Show simple item record

dc.contributorVirginia Tech. Virginia Tech Transportation Instituteen_US
dc.contributor.authorWang, B.en_US
dc.contributor.authorHallmark, S.en_US
dc.contributor.authorOneyear, N.en_US
dc.date.accessioned2015-07-01T18:07:57Z
dc.date.available2015-07-01T18:07:57Z
dc.date.issued2014-08-25en_US
dc.identifier.citationWang, B., Hallmark, S., & Oneyear, N. (2014, August). Time Series Analysis of Driver Behavior on Curves. Paper presented at the Fourth International Symposium on Naturalistic Driving Research, Blacksburg, VA. Presentation retrieved from http://www.apps.vtti.vt.edu/PDFs/ndrs-2014/Wang-2014.pdfen_US
dc.identifier.urihttp://hdl.handle.net/10919/53987
dc.description.abstractOver half of motor vehicle fatalities are roadway departures, with rural horizontal curves being of particular interest because they make up only a small share of the system mileage but have a crash rate that is significantly higher than tangent sections. However the interaction between the driver and roadway environment is not well understood, and, as a result, it is difficult to select appropriate countermeasures. Method In order to address this knowledge gap, data from the SHRP 2 naturalistic driving study were used to develop relationships between driver, roadway, and environmental characteristics and risk of a road departure on rural curves. The SHRP 2 NDS collected data from over 3,000 male and female volunteer passenger vehicle drivers, ages 16–98, during a three year period, with most drivers participating between one to two years. A Roadway Information Database was collected in parallel and contains detailed roadway data collected on more than 12,500 centerline miles of highways in and around the study sites. Results Roadway data were reduced for rural 2-lane curves and included factors such as geometry, shoulder type, presence of rumble strips, etc. Environmental and traffic characteristics, such as time of day, ambient conditions, or whether the subject vehicle was following another vehicle, were reduced from the forward roadway video view. Driver characteristics, such as glance location and distraction were reduced from the driver and over the shoulder videos. Conclusions Logistic regression models were developed to assess the probability (odds) of a given type of encroachment based on driver, roadway, and environmental characteristics. At the point this study was undertaken, crashes and near crashes were not yet available and only around 1/3 of the full SHRP NDS dataset could be queried. As a result, the likelihood of crossing the right or left lane line (encroachments) and speeding were used as dependent variables.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoen_USen_US
dc.relation.urihttp://dx.doi.org/10.1016/j.jsr.2015.06.017en_US
dc.subjectRoadway encroachmenten_US
dc.subjectRural curvesen_US
dc.subjectSpeeden_US
dc.subjectRoadway countermeasuresen_US
dc.subjectNaturalistic driving studiesen_US
dc.titleTime Series Analysis of Driver Behavior on Curvesen_US
dc.title.alternativeEvaluation of driving behavior on rural 2-lane curves using the SHRP 2 naturalistic driving study dataen_US
dc.typePresentationen_US
dc.description.notesPresented at the Fourth International Symposium on Naturalistic Driving Research in Blacksburg, VAen_US
dc.identifier.urlhttp://www.apps.vtti.vt.edu/PDFs/ndrs-2014/Wang-2014.pdfen_US
dc.date.accessed2014-11-24en_US
dc.type.dcmitypeTexten_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record