A new approach to understand metro operation safety by exploring metro operation hazard network (MOHN)
•An analytical framework is developed to analyze the interactions among metro hazards.•Metro operation hazard network (MOHN) is built based on accident database.•Complex network theory (CNM) is employed to explore the inherent features of MOHN.•MOHN captures the scale-free property as well as the sm...
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Veröffentlicht in: | Safety science 2017-03, Vol.93, p.50-61 |
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creator | Li, Qiming Song, Liangliang List, George F. Deng, Yongliang Zhou, Zhipeng Liu, Ping |
description | •An analytical framework is developed to analyze the interactions among metro hazards.•Metro operation hazard network (MOHN) is built based on accident database.•Complex network theory (CNM) is employed to explore the inherent features of MOHN.•MOHN captures the scale-free property as well as the small world property.
Numerous metro accidents expose the vulnerability of metro system. As cities are rapidly building and expanding metro systems, it is essential to thoroughly explore the nature of metro operation safety. Metro accidents can be regarded as an emergent property that arises from the unusual interactions of system components. These interactions could give rise to the phenomenon that several interrelated hazards simultaneously emerge in one single accident. Understanding these interrelations among hazards is indispensable to study metro operation safety. From this standpoint, 28 hazards and 48 interrelations among hazards were identified from 134 accidents and expert interviews, which were the foundation of establishing metro operation hazard network (MOHN). Whereby complex network theory, seven parameters were applied to further reveal the structural properties of MOHN. The results indicate that the MOHN is a scale-free network for the cumulative degree distribution obeys power-law distribution. The scale-free property of MOHN is indicative of its robustness to random attacks and its vulnerability to deliberate attacks. Nichetargeting controlling hazards of high degrees and betweenness centrality can significantly decrease the metro operation risks. Moreover, MOHN also possesses the small-world property for having a relatively high clustering coefficient and small shortest path length. This indicates that risks would be transmitted very quickly in MOHN. Secondary and derivative hazards should receive enough attention for the rapid propagation of MOHN. Revealing the inherent properties of MOHN assist in making beforehand strategies prior to metro accident and contributes to elevate system safety of metro operation. |
doi_str_mv | 10.1016/j.ssci.2016.10.010 |
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Numerous metro accidents expose the vulnerability of metro system. As cities are rapidly building and expanding metro systems, it is essential to thoroughly explore the nature of metro operation safety. Metro accidents can be regarded as an emergent property that arises from the unusual interactions of system components. These interactions could give rise to the phenomenon that several interrelated hazards simultaneously emerge in one single accident. Understanding these interrelations among hazards is indispensable to study metro operation safety. From this standpoint, 28 hazards and 48 interrelations among hazards were identified from 134 accidents and expert interviews, which were the foundation of establishing metro operation hazard network (MOHN). Whereby complex network theory, seven parameters were applied to further reveal the structural properties of MOHN. The results indicate that the MOHN is a scale-free network for the cumulative degree distribution obeys power-law distribution. The scale-free property of MOHN is indicative of its robustness to random attacks and its vulnerability to deliberate attacks. Nichetargeting controlling hazards of high degrees and betweenness centrality can significantly decrease the metro operation risks. Moreover, MOHN also possesses the small-world property for having a relatively high clustering coefficient and small shortest path length. This indicates that risks would be transmitted very quickly in MOHN. Secondary and derivative hazards should receive enough attention for the rapid propagation of MOHN. Revealing the inherent properties of MOHN assist in making beforehand strategies prior to metro accident and contributes to elevate system safety of metro operation.