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dc.contributor.advisorChairperson, Graduate Committee: Nicholas Warden
dc.contributor.authorBenzamanen
dc.coverage.spatialUnited Statesen
dc.date.accessioned2017-07-27T18:31:01Z
dc.date.available2017-07-27T18:31:01Z
dc.date.issued2017en
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/12755
dc.description.abstractStrategizing to decrease statewide road fatalities is an important aspect in road safety research in the United States. But obtaining information on a variety of variables, such as economic, socio-cultural, demographic and political factors, at the state level can be a difficult task. The public databases sometimes do not provide full information on these variables due to missing data. If these variables are neglected from the analysis because of missing data points. valuable information is lost in the process. Therefore, analyzing missing data has been considered as an additional step towards variable selection process in this thesis study. In order to impute the missing data, multiple imputation method was chosen. After the data imputation, the significant variables associated with road fatalities in 50 states were identified. This was done using a linear regression model which revealed that the top reasons for road fatalities are drunk driving, distracted driving and unemployment. In the process of linear regression modelling 48 predictive models were obtained. During the process of data collection, it was observed that data sources did not offer necessary information on road safety culture, behaviors, norms, attitudes and beliefs related to road fatality. This study offers two solutions for inferring a road safety culture and understanding its effects. The first solution was to analyze residuals from random effects two-way panel regression model and to generate performance indicator of inferred road safety culture. From the value of the indicators it was clear which state was the safest twenty years ago and which state is the safest now. Through the change in the value of the indicator, a state's progress in terms of safety culture was also measured. The second solution was to use people's political views on the democratic party and the republican party as a proxy for the road safety culture. This resulted in a significant increase in the goodness of fit for the linear regression model. This thesis provides prediction models, significant factors, and performance indicators of a road safety culture which can be used in state level road safety strategy development and policy making.en
dc.language.isoenen
dc.publisherMontana State University - Bozeman, College of Engineeringen
dc.subject.lcshDeath.en
dc.subject.lcshTraffic safety.en
dc.subject.lcshForecasting.en
dc.titleAn analysis of road traffic factors and road safety strategies that predict road fatalities over time across fifty states in USAen
dc.typeThesisen
dc.rights.holderCopyright 2017 by Benzamanen
thesis.degree.committeemembersMembers, Graduate Committee: Nicholas Ward (chairperson); Steven Swinford; Bill Schell; David Claudio.en
thesis.degree.departmentMechanical & Industrial Engineering.en
thesis.degree.genreThesisen
thesis.degree.nameMSen
thesis.format.extentfirstpage1en
thesis.format.extentlastpage193en
mus.data.thumbpage70en


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