{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T20:24:09Z","timestamp":1781382249775,"version":"3.54.1"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000140","name":"U.S. Department of Transportation, Office of the Assistant Secretary for Research and Technology","doi-asserted-by":"publisher","award":["69A3551847102"],"award-info":[{"award-number":["69A3551847102"]}],"id":[{"id":"10.13039\/100000140","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008982","name":"Qatar National Research Fund (a member of Qatar Foundation) under NPRP","doi-asserted-by":"publisher","award":["NPRP8-910-2-387"],"award-info":[{"award-number":["NPRP8-910-2-387"]}],"id":[{"id":"10.13039\/100008982","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Intell. Transport. Syst."],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1109\/tits.2021.3131596","type":"journal-article","created":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T20:37:39Z","timestamp":1639168659000},"page":"14689-14701","source":"Crossref","is-referenced-by-count":47,"title":["A Distributed Multi-Agent Reinforcement Learning With Graph Decomposition Approach for Large-Scale Adaptive Traffic Signal Control"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5243-6656","authenticated-orcid":false,"given":"Shan","family":"Jiang","sequence":"first","affiliation":[{"name":"Johnson and Johnson Supply Chain, Bridgewater, NJ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9996-9190","authenticated-orcid":false,"given":"Yufei","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Rutgers University—New Brunswick, Piscataway, NJ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohsen","family":"Jafari","sequence":"additional","affiliation":[{"name":"Department of Industrial and Systems Engineering, Rutgers University—New Brunswick, Piscataway, NJ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6059-3942","authenticated-orcid":false,"given":"Mohammad","family":"Jalayer","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Rowan University, Glassboro, NJ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Dota 2 with large scale deep reinforcement learning","author":"berner","year":"2019","journal-title":"arXiv 1912 06680"},{"key":"ref38","article-title":"Self-organizing traffic lights","author":"gershenson","year":"2004","journal-title":"arXiv 0411066"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3034419"},{"key":"ref32","article-title":"IG-RL: Inductive graph reinforcement learning for massive-scale traffic signal control","author":"devailly","year":"2020","journal-title":"arXiv 2003 05738"},{"key":"ref31","article-title":"Prioritized experience replay","author":"schaul","year":"2016","journal-title":"arXiv 1511 05952"},{"key":"ref30","first-page":"1995","article-title":"Dueling network architectures for deep reinforcement learning","author":"wang","year":"2015","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref37","article-title":"A K-means clustering method to urban intersection traffic state identification using interval data","author":"rao","year":"2016"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ACC.2016.7525014"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2901791"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2010.2091408"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1002\/atr.1456"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.17226\/22097"},{"key":"ref40","author":"abadi","year":"2016","journal-title":"Tensorflow A system for large-scale machine learning"},{"key":"ref12","author":"skabardonis","year":"2010","journal-title":"Measure and field test the effectiveness of adaptive control for traffic signal management"},{"key":"ref13","article-title":"Advanced traffic signal control algorithms","author":"skabardonis","year":"2013"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2004.838217"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2010.2050688"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1080\/15472450490435340"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2009.2034383"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2006.08.002"},{"key":"ref19","author":"sutton","year":"2018","journal-title":"Reinforcement Learning An Introduction"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2010.2070795"},{"key":"ref28","article-title":"Adaptive traffic signal control: Deep reinforcement learning algorithm with experience replay and target network","author":"gao","year":"2017","journal-title":"arXiv 1705 02755"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2009.05.003"},{"key":"ref27","article-title":"Deep reinforcement learning for traffic light control in vehicular networks","author":"liang","year":"2018","journal-title":"arXiv 1803 11115"},{"key":"ref6","first-page":"1","article-title":"Algorithms for the traffic light setting problem on the graph model","author":"chen","year":"2007","journal-title":"Taiwanese Assoc Artif Intell"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2008.4732676"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.10295"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1049\/iet-its.2018.0112"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/s18020435"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1227\/01.neu.0000393590.38637.f2"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1061\/(ASCE)TE.1943-5436.0000587"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1177\/0361198113235600102"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/BF00992698"},{"key":"ref22","first-page":"387","article-title":"Deterministic policy gradient algorithms","author":"silver","year":"2014","journal-title":"Proc 31st Int Conf Mach Learn"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1038\/nature14236","article-title":"Human-level control through deep reinforcement learning","volume":"518","author":"mnih","year":"2015","journal-title":"Nature"},{"key":"ref42","year":"2020","journal-title":"PTV Vistro Session 3-Signal Optimization"},{"key":"ref24","article-title":"Massively parallel methods for deep reinforcement learning","author":"nair","year":"2015","journal-title":"arXiv 1507 04296"},{"key":"ref41","article-title":"An overview of gradient descent optimization algorithms","author":"ruder","year":"2016","journal-title":"arXiv 1609 04747"},{"key":"ref23","first-page":"1008","article-title":"Actor-critic algorithms","author":"konda","year":"2000","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref26","first-page":"656","article-title":"Q-decomposition for reinforcement learning agents","author":"russell","year":"2003","journal-title":"Proc 20th Int Conf Mach Learn (ICML)"},{"key":"ref43","year":"2021","journal-title":"NYS traffic data viewer"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3307650.3322259"}],"container-title":["IEEE Transactions on Intelligent Transportation Systems"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6979\/9893028\/9646483-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6979\/9893028\/09646483.pdf?arnumber=9646483","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,3]],"date-time":"2022-10-03T20:18:44Z","timestamp":1664828324000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9646483\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":43,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tits.2021.3131596","relation":{},"ISSN":["1524-9050","1558-0016"],"issn-type":[{"value":"1524-9050","type":"print"},{"value":"1558-0016","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9]]}}}