Learning from traffic data collected before, during and after a hurricane
Hurricanes harm people and damage property through extreme wind speeds and flooding associated with heavy rains and storm surge. One of the most effective and widely used tactics to protect people from hurricanes is evacuation. Improved knowledge of the behavior of communities before, during and aft...
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doaj-bf88cc13e2674abf8f0dd65e73c2e7242020-11-24T23:04:19ZengElsevierIATSS Research0386-11122012-07-0136111010.1016/j.iatssr.2012.06.002Learning from traffic data collected before, during and after a hurricaneErik Archibald0Sue McNeil1Disaster Research Center, University of Delaware, Newark DE 19716, USADepartment of Civil and Environmental Engineering, University of Delaware, Newark DE 19716, USAHurricanes harm people and damage property through extreme wind speeds and flooding associated with heavy rains and storm surge. One of the most effective and widely used tactics to protect people from hurricanes is evacuation. Improved knowledge of the behavior of communities before, during and after an evacuation can better support emergency planning and operations, and thus help make evacuations safer and more efficient. The objective of this work is to identify ways to use traffic data to better understand evacuation behavior and to explore ways to integrate traffic data into evacuation planning and response. Traffic data collected in Delaware before, during and after Hurricane Irene in August 2011 using automated traffic recorders are assembled and analyzed. The analysis shows that a significant number of residents and visitors evacuated from the beach communities and the evacuation patterns are very similar to the traffic patterns experienced on summer weekends. These insights suggest that this type of analysis may also be of value for other events in other communities.http://www.sciencedirect.com/science/article/pii/S0386111212000222DisastersEvacuationTraffic countsHurricaneTraffic patternsEmergency services |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Erik Archibald Sue McNeil |
spellingShingle |
Erik Archibald Sue McNeil Learning from traffic data collected before, during and after a hurricane IATSS Research Disasters Evacuation Traffic counts Hurricane Traffic patterns Emergency services |
author_facet |
Erik Archibald Sue McNeil |
author_sort |
Erik Archibald |
title |
Learning from traffic data collected before, during and after a hurricane |
title_short |
Learning from traffic data collected before, during and after a hurricane |
title_full |
Learning from traffic data collected before, during and after a hurricane |
title_fullStr |
Learning from traffic data collected before, during and after a hurricane |
title_full_unstemmed |
Learning from traffic data collected before, during and after a hurricane |
title_sort |
learning from traffic data collected before, during and after a hurricane |
publisher |
Elsevier |
series |
IATSS Research |
issn |
0386-1112 |
publishDate |
2012-07-01 |
description |
Hurricanes harm people and damage property through extreme wind speeds and flooding associated with heavy rains and storm surge. One of the most effective and widely used tactics to protect people from hurricanes is evacuation. Improved knowledge of the behavior of communities before, during and after an evacuation can better support emergency planning and operations, and thus help make evacuations safer and more efficient. The objective of this work is to identify ways to use traffic data to better understand evacuation behavior and to explore ways to integrate traffic data into evacuation planning and response. Traffic data collected in Delaware before, during and after Hurricane Irene in August 2011 using automated traffic recorders are assembled and analyzed. The analysis shows that a significant number of residents and visitors evacuated from the beach communities and the evacuation patterns are very similar to the traffic patterns experienced on summer weekends. These insights suggest that this type of analysis may also be of value for other events in other communities. |
topic |
Disasters Evacuation Traffic counts Hurricane Traffic patterns Emergency services |
url |
http://www.sciencedirect.com/science/article/pii/S0386111212000222 |
work_keys_str_mv |
AT erikarchibald learningfromtrafficdatacollectedbeforeduringandafterahurricane AT suemcneil learningfromtrafficdatacollectedbeforeduringandafterahurricane |
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