</description><identifier>ISSN: 0925-7535</identifier><identifier>EISSN: 1879-1042</identifier><identifier>DOI: 10.1016/j.ssci.2016.10.010</identifier><language>eng</language><publisher>Amsterdam: Elsevier Ltd</publisher><subject>Accident analysis ; Accident prevention ; Accidents ; Cities ; Clustering ; Complex network theory ; Hazard identification ; Metro operation hazard network (MOHN) ; Occupational hazards ; Operational hazards ; Public safety ; Safety ; Safety analysis ; Shortest-path problems ; Structural characteristics ; Studies</subject><ispartof>Safety science, 2017-03, Vol.93, p.50-61</ispartof><rights>2016 Elsevier Ltd</rights><rights>Copyright Elsevier BV Mar 2017</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c394t-f43507dca0023f6c35f7b6441814f35eca7777ec751df2e431d276417cc277dc3</citedby><cites>FETCH-LOGICAL-c394t-f43507dca0023f6c35f7b6441814f35eca7777ec751df2e431d276417cc277dc3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ssci.2016.10.010$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,781,785,3551,27929,27930,46000</link.rule.ids></links><search><creatorcontrib>Li, Qiming</creatorcontrib><creatorcontrib>Song, Liangliang</creatorcontrib><creatorcontrib>List, George F.</creatorcontrib><creatorcontrib>Deng, Yongliang</creatorcontrib><creatorcontrib>Zhou, Zhipeng</creatorcontrib><creatorcontrib>Liu, Ping</creatorcontrib><title>A new approach to understand metro operation safety by exploring metro operation hazard network (MOHN)</title><title>Safety science</title><description>•An analytical framework is developed to analyze the interactions among metro hazards.•Metro operation hazard network (MOHN) is built based on accident database.•Complex network theory (CNM) is employed to explore the inherent features of MOHN.•MOHN captures the scale-free property as well as the small world property.
Numerous metro accidents expose the vulnerability of metro system. As cities are rapidly building and expanding metro systems, it is essential to thoroughly explore the nature of metro operation safety. Metro accidents can be regarded as an emergent property that arises from the unusual interactions of system components. These interactions could give rise to the phenomenon that several interrelated hazards simultaneously emerge in one single accident. Understanding these interrelations among hazards is indispensable to study metro operation safety. From this standpoint, 28 hazards and 48 interrelations among hazards were identified from 134 accidents and expert interviews, which were the foundation of establishing metro operation hazard network (MOHN). Whereby complex network theory, seven parameters were applied to further reveal the structural properties of MOHN. The results indicate that the MOHN is a scale-free network for the cumulative degree distribution obeys power-law distribution. The scale-free property of MOHN is indicative of its robustness to random attacks and its vulnerability to deliberate attacks. Nichetargeting controlling hazards of high degrees and betweenness centrality can significantly decrease the metro operation risks. Moreover, MOHN also possesses the small-world property for having a relatively high clustering coefficient and small shortest path length. This indicates that risks would be transmitted very quickly in MOHN. Secondary and derivative hazards should receive enough attention for the rapid propagation of MOHN. Revealing the inherent properties of MOHN assist in making beforehand strategies prior to metro accident and contributes to elevate system safety of metro operation.</description><subject>Accident analysis</subject><subject>Accident prevention</subject><subject>Accidents</subject><subject>Cities</subject><subject>Clustering</subject><subject>Complex network theory</subject><subject>Hazard identification</subject><subject>Metro operation hazard network (MOHN)</subject><subject>Occupational hazards</subject><subject>Operational hazards</subject><subject>Public safety</subject><subject>Safety</subject><subject>Safety analysis</subject><subject>Shortest-path problems</subject><subject>Structural characteristics</subject><subject>Studies</subject><issn>0925-7535</issn><issn>1879-1042</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9UE1LAzEQDaJgrf4BTwEvetg1n5sWvBRRK1R70XNIsxO7td2sSWqtv96UehOcywyP997MPITOKSkpodX1oozRNiXLcwZKQskB6tGBGhaUCHaIemTIZKEkl8foJMYFIYTyivaQG-EWNth0XfDGznHyeN3WEGIybY1XkILHvoNgUuNbHI2DtMWzLYavbulD07794czNtwl1dk0bH97x5dN0_Hx1io6cWUY4--199Hp_93I7LibTh8fb0aSwfChS4QSXRNXWEMK4qyyXTs0qIeiACsclWKNygVWS1o6B4LRmqhJUWctU1vE-utj75nc-1hCTXvh1aPNKTYdCKiaYJJnF9iwbfIwBnO5CszJhqynRuzz1Qu_y1Ls8d1jOM4tu9iLI9382EHRmQGuhbgLYpGvf_Cf_AbIQfsA</recordid><startdate>201703</startdate><enddate>201703</enddate><creator>Li, Qiming</creator><creator>Song, Liangliang</creator><creator>List, George F.