Application of Naturalistic Truck Driving Data to Analyze and Improve Car Following Models

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dc.contributor.authorHiggs, Bryan Jamesen
dc.contributor.committeechairAbbas, Montasir M.en
dc.contributor.committeememberMedina, Alejandraen
dc.contributor.committeememberGuo, Fengen
dc.contributor.departmentCivil Engineeringen
dc.date.accessioned2014-03-14T20:49:23Zen
dc.date.adate2012-01-03en
dc.date.available2014-03-14T20:49:23Zen
dc.date.issued2011-12-02en
dc.date.rdate2012-01-03en
dc.date.sdate2011-12-12en
dc.description.abstractThis research effort aims to compare car-following models when the models are calibrated to individual drivers with the naturalistic data. The models used are the GHR, Gipps, Intelligent Driver, Velocity Difference, Wiedemann, and the Fritzsche model. This research effort also analyzes the Wiedemann car-following model using car-following periods that occur at different speeds. The Wiedemann car-following model uses thresholds to define the different regimes in car following. Some of these thresholds use a speed parameter, but others rely solely upon the difference in speed between the subject vehicle and the lead vehicle. This research effort also reconstructs the Wiedemann car-following model for truck driver behavior using the Naturalistic Truck Driving Study's (NTDS) conducted by Virginia Tech Transportation Institute. This Naturalistic data was collected by equipping 9 trucks with various sensors and a data acquisition system. This research effort also combines the Wiedemann car-following model with the GHR car-following model for trucks using The Naturalistic Truck Driving Study's (NTDS) data.en
dc.description.degreeMaster of Scienceen
dc.identifier.otheretd-12122011-152121en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12122011-152121/en
dc.identifier.urihttp://hdl.handle.net/10919/36089en
dc.publisherVirginia Techen
dc.relation.haspartHiggs_BJ_T_2011.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectGHR Modelen
dc.subjectWiedemann Modelen
dc.subjectCar Followingen
dc.subjectNaturalistic Dataen
dc.titleApplication of Naturalistic Truck Driving Data to Analyze and Improve Car Following Modelsen
dc.typeThesisen
thesis.degree.disciplineCivil Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.levelmastersen
thesis.degree.nameMaster of Scienceen

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