Twisted Metal: An Investigation into Observable Factors that Lead to Critical Traffic Events

dc.contributor.authorKieliszewski, Cheryl A.en
dc.contributor.committeechairDingus, Thomas A.en
dc.contributor.committeememberKleiner, Brian M.en
dc.contributor.committeememberNeale, Vicki L.en
dc.contributor.committeememberSmith-Jackson, Tonya L.en
dc.contributor.committeememberHankey, Jonathan M.en
dc.contributor.departmentIndustrial and Systems Engineeringen
dc.date.accessioned2014-03-14T20:19:35Zen
dc.date.adate2005-12-09en
dc.date.available2014-03-14T20:19:35Zen
dc.date.issued2005-10-24en
dc.date.rdate2005-12-09en
dc.date.sdate2005-12-01en
dc.description.abstractThe purpose of this research was to explore traffic event severity relationships, evaluate the potentiality of a hazardous event, and develop a framework of observable event factors. Data was collected from three regions in Virginia, each assumed to exemplify a unique driving environment due to amount of traffic and infrastructure characteristics. In combination, a broad spectrum of site, traffic, and driver performance variables were accounted for. Observational techniques of surveillance, incident reporting, and inventorying were used to collect site, traffic, and driver data. This effort resulted in 368 observed traffic events that were evenly distributed among the three regions that represented metropolitan, mid-sized city, and town/rural driving environments. The 368 events were evaluated for severity and contributing variables where 1% of the events were non-injury crashes, 10% were serious, near-crashes, 24% were near-crashes, and the remaining 65% were serious errors with a hazard present. Exploratory analyses were performed to understand the general relationship between event severity levels. Binary logistic regression analyses (α = 0.05) were performed to further scope predictor variables to identify traffic event characteristics with respect to severity level, maneuver type, and conflict type. The results were that 69 of 162 observed predictor variables were valuable in characterizing traffic events based on severity. It was found that variables could be grouped to create event severity signatures for crashes, serious near-crashes, and near-crashes. Based on these signatures, it was found that there is a trend between severity levels that included a propensity for problems with straight path maneuvers, lateral and longitudinal vehicle control, and information density within the driving environment as contributing to driver error and hence crashes and near-crashes. There were also differences between the severity levels. These differences were evident in the degree of control the driver appeared to have of the vehicle, type of control regulating the driving environment, and type of road users present in the driving environment. Modifications to roadway evaluative techniques would increase awareness of additional variables that impact drivers to make more informed decisions for roadway enhancements.en
dc.description.degreePh. D.en
dc.identifier.otheretd-12012005-173602en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12012005-173602/en
dc.identifier.urihttp://hdl.handle.net/10919/29859en
dc.publisherVirginia Techen
dc.relation.haspartKieliszewskiDissertation.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectcrash investigationen
dc.subjectcrash analysisen
dc.subjectautomotiveen
dc.subjectnear-missen
dc.subjectdriver behavioren
dc.titleTwisted Metal: An Investigation into Observable Factors that Lead to Critical Traffic Eventsen
dc.typeDissertationen
thesis.degree.disciplineIndustrial and Systems Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en
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