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 …

Road safety modeling is a valuable strategy for promoting safe mobility, enabling the
development of crash prediction models (CPM) and the investigation of factors contributing …

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 …

Statistical analysis of traffic crash frequency is significant for figuring out the distribution
pattern of crashes, predicting the development trend of crashes, formulating traffic crash …

In this paper, a deep learning model using a Recurrent Neural Network (RNN) was
developed and employed to predict the injury severity of traffic accidents based on 1130 …

A traffic accident, a traffic collision or crash occurs when a vehicle collides with another
vehicle, pedestrian, animal, road barrier, or any stationary obstruction such as a tree or a …

This work examines the relationship between 3-year pedestrian crash counts across Census
tracts in Austin, Texas, and various land use, network, and demographic attributes, such as …

Head-on crashes are among the most severe collision types and of great concern to road
safety authorities. Therefore, it justifies more efforts to reduce both the frequency and …