Contrasting Rural and Urban Fatal Crashes, 1994-2003


Book Description

Data from the Fatality Analysis Reporting System (FARS) for the period 1994 2003 were used to compare the characteristics of fatal rural and urban crashes. The study found that there are approximately 42 percent more fatal crashes in rural areas compared to urban areas; however there are fewer vehicle miles traveled in rural areas than urban areas. In addition, fatal rural crashes are more likely to involve multiple fatalities, rollovers, and more trucks. Fatal rural crashes more often occur on curved roadways and have greater vehicle damage. Head-on crashes are more prevalent in rural areas than in urban areas. Finally, the length of time for emergency medical services to arrive at the scene is longer in rural areas than in urban areas.




Traffic Safety Facts


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World Report on Road Traffic Injury Prevention


Book Description

Every day thousands of people are killed and injured on our roads. Millions of people each year will spend long weeks in the hospital after severe crashes and many will never be able to live, work or play as they used to do. Current efforts to address road safety are minimal in comparison to this growing human suffering. This report presents a comprehensive overview of what is known about the magnitude, risk factors and impact of road traffic injuries, and about ways to prevent and lessen the impact of road crashes. Over 100 experts, from all continents and different sectors -- including transport, engineering, health, police, education and civil society -- have worked to produce the report. Charts and tables.




Traffic Safety Facts


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There Are No Accidents


Book Description

A journalist recounts the surprising history of accidents and reveals how they’ve come to define all that’s wrong with America. We hear it all the time: “Sorry, it was just an accident.” And we’ve been deeply conditioned to just accept that explanation and move on. But as Jessie Singer argues convincingly: There are no such things as accidents. The vast majority of mishaps are not random but predictable and preventable. Singer uncovers just how the term “accident” itself protects those in power and leaves the most vulnerable in harm’s way, preventing investigations, pushing off debts, blaming the victims, diluting anger, and even sparking empathy for the perpetrators. As the rate of accidental death skyrockets in America, the poor and people of color end up bearing the brunt of the violence and blame, while the powerful use the excuse of the “accident” to avoid consequences for their actions. Born of the death of her best friend, and the killer who insisted it was an accident, this book is a moving investigation of the sort of tragedies that are all too common, and all too commonly ignored. In this revelatory book, Singer tracks accidental death in America from turn of the century factories and coal mines to today’s urban highways, rural hospitals, and Superfund sites. Drawing connections between traffic accidents, accidental opioid overdoses, and accidental oil spills, Singer proves that what we call accidents are hardly random. Rather, who lives and dies by an accident in America is defined by money and power. She also presents a variety of actions we can take as individuals and as a society to stem the tide of “accidents”—saving lives and holding the guilty to account.







Global status report on road safety 2023


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Statistical and Econometric Methods for Transportation Data Analysis


Book Description

The book's website (with databases and other support materials) can be accessed here. Praise for the Second Edition: The second edition introduces an especially broad set of statistical methods ... As a lecturer in both transportation and marketing research, I find this book an excellent textbook for advanced undergraduate, Master’s and Ph.D. students, covering topics from simple descriptive statistics to complex Bayesian models. ... It is one of the few books that cover an extensive set of statistical methods needed for data analysis in transportation. The book offers a wealth of examples from the transportation field. —The American Statistician Statistical and Econometric Methods for Transportation Data Analysis, Third Edition offers an expansion over the first and second editions in response to the recent methodological advancements in the fields of econometrics and statistics and to provide an increasing range of examples and corresponding data sets. It describes and illustrates some of the statistical and econometric tools commonly used in transportation data analysis. It provides a wide breadth of examples and case studies, covering applications in various aspects of transportation planning, engineering, safety, and economics. Ample analytical rigor is provided in each chapter so that fundamental concepts and principles are clear and numerous references are provided for those seeking additional technical details and applications. New to the Third Edition Updated references and improved examples throughout. New sections on random parameters linear regression and ordered probability models including the hierarchical ordered probit model. A new section on random parameters models with heterogeneity in the means and variances of parameter estimates. Multiple new sections on correlated random parameters and correlated grouped random parameters in probit, logit and hazard-based models. A new section discussing the practical aspects of random parameters model estimation. A new chapter on Latent Class Models. A new chapter on Bivariate and Multivariate Dependent Variable Models. Statistical and Econometric Methods for Transportation Data Analysis, Third Edition can serve as a textbook for advanced undergraduate, Masters, and Ph.D. students in transportation-related disciplines including engineering, economics, urban and regional planning, and sociology. The book also serves as a technical reference for researchers and practitioners wishing to examine and understand a broad range of statistical and econometric tools required to study transportation problems.