{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T05:33:36Z","timestamp":1783661616121,"version":"3.55.0"},"reference-count":64,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/OAPA.html"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61300101"],"award-info":[{"award-number":["61300101"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key Research Plan of Jiangsu Province","award":["BE2017035"],"award-info":[{"award-number":["BE2017035"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2019]]},"DOI":"10.1109\/access.2019.2920489","type":"journal-article","created":{"date-parts":[[2019,6,3]],"date-time":"2019-06-03T23:10:54Z","timestamp":1559603454000},"page":"78515-78532","source":"Crossref","is-referenced-by-count":110,"title":["Impact of Driver Behavior on Fuel Consumption: Classification, Evaluation and Prediction Using Machine Learning"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7283-8043","authenticated-orcid":false,"given":"Peng","family":"Ping","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenhu","family":"Qin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chiyomi","family":"Miyajima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kazuya","family":"Takeda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/I2MTC.2018.8409675"},{"key":"ref38","author":"cohen","year":"1988","journal-title":"Statistical Power Analysis for the Behavioral Sciences"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s11222-007-9033-z"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.15837\/ijccc.2010.5.2221"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"792","DOI":"10.1049\/iet-its.2014.0139","article-title":"Leveraging longitudinal driving behaviour data with data mining techniques for driving style analysis","volume":"9","author":"wu","year":"2015","journal-title":"IET Intell Transp Syst"},{"key":"ref37","year":"2019","journal-title":"Pearson Correlation - SPSS Tutorial"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.trd.2009.05.009"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2018.12.006"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/UIC-ATC.2017.8397525"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.14358\/PERS.70.12.1365"},{"key":"ref62","year":"2019","journal-title":"Support Vector Machines for Binary Classification"},{"key":"ref61","first-page":"196","article-title":"Face recognition by support vector machines","author":"guo","year":"2000","journal-title":"Proc 4th IEEE Int Conf Autom Face Gesture Recognit (FG)"},{"key":"ref63","first-page":"329","article-title":"AUC: A better measure than accuracy in comparing learning algorithms","volume":"2671","author":"ling","year":"2003","journal-title":"Proc 16th Conf Can Soc Comput Stud Intell AI"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1080\/15568318.2018.1445321"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s10979-005-6832-7"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2015.08.062"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2015.2492923"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2015.04.092"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jclepro.2017.10.194"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2443980"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2015.02.007"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JCN.2017.000025"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2018.2850031"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"13866","DOI":"10.1016\/j.ifacol.2017.08.2233","article-title":"Driving style modelling for eco-driving applications","volume":"50","author":"trigui","year":"2017","journal-title":"IFAC-PapersOnLine"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/S1361-9209(00)00003-1"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.ergon.2006.12.003"},{"key":"ref50","article-title":"YOLOv3: An incremental improvement","author":"redmon","year":"2018","journal-title":"arXiv1804 02767"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1179"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.3115\/1614108.1614129"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"ref57","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2017","journal-title":"arXiv 1412 6980"},{"key":"ref56","year":"2019","journal-title":"Class LSTMCell"},{"key":"ref55","year":"2019","journal-title":"Tensorflow tutorials"},{"key":"ref54","doi-asserted-by":"crossref","first-page":"533","DOI":"10.1038\/323533a0","article-title":"Learning representations by back-propagating errors","volume":"323","author":"rumelhart","year":"1986","journal-title":"Nature"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2603007"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3020078.3021745"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2015.04.010"},{"key":"ref11","first-page":"10","article-title":"An incremental learning technique for detecting driving behaviors using collected EV big data","author":"lee","year":"2015","journal-title":"Proceedings of the ACM ASE BigData & SocialInformatics"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/263867.263872"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.tra.2017.08.014"},{"key":"ref13","article-title":"Understanding and quantifying motor vehicle emissions with vehicle specific power and TILDAS remote sensing","author":"jimnez-palacios","year":"1999"},{"key":"ref14","first-page":"1","article-title":"NCHRP PROJECT 25-11: Development of a comprehensive modal emissions model","author":"barth","year":"2000","journal-title":"Proc 7th CRC Road Vehicle Emissions Workshop"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1177\/0361198105193900118"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1111\/mice.12344"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2012.2187447"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2013.11.009"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1080\/15472450.2012.712494"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.scitotenv.2016.06.248"},{"key":"ref3","year":"2011","journal-title":"Health in the Green Economy Health Co-Benefits of Climate Change Mitigation"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CCNC.2015.7158016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2011.2142182"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2014.2336271"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2014.6856440"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2879887"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2009.10.021"},{"key":"ref46","year":"2019","journal-title":"Apache SPARK"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2011.11.005"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/S0031-3203(02)00060-2"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.6028\/jres.045.026"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/34.868688"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/43.159993"},{"key":"ref44","first-page":"849","article-title":"On spectral clustering: Analysis and an algorithm","author":"ng","year":"2001","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref43","first-page":"744","article-title":"Between min cut and graph bisection","author":"wagner","year":"1993","journal-title":"Proc Int l Symp Mathematical Foundations of Computer Science"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8600701\/08727915.pdf?arnumber=8727915","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,27]],"date-time":"2022-01-27T17:53:20Z","timestamp":1643306000000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8727915\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":64,"URL":"https:\/\/doi.org\/10.1109\/access.2019.2920489","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019]]}}}