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dc.contributor.authorGorman, Thomasen
dc.date.accessioned2020-04-20T18:50:59Zen
dc.date.available2020-04-20T18:50:59Zen
dc.date.issued2020-04-20en
dc.identifier.urihttp://hdl.handle.net/10919/97842en
dc.description.abstractThe objective of this work was to build predictive models of driver intent at T-intersections based on vehicle speed, acceleration, brake pedal state, and speed limit data from the Second Strategic Highway Research Program. The generated models predict if the driver will go straight or turn right at the intersection. The models show promise in predictive ability and could be incorporated into an automated driving system to help inform the system when more conservative driving might be beneficial. However, the derived models should not be used as the only source for safety decision-making because the risk of a crash would be too high.en
dc.language.isoen_USen
dc.publisherNational Surface Transportation Safety Center for Excellenceen
dc.relation.ispartofseriesNSTSCE;20-UT-080en
dc.rightsCreative Commons CC0 1.0 Universal Public Domain Dedicationen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.subjectautomated vehiclesen
dc.subjectbig data analyticsen
dc.subjectmap matchingen
dc.subjecttransportation safetyen
dc.titleModeling Driver Intent in Potential Right Turning Scenariosen
dc.typeReporten


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Creative Commons CC0 1.0 Universal Public Domain Dedication
License: Creative Commons CC0 1.0 Universal Public Domain Dedication