{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T13:19:44Z","timestamp":1779887984220,"version":"3.53.1"},"reference-count":24,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"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":[[2019,6]]},"DOI":"10.1109\/ivs.2019.8813881","type":"proceedings-article","created":{"date-parts":[[2019,8,29]],"date-time":"2019-08-29T21:11:26Z","timestamp":1567113086000},"page":"2215-2222","source":"Crossref","is-referenced-by-count":14,"title":["A Driving Scenario Representation for Scalable Real-Data Analytics with Neural Networks"],"prefix":"10.1109","author":[{"given":"Lennart","family":"Ries","sequence":"first","affiliation":[{"name":"FZI Research Center for Information Technology, Karlsruhe, 76131, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob","family":"Langner","sequence":"additional","affiliation":[{"name":"FZI Research Center for Information Technology, Karlsruhe, 76131, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Otten","sequence":"additional","affiliation":[{"name":"FZI Research Center for Information Technology, Karlsruhe, 76131, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Johannes","family":"Bach","sequence":"additional","affiliation":[{"name":"Dr. Ing. h.c. F. Porsche AG, Weissach, 71287, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric","family":"Sax","sequence":"additional","affiliation":[{"name":"FZI Research Center for Information Technology, Karlsruhe, 76131, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2016.7535534"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2015.164"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2018.8500464"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/app8122590"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1049\/iet-its.2018.0064"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2017.7995965"},{"key":"ref16","author":"bansal","year":"2018","journal-title":"Chauffeurnet Learning to drive by imitating the best and synthesizing the worst"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref18","first-page":"1310","article-title":"On the difficulty of training recurrent neural networks","author":"pascanu","year":"2013","journal-title":"International Conference on Machine Learning"},{"key":"ref19","author":"ghosh","year":"2016","journal-title":"Contextual lstm (clstm) models for large scale nlp tasks"},{"key":"ref4","article-title":"Database of relevant traffic scenarios database of relevant traffic scenarios","author":"zlocki","year":"2017","journal-title":"Autonomous Vehicle and Test Symposium"},{"key":"ref3","year":"0","journal-title":"Pegasus projekt"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2017.7995782"},{"key":"ref5","author":"waymo","year":"2017","journal-title":"Report on autonomous mode disengagements for Waymo self-driving vehicles in California"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639343"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2017.8317860"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IVS.2018.8500406"},{"key":"ref1","first-page":"425","article-title":"The release of autonomous vehicles","author":"wachenfeld","year":"2016","journal-title":"Autonomous Driving"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICDAR.2011.95"},{"key":"ref20","first-page":"843","article-title":"Unsupervised learning of video representations using lstms","author":"srivastava","year":"2015","journal-title":"International Conference on Machine Learning"},{"key":"ref22","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"2014","journal-title":"European Conference on Computer Vision"},{"key":"ref21","author":"goodfellow","year":"2016","journal-title":"Deep Learning"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1177\/0278364913491297"},{"key":"ref23","author":"madiraju","year":"2018","journal-title":"Deep Temporal Clustering Fully Unsupervised Learning of Time-Domain Features"}],"event":{"name":"2019 IEEE Intelligent Vehicles Symposium (IV)","location":"Paris, France","start":{"date-parts":[[2019,6,9]]},"end":{"date-parts":[[2019,6,12]]}},"container-title":["2019 IEEE Intelligent Vehicles Symposium (IV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8792328\/8813768\/08813881.pdf?arnumber=8813881","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,21]],"date-time":"2025-08-21T18:20:05Z","timestamp":1755800405000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8813881\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6]]},"references-count":24,"URL":"https:\/\/doi.org\/10.1109\/ivs.2019.8813881","relation":{},"subject":[],"published":{"date-parts":[[2019,6]]}}}