ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION
Approved for public release; distribution is unlimited === This thesis introduces an integer linear program called the Minimum Cost Flow with Congestion Assignment (MCF-CA) model. MCF-CA is a multi-period evacuation model that uses a novel approach called congestion assignment to analyze clearing ti...
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ndltd-nps.edu-oai-calhoun.nps.edu-10945-328612015-05-06T03:58:47Z ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION Malveo, April E. Craparo, Emily M. Alderson, David L. Operations Research Approved for public release; distribution is unlimited This thesis introduces an integer linear program called the Minimum Cost Flow with Congestion Assignment (MCF-CA) model. MCF-CA is a multi-period evacuation model that uses a novel approach called congestion assignment to analyze clearing times during mass evacuations. Congestion assignment discretizes the nonlinear relationship between the number of vehicles on a road segment and the maximum speed at which those vehicles can travel. MCF-CA selects among three congestion levels (none, moderate, and high) for each road segment in each time epoch. Depending on the congestion level selected, MCF-CA limits the number of vehicles that are able to traverse the road segment and uses Akeliks Time-Dependent Speed-Flow Function (Akelik 2003) to determine the average travel speed of the vehicles for that time period. As a result, we are able to determine approximate evacuation clearing times under nonlinear congestion effects by solving an integer linear program. We limit residents prior knowledge of traffic conditions by implementing MCF-CA in a rolling horizon fashion and study the impact of this limited knowledge on evacuation patterns. We also model the impact of sub-optimal routing decisions on the part of residents by artificially shifting residents toward their own shortest paths rather than a socially optimal route. We find that a mass evacuation can more than double the clearing times of individual county evacuations. However, during both county and mass evacuations, resident routing choices significantly impact clearing times. As more residents choose suboptimal routes, clearing times are prolonged. Lastly, we find that more than 50% of residents will experience congestion at some point during the evacuation horizon. However, allowing some congestion improves evacuation clearing times by 2036% over not congesting. Although congestion decreases vehicle travel speed by 7080%, over 50% more residents are able to start or continue evacuating during each time epoch. 2013-05-08T20:42:22Z 2013-05-08T20:42:22Z 2013-03 http://hdl.handle.net/10945/32861 This publication is a work of the U.S. Government as defined
in Title 17, United States Code, Section 101. As such, it is in the
public domain, and under the provisions of Title 17, United States
Code, Section 105, is not copyrighted in the U.S. Monterey, California. Naval Postgraduate School |
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Approved for public release; distribution is unlimited === This thesis introduces an integer linear program called the Minimum Cost Flow with Congestion Assignment (MCF-CA) model. MCF-CA is a multi-period evacuation model that uses a novel approach called congestion assignment to analyze clearing times during mass evacuations. Congestion assignment discretizes the nonlinear relationship between the number of vehicles on a road segment and the maximum speed at which those vehicles can travel. MCF-CA selects among three congestion levels (none, moderate, and high) for each road segment in each time epoch. Depending on the congestion level selected, MCF-CA limits the number of vehicles that are able to traverse the road segment and uses Akeliks Time-Dependent Speed-Flow Function (Akelik 2003) to determine the average travel speed of the vehicles for that time period. As a result, we are able to determine approximate evacuation clearing times under nonlinear congestion effects by solving an integer linear program. We limit residents prior knowledge of traffic conditions by implementing MCF-CA in a rolling horizon fashion and study the impact of this limited knowledge on evacuation patterns. We also model the impact of sub-optimal routing decisions on the part of residents by artificially shifting residents toward their own shortest paths rather than a socially optimal route. We find that a mass evacuation can more than double the clearing times of individual county evacuations. However, during both county and mass evacuations, resident routing choices significantly impact clearing times. As more residents choose suboptimal routes, clearing times are prolonged. Lastly, we find that more than 50% of residents will experience congestion at some point during the evacuation horizon. However, allowing some congestion improves evacuation clearing times by 2036% over not congesting. Although congestion decreases vehicle travel speed by 7080%, over 50% more residents are able to start or continue evacuating during each time epoch. |
author2 |
Craparo, Emily M. |
author_facet |
Craparo, Emily M. Malveo, April E. |
author |
Malveo, April E. |
spellingShingle |
Malveo, April E. ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION |
author_sort |
Malveo, April E. |
title |
ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION |
title_short |
ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION |
title_full |
ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION |
title_fullStr |
ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION |
title_full_unstemmed |
ASSESSING THE IMPACT OF CONGESTION DURING A MULTI-COUNTY EVACUATION |
title_sort |
assessing the impact of congestion during a multi-county evacuation |
publisher |
Monterey, California. Naval Postgraduate School |
publishDate |
2013 |
url |
http://hdl.handle.net/10945/32861 |
work_keys_str_mv |
AT malveoaprile assessingtheimpactofcongestionduringamulticountyevacuation |
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1716803299830661120 |