Data-driven intelligent technologies are promoting a disruptive digital transformation of
human society. Industrial accident prevention is also amid this change. Although many …

Extreme value theory is the state-of-the-art modelling technique for estimating crash risk
from traffic conflicts, with two different sampling techniques, ie block maxima and peak-over …

Understanding locally heterogeneous physical contexts in built environment is of great
importance in developing preemptive countermeasures to mitigate pedestrian fatality risks …

Road crash fatality is a universal problem of the transportation system. A massive death toll
caused annually due to road crash incidents, and among them, vulnerable road users (VRU) …

This study aims to explore the effects of drivers' visual environment on speeding crashes by
using different machine learning techniques. To obtain the data of drivers' visual …

Millions of car crashes occur annually in the US, leaving tens of thousands of deaths and
many more severe injuries. Thus, understanding the most impactful contributors to severe …

The classification method in the spatial analysis modeling based on the multi-criteria
parameter is currently widely used to manage geographic information systems (GIS) …

Because of the lag in sinter composition detection, fluctuations in production conditions are
not conducive to making timely adjustments to sintering. In this paper, the characteristics of …

Despite the greatest efforts of the car industry's engineers and researchers, traffic accidents
will continue to occur. In order to better understand the causes of risky traffic occurrences, it …

Crash severity models play a crucial role in evaluating the influencing factors in the severity
of traffic crashes. In this study, Extremely Randomised Tree (ERT) is used as a machine …