</creator><creator>Deng, Yongliang</creator><creator>Zhou, Zhipeng</creator><creator>Liu, Ping</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T2</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>NAPCQ</scope></search><sort><creationdate>201703</creationdate><title>A new approach to understand metro operation safety by exploring metro operation hazard network (MOHN)</title><author>Li, Qiming ; Song, Liangliang ; List, George F. ; Deng, Yongliang ; Zhou, Zhipeng ; Liu, Ping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c394t-f43507dca0023f6c35f7b6441814f35eca7777ec751df2e431d276417cc277dc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Accident analysis</topic><topic>Accident prevention</topic><topic>Accidents</topic><topic>Cities</topic><topic>Clustering</topic><topic>Complex network theory</topic><topic>Hazard identification</topic><topic>Metro operation hazard network (MOHN)</topic><topic>Occupational hazards</topic><topic>Operational hazards</topic><topic>Public safety</topic><topic>Safety</topic><topic>Safety analysis</topic><topic>Shortest-path problems</topic><topic>Structural characteristics</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Qiming</creatorcontrib><creatorcontrib>Song, Liangliang</creatorcontrib><creatorcontrib>List, George F.</creatorcontrib><creatorcontrib>Deng, Yongliang</creatorcontrib><creatorcontrib>Zhou, Zhipeng</creatorcontrib><creatorcontrib>Liu, Ping</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Nursing & Allied Health Premium</collection><jtitle>Safety science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Qiming</au><au>Song, Liangliang</au><au>List, George F.</au><au>Deng, Yongliang</au><au>Zhou, Zhipeng</au><au>Liu, Ping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new approach to understand metro operation safety by exploring metro operation hazard network (MOHN)</atitle><jtitle>Safety science</jtitle><date>2017-03</date><risdate>2017</risdate><volume>93</volume><spage>50</spage><epage>61</epage><pages>50-61</pages><issn>0925-7535</issn><eissn>1879-1042</eissn><abstract>•An analytical framework is developed to analyze the interactions among metro hazards.•Metro operation hazard network (MOHN) is built based on accident database.•Complex network theory (CNM) is employed to explore the inherent features of MOHN.•MOHN captures the scale-free property as well as the small world property.
Numerous metro accidents expose the vulnerability of metro system. As cities are rapidly building and expanding metro systems, it is essential to thoroughly explore the nature of metro operation safety. Metro accidents can be regarded as an emergent property that arises from the unusual interactions of system components. These interactions could give rise to the phenomenon that several interrelated hazards simultaneously emerge in one single accident. Understanding these interrelations among hazards is indispensable to study metro operation safety. From this standpoint, 28 hazards and 48 interrelations among hazards were identified from 134 accidents and expert interviews, which were the foundation of establishing metro operation hazard network (MOHN). Whereby complex network theory, seven parameters were applied to further reveal the structural properties of MOHN. The results indicate that the MOHN is a scale-free network for the cumulative degree distribution obeys power-law distribution. The scale-free property of MOHN is indicative of its robustness to random attacks and its vulnerability to deliberate attacks. Nichetargeting controlling hazards of high degrees and betweenness centrality can significantly decrease the metro operation risks. Moreover, MOHN also possesses the small-world property for having a relatively high clustering coefficient and small shortest path length. This indicates that risks would be transmitted very quickly in MOHN. Secondary and derivative hazards should receive enough attention for the rapid propagation of MOHN. Revealing the inherent properties of MOHN assist in making beforehand strategies prior to metro accident and contributes to elevate system safety of metro operation.</abstract><cop>Amsterdam</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ssci.2016.10.010</doi><tpages>12</tpages></addata></record> |
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subjects | Accident analysis Accident prevention Accidents Cities Clustering Complex network theory Hazard identification Metro operation hazard network (MOHN) Occupational hazards Operational hazards Public safety Safety Safety analysis Shortest-path problems Structural characteristics Studies |
title | A new approach to understand metro operation safety by exploring metro operation hazard network (MOHN) |
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