Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach
A wide range of relatively short-term disruptive events such as partial flooding, visibility reductions, traction hazards due to weather, and pavement deterioration occur on transportation networks on a daily basis. Despite being relatively minor when compared to catastrophes, these events still hav...
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Veröffentlicht in: | Transportation research. Part A, Policy and practice Policy and practice, 2010-06, Vol.44 (5), p.323-336 |
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creator | Sullivan, J.L. Novak, D.C. Aultman-Hall, L. Scott, D.M. |
description | A wide range of relatively short-term disruptive events such as partial flooding, visibility reductions, traction hazards due to weather, and pavement deterioration occur on transportation networks on a daily basis. Despite being relatively minor when compared to catastrophes, these events still have profound impacts on traffic flow. To date there has been very little distinction drawn between different types of network-disruption studies and how the methodological approaches used in those studies differ depending on the specific research objectives and on the disruption scenarios being modeled.
In this paper, we advance a methodological approach that employs different link-based capacity-disruption values for identifying and ranking the most critical links and quantifying network robustness in a transportation network. We demonstrate how an ideal capacity-disruption range can be objectively determined for a particular network and introduce a scalable system-wide performance measure, called the Network Trip Robustness (NTR) that can be used to directly compare networks of different sizes, topologies, and connectivity levels.
Our approach yields results that are independent of the degree of connectivity and can be used to evaluate robustness on networks with isolating links. We show that system-wide travel-times and the rank-ordering of the most critical links in a network can vary dramatically based on both the capacity-disruption level and on the overall connectivity of the network. We further show that the relationships between network robustness, the capacity-disruption level used for modeling, and network connectivity are non-linear and not necessarily intuitive. We discuss our findings with respect to Braess’ Paradox. |
doi_str_mv | 10.1016/j.tra.2010.02.003 |
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In this paper, we advance a methodological approach that employs different link-based capacity-disruption values for identifying and ranking the most critical links and quantifying network robustness in a transportation network. We demonstrate how an ideal capacity-disruption range can be objectively determined for a particular network and introduce a scalable system-wide performance measure, called the Network Trip Robustness (NTR) that can be used to directly compare networks of different sizes, topologies, and connectivity levels.
Our approach yields results that are independent of the degree of connectivity and can be used to evaluate robustness on networks with isolating links. We show that system-wide travel-times and the rank-ordering of the most critical links in a network can vary dramatically based on both the capacity-disruption level and on the overall connectivity of the network. We further show that the relationships between network robustness, the capacity-disruption level used for modeling, and network connectivity are non-linear and not necessarily intuitive. We discuss our findings with respect to Braess’ Paradox.</description><identifier>ISSN: 0965-8564</identifier><identifier>EISSN: 1879-2375</identifier><identifier>DOI: 10.1016/j.tra.2010.02.003</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Buildings. Public works ; Exact sciences and technology ; Isolating links ; Link capacity reduction ; Links ; Mathematical models ; Network modeling ; Network Robustness Index (NRI) ; Network-disruption ; Network-disruption Network modeling Network Robustness Index (NRI) Isolating links Link capacity reduction ; Networks ; Nonlinearity ; Reduction ; Road types (roads, freeways, express ways, etc.) ; Robustness ; Transportation infrastructure ; Transportation networks ; Visibility</subject><ispartof>Transportation research. Part A, Policy and practice, 2010-06, Vol.44 (5), p.323-336</ispartof><rights>2010 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c491t-cf80c354f41d516fcce05b8c34dbc9c6865bffe9c6185c4e43ba01b42aceba73</citedby><cites>FETCH-LOGICAL-c491t-cf80c354f41d516fcce05b8c34dbc9c6865bffe9c6185c4e43ba01b42aceba73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0965856410000418$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,3994,27901,27902,65534</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=22703005$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttp://econpapers.repec.org/article/eeetransa/v_3a44_3ay_3a2010_3ai_3a5_3ap_3a323-336.htm$$DView record in RePEc$$Hfree_for_read</backlink></links><search><creatorcontrib>Sullivan, J.L.</creatorcontrib><creatorcontrib>Novak, D.C.</creatorcontrib><creatorcontrib>Aultman-Hall, L.</creatorcontrib><creatorcontrib>Scott, D.M.</creatorcontrib><title>Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach</title><title>Transportation research. Part A, Policy and practice</title><description>A wide range of relatively short-term disruptive events such as partial flooding, visibility reductions, traction hazards due to weather, and pavement deterioration occur on transportation networks on a daily basis. Despite being relatively minor when compared to catastrophes, these events still have profound impacts on traffic flow. To date there has been very little distinction drawn between different types of network-disruption studies and how the methodological approaches used in those studies differ depending on the specific research objectives and on the disruption scenarios being modeled.
