{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,3]],"date-time":"2025-03-03T05:58:25Z","timestamp":1740981505579,"version":"3.38.0"},"reference-count":25,"publisher":"SAGE Publications","issue":"5","license":[{"start":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T00:00:00Z","timestamp":1645660800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Department of Science and Technology of Zhejiang","award":["No. 2022C01241, No. 2018C01058"],"award-info":[{"award-number":["No. 2022C01241, No. 2018C01058"]}]},{"DOI":"10.13039\/501100007928","name":"ningbo municipal bureau of science and technology","doi-asserted-by":"publisher","award":["No. 2018B10063, 2018B10064"],"award-info":[{"award-number":["No. 2018B10063, 2018B10064"]}],"id":[{"id":"10.13039\/501100007928","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering"],"published-print":{"date-parts":[[2022,5]]},"abstract":"<jats:p> An automated driving system should have the ability to supervise its own performance and to request human driver to take over when necessary. In the lane keeping scenario, the prediction of vehicle future trajectory is the key to realize safe and trustworthy driving automation. Previous studies on vehicle trajectory prediction mainly fall into two categories, that is, physics-based and manoeuvre-based methods. Using a physics-based methodology, this article proposes a lane departure prediction algorithm based on closed-loop vehicle dynamics model. We use extended Kalman filter to estimate the current vehicle states based on sensing module outputs. Then, a Kalman Predictor with actual lane keeping control law is used to predict steering actions and vehicle states in the future. A lane departure assessment module evaluates the probabilistic distribution of vehicle corner positions and decides whether to initiate a human takeover request. The prediction algorithm is capable to describe the stochastic characteristics of future vehicle pose, which is preliminarily proved in simulated tests. Finally, the on-road tests at speeds of 15\u201350\u2009km\/h further show that the proposed method can accurately predict vehicle future trajectory. It may work as a promising solution to lane departure risk assessment for automated lane keeping functions. <\/jats:p>","DOI":"10.1177\/09596518221079460","type":"journal-article","created":{"date-parts":[[2022,2,24]],"date-time":"2022-02-24T10:32:41Z","timestamp":1645698761000},"page":"913-926","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Lane departure prediction based on closed-loop vehicle dynamics"],"prefix":"10.1177","volume":"236","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6909-0169","authenticated-orcid":false,"given":"Daofei","family":"Li","sequence":"first","affiliation":[{"name":"Institute of Power Machinery and Vehicular Engineering, College of Energy Engineering, Zhejiang University, Hangzhou, China"}]},{"given":"Siyuan","family":"Lin","sequence":"additional","affiliation":[{"name":"Institute of Power Machinery and Vehicular Engineering, College of Energy Engineering, Zhejiang University, Hangzhou, China"}]},{"given":"Guanming","family":"Liu","sequence":"additional","affiliation":[{"name":"Institute of Power Machinery and Vehicular Engineering, College of Energy Engineering, Zhejiang University, Hangzhou, China"}]}],"member":"179","published-online":{"date-parts":[[2022,2,24]]},"reference":[{"first-page":"417","volume-title":"Proceedings of the 2009 IEEE 5th international conference on intelligent computer communication and processing","author":"Ammoun S","key":"bibr1-09596518221079460"},{"key":"bibr2-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2007.903439"},{"first-page":"907","volume-title":"Proceedings of the 2009 IEEE intelligent vehicles symposium","author":"Batz T","key":"bibr3-09596518221079460"},{"first-page":"1","volume-title":"Proceedings of the 2008 11th international conference on information fusion","author":"Schubert R","key":"bibr4-09596518221079460"},{"key":"bibr5-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2782236"},{"volume-title":"Proceedings of the WCX 2020 SAE world congress experience","author":"Xiao W","key":"bibr6-09596518221079460"},{"key":"bibr7-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1186\/s40648-014-0001-z"},{"key":"bibr8-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2006.883938"},{"key":"bibr9-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2010.2048314"},{"key":"bibr10-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2007.909241"},{"key":"bibr11-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2018.2854406"},{"issue":"9","key":"bibr12-09596518221079460","first-page":"1","volume":"10","author":"Yuan W","journal-title":"Adv Mech Eng"},{"first-page":"1625","volume-title":"Proceedings of the 13th international IEEE conference on intelligent transportation systems","author":"Gindele T","key":"bibr13-09596518221079460"},{"first-page":"797","volume-title":"Proceedings of the 2013 IEEE intelligent vehicles symposium (IV)","author":"Kumar P","key":"bibr14-09596518221079460"},{"first-page":"1","volume-title":"Proceedings of the 2017 IEEE 20th international conference on intelligent transportation systems (ITSC)","author":"Izquierdo R","key":"bibr15-09596518221079460"},{"first-page":"399","volume-title":"Proceedings of the 2017 IEEE 20th international conference on intelligent transportation systems","author":"Kim B","key":"bibr16-09596518221079460"},{"first-page":"1468","volume-title":"Proceedings of the 2018 IEEE\/CVF conference on computer vision and pattern recognition workshops","author":"Deo N","key":"bibr17-09596518221079460"},{"first-page":"2084","volume-title":"Proceedings of the 2020 IEEE winter conference on applications of computer vision","author":"Djuric N","key":"bibr18-09596518221079460"},{"first-page":"1179","volume-title":"Proceedings of the 2018 IEEE intelligent vehicles symposium (IV)","author":"Deo N","key":"bibr19-09596518221079460"},{"key":"bibr20-09596518221079460","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2017.2743204"},{"key":"bibr21-09596518221079460","unstructured":"Boulton FA, Grigore EC, Wolff EM. 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