Highway accidents are complex events that involve a variety of human responses to external
stimuli, as well as complex interactions between the vehicle, roadway features/condition …

Accurate crash frequency prediction is critical for proactive safety management. The
emerging connected vehicles technology provides us with a wealth of vehicular motion data …

Automated vehicles (AVs) represent an opportunity to reduce crash frequency by eliminating
driver error, as safety studies reveal human error contributes to the majority of crashes. To …

This study attempts to explore the viability of dual-state models (ie, zero-inflated and hurdle
models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency …

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 …

Introduction Truck crashes contribute to a large number of injuries and fatalities. This study
seeks to identify the contributing factors affecting truck crash severity using 2010 to 2016 …

Machine‐learning technology powers many aspects of modern society. Compared to the
conventional machine learning techniques that were limited in processing natural data in the …

Intersections are among the most dangerous roadway facilities due to the complex traffic
conflicting movements and frequent stop-and-go traffic. However, previous intersection …

Automated vehicles are emerging on the transportation networks as manufacturers test their
automated driving system (ADS) capabilities in complex real-world environments in testing …

Abstract Accident Analysis & Prevention (AA&P) is a leading academic journal established
in 1969 that serves as an important scientific communication platform for road safety studies …