Loading…
Resilience and efficiency in transportation networks
Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that impro...
Saved in:
Published in: | arXiv.org 2017-12 |
---|---|
Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | |
---|---|
cites | |
container_end_page | |
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Ganin, Alexander A Kitsak, Maksim Marchese, Dayton Keisler, Jeffrey M Seager, Thomas Linkov, Igor |
description | Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions. |
doi_str_mv | 10.48550/arxiv.1712.08072 |
format | article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2076877421</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2076877421</sourcerecordid><originalsourceid>FETCH-LOGICAL-a521-77f0d3aa992a47e761c453b7885dde7c89a52023930ef0f91b2402c6abd2537d3</originalsourceid><addsrcrecordid>eNotjUtrAyEURqVQSEjzA7oTup7p9apzdVlCXxAIlOyDMyqYBCfVSR__vint6uPA4XyM3QpoldEa7l35Sh-tIIEtGCC8YnOUUjRGIc7YstY9AGBHqLWcM_UWajqmkIfAXfY8xJiGX_zmKfOpuFxPY5nclMbMc5g-x3KoN-w6umMNy_9dsO3T43b10qw3z6-rh3XjNIqGKIKXzlmLTlGgTgxKy56M0d4HGoy9aIDSSggRohU9KsChc71HLcnLBbv7y57K-H4Oddrtx3PJl8cdAnWGSKGQP6LKRnM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2076877421</pqid></control><display><type>article</type><title>Resilience and efficiency in transportation networks</title><source>ProQuest - Publicly Available Content Database</source><creator>Ganin, Alexander A ; Kitsak, Maksim ; Marchese, Dayton ; Keisler, Jeffrey M ; Seager, Thomas ; Linkov, Igor</creator><creatorcontrib>Ganin, Alexander A ; Kitsak, Maksim ; Marchese, Dayton ; Keisler, Jeffrey M ; Seager, Thomas ; Linkov, Igor</creatorcontrib><description>Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions.</description><identifier>EISSN: 2331-8422</identifier><identifier>DOI: 10.48550/arxiv.1712.08072</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Accidents ; Disruption ; Efficiency ; Mapping ; Resilience ; Roads ; Roads & highways ; Segments ; Traffic congestion ; Traffic delay ; Traffic intersections ; Traffic models ; Transportation networks ; Transportation systems ; Urban areas ; Urban transportation</subject><ispartof>arXiv.org, 2017-12</ispartof><rights>2017. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/2076877421?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>780,784,25753,27925,37012,44590</link.rule.ids></links><search><creatorcontrib>Ganin, Alexander A</creatorcontrib><creatorcontrib>Kitsak, Maksim</creatorcontrib><creatorcontrib>Marchese, Dayton</creatorcontrib><creatorcontrib>Keisler, Jeffrey M</creatorcontrib><creatorcontrib>Seager, Thomas</creatorcontrib><creatorcontrib>Linkov, Igor</creatorcontrib><title>Resilience and efficiency in transportation networks</title><title>arXiv.org</title><description>Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions.</description><subject>Accidents</subject><subject>Disruption</subject><subject>Efficiency</subject><subject>Mapping</subject><subject>Resilience</subject><subject>Roads</subject><subject>Roads & highways</subject><subject>Segments</subject><subject>Traffic congestion</subject><subject>Traffic delay</subject><subject>Traffic intersections</subject><subject>Traffic models</subject><subject>Transportation networks</subject><subject>Transportation systems</subject><subject>Urban areas</subject><subject>Urban transportation</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNotjUtrAyEURqVQSEjzA7oTup7p9apzdVlCXxAIlOyDMyqYBCfVSR__vint6uPA4XyM3QpoldEa7l35Sh-tIIEtGCC8YnOUUjRGIc7YstY9AGBHqLWcM_UWajqmkIfAXfY8xJiGX_zmKfOpuFxPY5nclMbMc5g-x3KoN-w6umMNy_9dsO3T43b10qw3z6-rh3XjNIqGKIKXzlmLTlGgTgxKy56M0d4HGoy9aIDSSggRohU9KsChc71HLcnLBbv7y57K-H4Oddrtx3PJl8cdAnWGSKGQP6LKRnM</recordid><startdate>20171221</startdate><enddate>20171221</enddate><creator>Ganin, Alexander A</creator><creator>Kitsak, Maksim</creator><creator>Marchese, Dayton</creator><creator>Keisler, Jeffrey M</creator><creator>Seager, Thomas</creator><creator>Linkov, Igor</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20171221</creationdate><title>Resilience and efficiency in transportation networks</title><author>Ganin, Alexander A ; Kitsak, Maksim ; Marchese, Dayton ; Keisler, Jeffrey M ; Seager, Thomas ; Linkov, Igor</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a521-77f0d3aa992a47e761c453b7885dde7c89a52023930ef0f91b2402c6abd2537d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accidents</topic><topic>Disruption</topic><topic>Efficiency</topic><topic>Mapping</topic><topic>Resilience</topic><topic>Roads</topic><topic>Roads & highways</topic><topic>Segments</topic><topic>Traffic congestion</topic><topic>Traffic delay</topic><topic>Traffic intersections</topic><topic>Traffic models</topic><topic>Transportation networks</topic><topic>Transportation systems</topic><topic>Urban areas</topic><topic>Urban transportation</topic><toplevel>online_resources</toplevel><creatorcontrib>Ganin, Alexander A</creatorcontrib><creatorcontrib>Kitsak, Maksim</creatorcontrib><creatorcontrib>Marchese, Dayton</creatorcontrib><creatorcontrib>Keisler, Jeffrey M</creatorcontrib><creatorcontrib>Seager, Thomas</creatorcontrib><creatorcontrib>Linkov, Igor</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>ProQuest - Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>arXiv.org</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ganin, Alexander A</au><au>Kitsak, Maksim</au><au>Marchese, Dayton</au><au>Keisler, Jeffrey M</au><au>Seager, Thomas</au><au>Linkov, Igor</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Resilience and efficiency in transportation networks</atitle><jtitle>arXiv.org</jtitle><date>2017-12-21</date><risdate>2017</risdate><eissn>2331-8422</eissn><abstract>Urban transportation systems are vulnerable to congestion, accidents, weather, special events, and other costly delays. Whereas typical policy responses prioritize reduction of delays under normal conditions to improve the efficiency of urban road systems, analytic support for investments that improve resilience (defined as system recovery from additional disruptions) is still scarce. In this effort, we represent paved roads as a transportation network by mapping intersections to nodes and road segments between the intersections to links. We built road networks for 40 of the urban areas defined by the U.S. Census Bureau. We developed and calibrated a model to evaluate traffic delays using link loads. The loads may be regarded as traffic-based centrality measures, estimating the number of individuals using corresponding road segments. Efficiency was estimated as the average annual delay per peak-period auto commuter, and modeled results were found to be close to observed data, with the notable exception of New York City. Resilience was estimated as the change in efficiency resulting from roadway disruptions and was found to vary between cities, with increased delays due to a 5% random loss of road linkages ranging from 9.5% in Los Angeles to 56.0% in San Francisco. The results demonstrate that many urban road systems that operate inefficiently under normal conditions are nevertheless resilient to disruption, whereas some more efficient cities are more fragile. The implication is that resilience, not just efficiency, should be considered explicitly in roadway project selection and justify investment opportunities related to disaster and other disruptions.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><doi>10.48550/arxiv.1712.08072</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2017-12 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2076877421 |
source | ProQuest - Publicly Available Content Database |
subjects | Accidents Disruption Efficiency Mapping Resilience Roads Roads & highways Segments Traffic congestion Traffic delay Traffic intersections Traffic models Transportation networks Transportation systems Urban areas Urban transportation |
title | Resilience and efficiency in transportation networks |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-05T06%3A38%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Resilience%20and%20efficiency%20in%20transportation%20networks&rft.jtitle=arXiv.org&rft.au=Ganin,%20Alexander%20A&rft.date=2017-12-21&rft.eissn=2331-8422&rft_id=info:doi/10.48550/arxiv.1712.08072&rft_dat=%3Cproquest%3E2076877421%3C/proquest%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a521-77f0d3aa992a47e761c453b7885dde7c89a52023930ef0f91b2402c6abd2537d3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2076877421&rft_id=info:pmid/&rfr_iscdi=true |