{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T17:03:28Z","timestamp":1763226208746,"version":"3.37.3"},"reference-count":16,"publisher":"Wiley","license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51308298","51308311","2013-K5-20"],"award-info":[{"award-number":["51308298","51308311","2013-K5-20"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51308298","51308311","2013-K5-20"],"award-info":[{"award-number":["51308298","51308311","2013-K5-20"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005316","name":"Ministry of Housing and Urban-Rural Development","doi-asserted-by":"publisher","award":["51308298","51308311","2013-K5-20"],"award-info":[{"award-number":["51308298","51308311","2013-K5-20"]}],"id":[{"id":"10.13039\/501100005316","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2014]]},"abstract":"<jats:p>Pedestrian injuries and fatalities present a problem all over the world. Pedestrian conformity violation behaviors, which lead to many pedestrian crashes, are common phenomena at the signalized intersections in China. The concepts and metrics of complex networks are applied to analyze the structural characteristics and evolution rules of pedestrian network about the conformity violation crossings. First, a network of pedestrians crossing the street is established, and the network\u2019s degree distributions are analyzed. Then, by using the basic idea of SI model, a spreading model of pedestrian illegal crossing behavior is proposed. Finally, through simulation analysis, pedestrian\u2019s illegal crossing behavior trends are obtained in different network structures and different spreading rates. Some conclusions are drawn: as the waiting time increases, more pedestrians will join in the violation crossing once a pedestrian crosses on red firstly. And pedestrian\u2019s conformity violation behavior will increase as the spreading rate increases.<\/jats:p>","DOI":"10.1155\/2014\/865750","type":"journal-article","created":{"date-parts":[[2014,11,4]],"date-time":"2014-11-04T16:03:24Z","timestamp":1415117004000},"page":"1-7","source":"Crossref","is-referenced-by-count":3,"title":["Modeling Pedestrian\u2019s Conformity Violation Behavior: A Complex Network Based Approach"],"prefix":"10.1155","volume":"2014","author":[{"given":"Zhuping","family":"Zhou","sequence":"first","affiliation":[{"name":"Department of Traffic Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qizhou","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Traffic Engineering, Nanjing University of Science and Technology, Nanjing 210094, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Transportation, Southeast University, Nanjing 210096, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ssci.2009.03.010"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2006.07.003"},{"issue":"2264","key":"3","first-page":"65","year":"2012","journal-title":"Transportation Research Record"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1093\/her\/cyf023"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1005152515264"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.aap.2009.01.007"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.trf.2009.12.001"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1038\/30918"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1103\/RevModPhys.74.47"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.1080\/00018730601170527"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1016\/S0378-4371(99)00018-7"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2005.08.036"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2006.11.035"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2010.01.014"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1002\/cav.243"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1093\/beheco\/arq141"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2014\/865750.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2014\/865750.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2014\/865750.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2016,12,28]],"date-time":"2016-12-28T16:25:33Z","timestamp":1482942333000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/cin\/2014\/865750\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"references-count":16,"alternative-id":["865750","865750"],"URL":"https:\/\/doi.org\/10.1155\/2014\/865750","relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"type":"print","value":"1687-5265"},{"type":"electronic","value":"1687-5273"}],"subject":[],"published":{"date-parts":[[2014]]}}}