A growing interest in non-Gaussian time series, particularly in series comprised of
nonnegative integers (counts), is taking place in today's statistics literature. Count series …

Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has
been an area of research focus for many decades. However, in the absence of detailed …

The analysis of highway-crash data has long been used as a basis for influencing highway
and vehicle designs, as well as directing and implementing a wide variety of regulatory …

Reducing the severity of injuries resulting from motor-vehicle crashes has long been a
primary emphasis of highway agencies and motor-vehicle manufacturers. While progress …

Crash injury severity analysis is useful for traffic management agency to further understand
severity of crashes. A two-layer Stacking framework is proposed in this study to predict the …

The objective of this work is to determine and study, analyze and elaborate, classify and
categorize the main risk analysis and risk-assessment methods and techniques by …

Traditional crash-severity modeling uses detailed data gathered after a crash has occurred
(number of vehicles involved, age of occupants, weather conditions at the time of the crash …

This paper uses data collected over a five-year period between 2005 and 2009 in Indiana to
estimate random parameters multivariate tobit and zero-inflated count data models of …

Macroscopic traffic crash analyses have been conducted to incorporate traffic safety into
long-term transportation planning. This study aims at developing a multivariate Poisson …

BACKGROUND: Traditional crash prediction models, such as generalized linear regression
model, are incapable of taking into account multilevel data structure. Therefore they suffer …