Analysis of vehicle driving behavior on special road segments using context-specific information

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dc.contributor.author Sridhar, Shankar
dc.contributor.department Electrical and Computer Engineering
dc.contributor.majorProfessor Daji Qiao
dc.date 2020-01-07T20:22:26.000
dc.date.accessioned 2020-06-30T01:34:59Z
dc.date.available 2020-06-30T01:34:59Z
dc.date.copyright Tue Jan 01 00:00:00 UTC 2019
dc.date.issued 2019-01-01
dc.description.abstract <p>Typical telematics and fleet-management systems today use embedded systems attached to the vehicle and get their driving data from their diagnostics port to identify the action of driver and grade it to provide feedback based on their quality of driving to efficiently handle the vehicle and also their driving behavior. Today’s insurance companies provide embedded devices or the customer’s smartphone to analyze basic driving parameters such as speed, rpm, GPS location to understand driver’s braking, acceleration and distance traveled over a period and use it to assess quotes for insurance premium. But most of the solutions above do not consider of context-specific information in the cases of fixed-route scenarios whose details can be understood better in the first place and use it to grade the driver’s performance for the trip more efficiently. In this experiment, a driver’s behavior on a pre-defined route is analyzed on different perspectives by also taking into account of the road context, such as turns, straight road segments, traffic lights, stop signs, etc. and graded accordingly and providing a score to reflect their behavior in each segment of the road as well as a complete score for their trip</p>
dc.format.mimetype PDF
dc.identifier archive/lib.dr.iastate.edu/creativecomponents/431/
dc.identifier.articleid 1439
dc.identifier.contextkey 15860394
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath creativecomponents/431
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/16991
dc.source.bitstream archive/lib.dr.iastate.edu/creativecomponents/431/cc_report.pdf|||Sat Jan 15 00:15:39 UTC 2022
dc.subject.disciplines Other Computer Engineering
dc.subject.keywords telematics
dc.subject.keywords OBD
dc.subject.keywords driving
dc.subject.keywords behavior
dc.subject.keywords raspberrypi
dc.subject.keywords CAN
dc.title Analysis of vehicle driving behavior on special road segments using context-specific information
dc.type article
dc.type.genre creativecomponent
dspace.entity.type Publication
relation.isOrgUnitOfPublication a75a044c-d11e-44cd-af4f-dab1d83339ff
thesis.degree.discipline Computer Engineering
thesis.degree.level creativecomponent
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