: The Case of Hurricane Irma in Southeast Florida

Spatiotemporal Analysis of Highway Traffic Patterns in Hurricane Irma Evacuation

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