Road accidents are one of the most relevant causes of injuries and death worldwide, and
therefore, they constitute a significant field of research on the use of advanced algorithms …

With the trend of global warming and destructive human activities, the frequent occurrences
of catastrophes have posed devastating threats to human life and social stability worldwide …

Real-time crash risk prediction is expected to play a crucial role in preventing traffic
accidents. However, most existing studies only focus on freeways rather than urban arterials …

Predicting traffic accidents is a crucial problem to improving transportation and public safety
as well as safe routing. The problem is also challenging due to the rareness of accidents in …

In this paper, we present a data augmentation technique to reproduce crash data. The
dataset comprising crash and non-crash events are extremely imbalanced. For instance, the …

Traffic accidents usually lead to severe human casualties and huge economic losses in real-
world scenarios. Timely accurate prediction of traffic accidents has great potential to protect …

Real-time crash prediction is essential for proactive traffic safety management. However,
developing an accurate prediction model is challenging as the traffic data of crash and non …

The prediction of traffic crashes is an essential topic in traffic safety research. Most of the
previous studies conducted experiments on real-time crash prediction of expressways or …

Real-time traffic accident forecasting is increasingly important for public safety and urban
management (eg, real-time safe route planning and emergency response deployment) …

We develop accident prediction models for a stretch of the urban expressway Autopista
Central in Santiago, Chile, using disaggregate data captured by free-flow toll gates with …