In this paper, we advance a methodological approach that employs different link-based capacity-disruption values for identifying and ranking the most critical links and quantifying network robustness in a transportation network. We demonstrate how an ideal capacity-disruption range can be objectively determined for a particular network and introduce a scalable system-wide performance measure, called the Network Trip Robustness (NTR) that can be used to directly compare networks of different sizes, topologies, and connectivity levels.
Our approach yields results that are independent of the degree of connectivity and can be used to evaluate robustness on networks with isolating links. We show that system-wide travel-times and the rank-ordering of the most critical links in a network can vary dramatically based on both the capacity-disruption level and on the overall connectivity of the network. We further show that the relationships between network robustness, the capacity-disruption level used for modeling, and network connectivity are non-linear and not necessarily intuitive. We discuss our findings with respect to Braess’ Paradox.</description><subject>Applied sciences</subject><subject>Buildings. Public works</subject><subject>Exact sciences and technology</subject><subject>Isolating links</subject><subject>Link capacity reduction</subject><subject>Links</subject><subject>Mathematical models</subject><subject>Network modeling</subject><subject>Network Robustness Index (NRI)</subject><subject>Network-disruption</subject><subject>Network-disruption Network modeling Network Robustness Index (NRI) Isolating links Link capacity reduction</subject><subject>Networks</subject><subject>Nonlinearity</subject><subject>Reduction</subject><subject>Road types (roads, freeways, express ways, etc.)</subject><subject>Robustness</subject><subject>Transportation infrastructure</subject><subject>Transportation networks</subject><subject>Visibility</subject><issn>0965-8564</issn><issn>1879-2375</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><sourceid>X2L</sourceid><recordid>eNp9Uctu2zAQFIoWqJv2A3rjpWgvckmRerg9BUEfKQL0kjtBrVYxHYlSuVQMf07-tGs7yDGHJZfkzHCwk2UflVwrqaqvu3WKbl1IPstiLaV-la1UU2_yQtfl62wlN1WZN2Vl3mbviHZSSlPVxSp7vO4wJN8ffLgTEH3y4AYRJ9cJwruR30i40IkRHS3xCKIDJRzzve-Qce1CKSCR8EGwg0DzFJNLfgoiYNpP8Z7E3qet8DQNfM8Cgw_39E1cnpq8dYSdADc78OmQR-wWONHdPLMN2L7P3vRuIPzwtF9ktz9_3F79zm_-_rq-urzJwWxUyqFvJOjS9EZ1pap6AJRl24A2XQsbqJqqbPseuVNNCQaNbp1UrSkcYOtqfZF9Psvyr_8WpGRHT4DD4AJOC9mNaqRujJGM_PIiUtVayqrifxiqzlCIE1HE3s7Rjy4erJL2mJvdWZ6aPeZmZWE5N-b8OXMizgjPBEQ8zdfZB6udMbwcuE5M7TxXyTVz6UJbrSu7TSOLfXry6oiD7VkBPD2LFkUt2WzJuO9nHPKEHzxGS-AxAHY-IiTbTf4Fy_8BFsHMFQ</recordid><startdate>20100601</startdate><enddate>20100601</enddate><creator>Sullivan, J.L.</creator><creator>Novak, D.C.</creator><creator>Aultman-Hall, L.</creator><creator>Scott, D.M.</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>DKI</scope><scope>X2L</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope><scope>7ST</scope><scope>C1K</scope><scope>SOI</scope></search><sort><creationdate>20100601</creationdate><title>Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach</title><author>Sullivan, J.L. ; Novak, D.C. ; Aultman-Hall, L. ; Scott, D.M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c491t-cf80c354f41d516fcce05b8c34dbc9c6865bffe9c6185c4e43ba01b42aceba73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Applied sciences</topic><topic>Buildings. Public works</topic><topic>Exact sciences and technology</topic><topic>Isolating links</topic><topic>Link capacity reduction</topic><topic>Links</topic><topic>Mathematical models</topic><topic>Network modeling</topic><topic>Network Robustness Index (NRI)</topic><topic>Network-disruption</topic><topic>Network-disruption Network modeling Network Robustness Index (NRI) Isolating links Link capacity reduction</topic><topic>Networks</topic><topic>Nonlinearity</topic><topic>Reduction</topic><topic>Road types (roads, freeways, express ways, etc.)