{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T14:47:27Z","timestamp":1773931647628,"version":"3.50.1"},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,2,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The dissertation approaches the questions i) how to represent the driving environment in an environment model, ii) how to\nobtain such a representation, and iii) how to predict the traffic scene for criticality assessment. Bayesian inference\nprovides the common framework of all designed methods. First, Parametric Free Space (PFS) maps are introduced, which\ncompactly represent the vehicle environment in form of relevant, drivable free space. They are obtained by a novel method\nfor grid mapping and tracking in dynamic environments. In addition, a maneuver-based, long-term trajectory prediction and\ncriticality assessment system is introduced and the application of all methods within the advanced driver assistance\nsystem PRORETA 3 is described.<\/jats:p>","DOI":"10.1515\/auto-2016-0129","type":"journal-article","created":{"date-parts":[[2017,2,7]],"date-time":"2017-02-07T10:02:03Z","timestamp":1486461723000},"page":"151-152","source":"Crossref","is-referenced-by-count":24,"title":["Bayesian environment representation, prediction, and criticality assessment for driver assistance systems"],"prefix":"10.1515","volume":"65","author":[{"given":"Matthias","family":"Schreier","sequence":"first","affiliation":[{"name":"Continental Teves AG & Co. oHG, Advanced Engineering, Guerickestr. 7, 60488 Frankfurt am Main Germany"}]}],"member":"374","published-online":{"date-parts":[[2017,2,7]]},"container-title":["at - Automatisierungstechnik"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/auto.2017.65.issue-2\/auto-2016-0129\/auto-2016-0129.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0129\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0129\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T18:30:32Z","timestamp":1624300232000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0129\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,2,7]]},"references-count":0,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2017,2,7]]},"published-print":{"date-parts":[[2017,2,28]]}},"alternative-id":["10.1515\/auto-2016-0129"],"URL":"https:\/\/doi.org\/10.1515\/auto-2016-0129","relation":{},"ISSN":["0178-2312","2196-677X"],"issn-type":[{"value":"0178-2312","type":"print"},{"value":"2196-677X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,2,7]]}}}