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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Bibliographic Details
Main Authors: Erik Archibald, Sue McNeil
Format: Article
Language:English
Published: Elsevier 2012-07-01
Series:IATSS Research
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S0386111212000222
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spelling 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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