Reference Machine Vision for ADAS Functions

dc.contributor.authorNayak, Abhisheken
dc.contributor.authorRathinam, Sivakumaren
dc.contributor.authorPike, Adamen
dc.date.accessioned2021-07-19T11:56:37Zen
dc.date.available2021-07-19T11:56:37Zen
dc.date.issued2021-05en
dc.description.abstractStudies have shown that fatalities due to unintentional roadway departures can be significantly reduced if Lane Departure Warning and Lane Keep Assist systems are used effectively. However, these systems have not been widely adopted due, in part, to the lack of suitable standards for pavement markings that enable reliable functionality of sensor systems. The objective of this project is to develop a reference lane detection system that will provide a benchmark for evaluating different lane markings and perception algorithms. The project will also validate the effectiveness of lane markings’ material characteristics as well as the vision algorithms through a systematic testing of lane detection algorithms in a robust test/vehicle environment.en
dc.format.mimetypeapplication/pdfen
dc.identifier.urihttp://hdl.handle.net/10919/104206en
dc.language.isoenen
dc.publisherSAFE-D: Safety Through Disruption National University Transportation Centeren
dc.relation.ispartofseriesSAFE-D;04-115en
dc.rightsCC0 1.0 Universalen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.subjectlane detectionen
dc.subjectlane marking materialsen
dc.subjectcomputer visionen
dc.titleReference Machine Vision for ADAS Functionsen
dc.typeReporten
dc.type.dcmitypeTexten

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