Thesis (Ph. D.)--Virginia Commonwealth University, 2009. / Prepared for: Dept. of Public Policy and Administration. Title from title-page of electronic thesis. Bibliography: leaves 128-141.

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Over the past twenty years bicycle use as a mode of transportation has grown considerably in the United States. Other studies have examined the individual bicyclist’s risk in proportion to the growth in cycling across cities, a phenomenon referred to as ‘safety in numbers.’ This study expands from that research and examines the effect of cyclists on road safety for all road users. The study examines the roles of bicycle modal split, a city wide analysis, and bicycle infrastructure, a site based analysis, in road safety outcomes. For the city based analysis, twenty years of crash data in 12 California cities were analyzed over a 20 year period. This study primarily used census data and State wide Integrated Traffic Records System (SWITRS) data. This study concludes that as bicycle modal split increases in a city, the traffic fatalities tend to decrease and the relationship is an exponential function. The site based analysis focuses on the effects of installing a bicycle lane on a street and examined its effect on injury crashes. 20 sites in San Francisco, CA that had bike lanes installed on them were compared to 25 control group sites, also in San Francisco, that did not have any bike lanes or other significant changes. An Empirical Bayes method of analysis was done to test its effects and determined that the effects were statistically significant.

Road traffic injuries (RTI) currently rank as the 11th leading cause of death world wide and the leading cause of injury related deaths worldwide. Globally, road traffic crashes kill over 1.2 million people per year with over 90% of the deaths occurring in low and middle income countries. Pedestrians, cyclists, and motorcyclists, collectively called vulnerable road users, are often times the victims. Therefore, the purpose of this study was to identify the factors that are associated with traffic fatalities as well as the factors that are associated with being a vulnerable road user in traffic injuries and traffic fatalities in Pasto, Colombia. The results from this study showed that males had increased odds of being involved in a traffic fatality (OR=2.16 95%;CI 1.03-4.53). Rural road users are more likely to be involved in fatal traffic crashes than their urban counterparts (OR=5.92 95%;CI 3.00-11.71) Other groups such as young adults, vulnerable road users, and those not using safety equipment were also more likely to be injured or die in a traffic crash. Interventions specifically targeting these groups are needed.

A traditional two dimensional (planar) statistical analysis was used to identify the clustering types of North Central Texas traffic fatalities occurring in 2001-2006. Over 3,700 crash locations clustered in ways that were unlike other researched regions. A two dimensional (x and y coordinates) space was manipulated to mimic a one dimensional network to identify the tightest clustering of fatalities in the nearly 400,000 crashes reported from state agencies from 2003-2006. The roadway design was found to significantly affect crash location. A one dimensional (linear) network analysis was then used to measure the statistically significant clustering of flow variables of after dark crashes and daylight crashes. Flow variables were determined to significantly affect crash location after dark. The linear and planar results were compared and the one dimensional, linear analysis was found to be more accurate because it did not over detect the clustering of events on a network.

Neste trabalho é estimado o valor do índice de mortes por quilômetro percorrido pela frota de veículos rodoviários no Brasil e em cada estado da federação nos anos de 2004 a 2008. Para determinar os valores da quilometragem anual média dos veículos - parâmetro necessário para estimativa do índice de mortes por veículo - quilômetro - desenvolveu-se um método apropriado tomando como referência a quantidade de combustível vendida pelas distribuidoras em cada estado. Os estados foram classificados em relação a todos os índices associados à mortalidade viária, assim como analisadas as relações entre o índice de mortes por quilômetro e o nível de desenvolvimento econômico dos estados. Constata-se que a situação da mortalidade no trânsito é um grave problema nacional, sobretudo nos estados mais pobres, onde os índices de mortes por veículo-quilômetro atingem números extremamente elevados. O fato positivo é que os números apontam para uma redução contínua do índice de mortes por quilômetro, que passou de 68,26 para 55,87 mortes por bilhão de quilômetros no país entre 2004 e 2008 (queda de 18,15%). Isso se deve ao aumento da quilometragem percorrida, função do aumento da frota, do crescimento econômico e de certa estabilização do número de mortes; este último em decorrência de ações em âmbito nacional implementadas pelo governo federal, bem como de ações específicas levadas a efeito em alguns estados. / This research estimated the value of the rate of deaths per kilometer traveled by the road vehicles fleet in Brazil and in each of the states of the federation, in the years 2004 to 2008. To determine the values of the average annual distance traveled by vehicles - parameter needed to estimate the rate of deaths per vehicle-kilometers - an appropriate methodology has been developed with reference on the amount of fuel sold by distributors in every state. The states were ranked according to all indexes associated with road fatalities, and the relationship between the rate of deaths per kilometer and the level of economic development of states, expressed by the motorization rate and the GDP per capita, is analyzed. It appears that the situation of traffic mortality is a serious national problem, especially in the poorest states, where the rate of deaths per vehicle-km reaches very high figures. The positive fact is that the numbers point to a continued reduction in the rate of deaths per kilometer, which decreased from 68.26 to 55.87 deaths per billion km in the country between 2004 and 2008 (a decrease of 18.15%). This is due to the increase on the distance traveled, a result of the increased fleet and economic growth, and also of some stabilization in the number of deaths; being the last a consequence of nationwide actions implemented by the federal government, and also of specific actions carried out in some states.

