{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T15:42:35Z","timestamp":1785858155704,"version":"3.56.0"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T00:00:00Z","timestamp":1569888000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,10]]},"DOI":"10.1109\/itsc.2019.8917149","type":"proceedings-article","created":{"date-parts":[[2019,11,29]],"date-time":"2019-11-29T11:11:50Z","timestamp":1575025910000},"page":"2736-2742","source":"Crossref","is-referenced-by-count":42,"title":["Vision-Based Trajectory Planning via Imitation Learning for Autonomous Vehicles"],"prefix":"10.1109","author":[{"given":"Peide","family":"Cai","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuxiang","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuying","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ming","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2018.8500440"},{"key":"ref11","article-title":"End-to-end deep learning for steering autonomous vehicles considering temporal dependencies","author":"eraqi","year":"2017"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460487"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.376"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1177\/0278364916679498"},{"key":"ref15","first-page":"305","article-title":"Alvinn: An autonomous land vehicle in a neural network","author":"pomerleau","year":"1989","journal-title":"Advances in neural information processing systems"},{"key":"ref16","article-title":"Intention-net: Integrating planning and deep learning for goal-directed autonomous navigation","author":"gao","year":"2017"},{"key":"ref17","article-title":"Deep Path Planning Using Images and Object Data","author":"bergqvist","year":"2018","journal-title":"Master&#x2019;s thesis"},{"key":"ref18","article-title":"Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst","author":"bansal","year":"2018"},{"key":"ref19","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2019.2904733"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TASE.2019.2894748"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3200\/35-09-004-RC"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2018.07.002"},{"key":"ref6","article-title":"Driving like a human: Imitation learning for path planning using convolutional neural networks","author":"rehder","year":"2017","journal-title":"International Conference on Robotics and Automation Workshop"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIV.2016.2578706"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-control-060117-105157"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68345-4_9"},{"key":"ref2","article-title":"Movable-object-aware visual slam via weakly supervised semantic segmentation","author":"sun","year":"2019"},{"key":"ref9","article-title":"End to end learning for self-driving cars","author":"bojarski","year":"2016"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.robot.2016.11.012"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.597"},{"key":"ref21","article-title":"Mask r-cnn for object detection and instance segmentation on keras and tensorflow","author":"abdulla","year":"2017"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00567"},{"key":"ref23","article-title":"3d_detection","year":"2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2009.5459260"},{"key":"ref25","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"}],"event":{"name":"2019 IEEE Intelligent Transportation Systems Conference - ITSC","location":"Auckland, New Zealand","start":{"date-parts":[[2019,10,27]]},"end":{"date-parts":[[2019,10,30]]}},"container-title":["2019 IEEE Intelligent Transportation Systems Conference (ITSC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8907344\/8916833\/08917149.pdf?arnumber=8917149","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T15:22:29Z","timestamp":1658157749000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8917149\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,10]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/itsc.2019.8917149","relation":{},"subject":[],"published":{"date-parts":[[2019,10]]}}}