Spatial analyses of crashes have been adopted in road safety for decades in order to
determine how crashes are affected by neighboring locations, how the influence of …

This study aims at contributing to the literature on pedestrian and bicyclist safety by building
on the conventional count regression models to explore exogenous factors affecting …

Introduction: The market share of e-scooters in the United States has proliferated in cities: 86
million trips were made on shared e-scooters in 2019, a more than 100% increase …

This study develops a Bayesian spatial generalized ordered logit model with conditional
autoregressive priors to examine severity of freeway crashes. Our model can simultaneously …

This study attempts to examine the main and interaction effects of roadway and weather
conditions on crash incidence, using the comprehensive crash, traffic and weather data from …

This study presents an empirical investigation of the impacts of real-time weather conditions
on the freeway crash severity. A Bayesian spatial generalized ordered logit model was …

Crash frequency model is often subject to excessive zero observation because of the rare
nature of crashes. To address the problem of imbalanced crash data, a deep generative …

There have been great efforts to develop traffic crash prediction models for various types of
facilities. The crash models have played a key role to identify crash hotspots and evaluate …

Despite the recognized benefits of cycling as a sustainable mode of transportation, cyclists
are considered vulnerable road users and there are concerns about their safety. Therefore, it …

In the twentieth year of the twenty-first century, humanity is facing an unprecedented global
crisis owing to the COVID-19 pandemic. It has brought about drastic changes in the way we …