Neste trabalho é estimado o valor do índice de mortes por quilômetro percorrido pela frota de veículos rodoviários no Brasil e em cada estado da federação nos anos de 2004 a 2008. Para determinar os valores da quilometragem anual média dos veículos - parâmetro necessário para estimativa do índice de mortes por veículo - quilômetro - desenvolveu-se um método apropriado tomando como referência a quantidade de combustível vendida pelas distribuidoras em cada estado. Os estados foram classificados em relação a todos os índices associados à mortalidade viária, assim como analisadas as relações entre o índice de mortes por quilômetro e o nível de desenvolvimento econômico dos estados. Constata-se que a situação da mortalidade no trânsito é um grave problema nacional, sobretudo nos estados mais pobres, onde os índices de mortes por veículo-quilômetro atingem números extremamente elevados. O fato positivo é que os números apontam para uma redução contínua do índice de mortes por quilômetro, que passou de 68,26 para 55,87 mortes por bilhão de quilômetros no país entre 2004 e 2008 (queda de 18,15%). Isso se deve ao aumento da quilometragem percorrida, função do aumento da frota, do crescimento econômico e de certa estabilização do número de mortes; este último em decorrência de ações em âmbito nacional implementadas pelo governo federal, bem como de ações específicas levadas a efeito em alguns estados. / This research estimated the value of the rate of deaths per kilometer traveled by the road vehicles fleet in Brazil and in each of the states of the federation, in the years 2004 to 2008. To determine the values of the average annual distance traveled by vehicles - parameter needed to estimate the rate of deaths per vehicle-kilometers - an appropriate methodology has been developed with reference on the amount of fuel sold by distributors in every state. The states were ranked according to all indexes associated with road fatalities, and the relationship between the rate of deaths per kilometer and the level of economic development of states, expressed by the motorization rate and the GDP per capita, is analyzed. It appears that the situation of traffic mortality is a serious national problem, especially in the poorest states, where the rate of deaths per vehicle-km reaches very high figures. The positive fact is that the numbers point to a continued reduction in the rate of deaths per kilometer, which decreased from 68.26 to 55.87 deaths per billion km in the country between 2004 and 2008 (a decrease of 18.15%). This is due to the increase on the distance traveled, a result of the increased fleet and economic growth, and also of some stabilization in the number of deaths; being the last a consequence of nationwide actions implemented by the federal government, and also of specific actions carried out in some states.

This dissertation examines the use of statistical models for prediction. Examples are drawn from public policy and chosen because they represent pressing problems facing U.S. governments at the local, state, and federal level. The first five chapters provide examples where the perfunctory use of linear models, the prediction tool of choice in government, failed to produce reasonable predictions. Methodological flaws are identified, and more accurate models are proposed that draw on advances in statistics, data science, and machine learning. Chapter 1 examines skyscraper construction, where the normality assumption is violated and extreme value analysis is more appropriate. Chapters 2 and 3 examine presidential approval and voting (a leading measure of civic participation), where the non-collinearity assumption is violated and an index model is more appropriate. Chapter 4 examines changes in temperature sensitivity due to global warming, where the linearity assumption is violated and a first-hitting-time model is more appropriate. Chapter 5 examines the crime rate, where the independence assumption is violated and a block model is more appropriate. The last chapter provides an example where simple linear regression was overlooked as providing a sensible solution. Chapter 6 examines traffic fatalities, where the linear assumption provides a better predictor than the more popular non-linear probability model, logistic regression. A theoretical connection is established between the linear probability model, the influence score, and the predictivity.

Southeastern states have about 26 percent of the nations total fatalities, and are about 24 percent above the national mean over recent years. Descriptive statistics, graphs, and figures are used to illustrate and quantify the crash trends, which depict a comprehensive picture of status and trends of the fatal crashes in southeastern states. The severity of crashes is studied as a function of characteristics of the person involved in the crash, vehicle, traffic condition, physical road geometry, and environmental factors. Detailed geometric feature data were collected for this study, which makes it possible to investigate the relationship between geometric features and crash severity. This study identifies causal factors contributing to the high fatality rate in southeastern states, and sheds light on the differences and similarities among these states for reducing the severity of fatal crashes, by developing multinomial logit models to explain the severity and type of fatal crashes.

Thesis (M.Sc. (Statistics)) -- University of Limpopo, 2020 / Background: Death and economic losses due to road traffic accidents (RTA) are huge global public health and developmental problems and need urgent attention. Each year nearly 1.24 million people die and millions suffer various forms of disability as a result of road accidents. This puts road traffic injuries (RTIs) as the eighth leading cause of death globally and RTIs are set to become the fifth leading cause of death worldwide by the year 2030 unless urgent actions are taken. Aim: In this paper, we investigate factors that contribute to road traffic deaths (RTDs) in the Limpopo province of South Africa using models such as the generalized linear models (GLM) and zero inflated models. Methods: The study was based on retrospective data that comprised of reports of 18,029 road traffic accidents and 4,944 road traffic deaths over the years 2009 – 2015. Generalized linear modelling and zero-inflated models were used to identify factors and determine their relationships to RTDs. Results: The data was split into two categories: deaths that occurred during holidays and those that occurred during non-holiday periods. It was found that the following variables, namely, Monday, human actions, vehicle conditions and vehicle makes, were significant predictors of RTDs during holidays. On the other hand, during non-holiday periods, weekend, Tuesday, Wednesday, national road, provincial road, sedan, LDV, combi and bus were found to be significant predictors of road traffic deaths. Conclusion: GLM techniques, such as the standard Poisson regression model and the negative binomial (NB) model, did little to explain the zero excess, therefore, zero-inflated models, such as zero-inflated negative binomial (ZINB), were found to be useful in explaining excess zeros. Recommendation: The study recommends that the government should make more human power available during the festive seasons, such as the December holidays, and over weekends.