Taking the freeway: Inferring evacuee route selection from survey data
Effective evacuation management plans can help reduce the negative impacts of disasters. Understanding evacuee travel behavior is critical for the design of evacuation plans. In this paper, we explore which factors contribute to evacuees selecting freeway vs. non-freeway evacuation routes. Freeways...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-09-01
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| Series: | Transportation Research Interdisciplinary Perspectives |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590198221001275 |
| _version_ | 1819125285018140672 |
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| author | Daeyeol Chang Praveen Edara Pamela Murray-Tuite Joseph Trainor Kostas Triantis |
| author_facet | Daeyeol Chang Praveen Edara Pamela Murray-Tuite Joseph Trainor Kostas Triantis |
| author_sort | Daeyeol Chang |
| collection | DOAJ |
| description | Effective evacuation management plans can help reduce the negative impacts of disasters. Understanding evacuee travel behavior is critical for the design of evacuation plans. In this paper, we explore which factors contribute to evacuees selecting freeway vs. non-freeway evacuation routes. Freeways are of particular interest due to their ability to evacuate large volumes of traffic. This study used survey data collected for the Hampton Roads region of Virginia. Respondents were asked to provide their preferred route types in the event of a hypothetical Category 4 hurricane evacuation. A mixed (random parameters) logit model was proposed to determine factors that influence evacuees selecting between freeway and non-freeway route. The study found that several factors contribute to evacuees choosing a freeway over other routes. In the descending order of importance (i.e., marginal effects), these factors are: willingness to use the official recommended route, living in a single-family or duplex housing, expected travel time to reach the destination, being employed, and possessing prior evacuation experience. Conversely, a few factors had a negative effect on choosing a freeway. These factors are: willingness to evacuate two days prior to landfall and evacuating to a public shelter or a second home. The findings of this study can help emergency management and transportation agencies design effective traffic control plans to safely evacuate populations during a hurricane. |
| first_indexed | 2024-12-22T07:37:42Z |
| format | Article |
| id | doaj.art-ebeea6dc2af04d6e90cb5e9bd324c686 |
| institution | Directory Open Access Journal |
| issn | 2590-1982 |
| language | English |
| last_indexed | 2024-12-22T07:37:42Z |
| publishDate | 2021-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Transportation Research Interdisciplinary Perspectives |
| spelling | doaj.art-ebeea6dc2af04d6e90cb5e9bd324c6862022-12-21T18:33:51ZengElsevierTransportation Research Interdisciplinary Perspectives2590-19822021-09-0111100421Taking the freeway: Inferring evacuee route selection from survey dataDaeyeol Chang0Praveen Edara1Pamela Murray-Tuite2Joseph Trainor3Kostas Triantis4Department of Civil and Environmental Engineering, University of Missouri-Columbia, United StatesDepartment of Civil and Environmental Engineering, University of Missouri-Columbia, United States; Corresponding author.Department of Civil Engineering, Clemson University, Unites StatesDepartment of Public Policy and Administration, University of Delaware, United StatesDepartment of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, United StatesEffective evacuation management plans can help reduce the negative impacts of disasters. Understanding evacuee travel behavior is critical for the design of evacuation plans. In this paper, we explore which factors contribute to evacuees selecting freeway vs. non-freeway evacuation routes. Freeways are of particular interest due to their ability to evacuate large volumes of traffic. This study used survey data collected for the Hampton Roads region of Virginia. Respondents were asked to provide their preferred route types in the event of a hypothetical Category 4 hurricane evacuation. A mixed (random parameters) logit model was proposed to determine factors that influence evacuees selecting between freeway and non-freeway route. The study found that several factors contribute to evacuees choosing a freeway over other routes. In the descending order of importance (i.e., marginal effects), these factors are: willingness to use the official recommended route, living in a single-family or duplex housing, expected travel time to reach the destination, being employed, and possessing prior evacuation experience. Conversely, a few factors had a negative effect on choosing a freeway. These factors are: willingness to evacuate two days prior to landfall and evacuating to a public shelter or a second home. The findings of this study can help emergency management and transportation agencies design effective traffic control plans to safely evacuate populations during a hurricane.http://www.sciencedirect.com/science/article/pii/S2590198221001275Hurricane evacuationEvacuee route choiceLogit modelRandom parameter model |
| spellingShingle | Daeyeol Chang Praveen Edara Pamela Murray-Tuite Joseph Trainor Kostas Triantis Taking the freeway: Inferring evacuee route selection from survey data Transportation Research Interdisciplinary Perspectives Hurricane evacuation Evacuee route choice Logit model Random parameter model |
| title | Taking the freeway: Inferring evacuee route selection from survey data |
| title_full | Taking the freeway: Inferring evacuee route selection from survey data |
| title_fullStr | Taking the freeway: Inferring evacuee route selection from survey data |
| title_full_unstemmed | Taking the freeway: Inferring evacuee route selection from survey data |
| title_short | Taking the freeway: Inferring evacuee route selection from survey data |
| title_sort | taking the freeway inferring evacuee route selection from survey data |
| topic | Hurricane evacuation Evacuee route choice Logit model Random parameter model |
| url | http://www.sciencedirect.com/science/article/pii/S2590198221001275 |
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