</topic><topic>Robustness</topic><topic>Transportation infrastructure</topic><topic>Transportation networks</topic><topic>Visibility</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sullivan, J.L.</creatorcontrib><creatorcontrib>Novak, D.C.</creatorcontrib><creatorcontrib>Aultman-Hall, L.</creatorcontrib><creatorcontrib>Scott, D.M.</creatorcontrib><collection>Pascal-Francis</collection><collection>RePEc IDEAS</collection><collection>RePEc</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Environment Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Environment Abstracts</collection><jtitle>Transportation research. Part A, Policy and practice</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sullivan, J.L.</au><au>Novak, D.C.</au><au>Aultman-Hall, L.</au><au>Scott, D.M.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach</atitle><jtitle>Transportation research. Part A, Policy and practice</jtitle><date>2010-06-01</date><risdate>2010</risdate><volume>44</volume><issue>5</issue><spage>323</spage><epage>336</epage><pages>323-336</pages><issn>0965-8564</issn><eissn>1879-2375</eissn><abstract>A wide range of relatively short-term disruptive events such as partial flooding, visibility reductions, traction hazards due to weather, and pavement deterioration occur on transportation networks on a daily basis. Despite being relatively minor when compared to catastrophes, these events still have profound impacts on traffic flow. To date there has been very little distinction drawn between different types of network-disruption studies and how the methodological approaches used in those studies differ depending on the specific research objectives and on the disruption scenarios being modeled.
In this paper, we advance a methodological approach that employs different link-based capacity-disruption values for identifying and ranking the most critical links and quantifying network robustness in a transportation network. We demonstrate how an ideal capacity-disruption range can be objectively determined for a particular network and introduce a scalable system-wide performance measure, called the Network Trip Robustness (NTR) that can be used to directly compare networks of different sizes, topologies, and connectivity levels.
Our approach yields results that are independent of the degree of connectivity and can be used to evaluate robustness on networks with isolating links. We show that system-wide travel-times and the rank-ordering of the most critical links in a network can vary dramatically based on both the capacity-disruption level and on the overall connectivity of the network. We further show that the relationships between network robustness, the capacity-disruption level used for modeling, and network connectivity are non-linear and not necessarily intuitive. We discuss our findings with respect to Braess’ Paradox.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.tra.2010.02.003</doi><tpages>14</tpages></addata></record> |
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subjects | Applied sciences Buildings. Public works Exact sciences and technology Isolating links Link capacity reduction Links Mathematical models Network modeling Network Robustness Index (NRI) Network-disruption Network-disruption Network modeling Network Robustness Index (NRI) Isolating links Link capacity reduction Networks Nonlinearity Reduction Road types (roads, freeways, express ways, etc.) Robustness Transportation infrastructure Transportation networks Visibility |
title | Identifying critical road segments and measuring system-wide robustness in transportation networks with isolating links: A link-based capacity-reduction approach |
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