Purpose Over the past 10 years, building on road infrastructure data, crash prediction
models (CPMs) have become fundamental scientific tools for road safety management …

Introduction Road safety is still a major issue all around the world. The capability to analyze
the road network and identify high risk sections is crucial in road safety management …

The conditional generative adversarial network (CGAN) is used in this paper for empirical
Bayes (EB) analysis of road crash hotspots. EB is a well-known method for estimating the …

The study objective is to compare three approaches to identification of hazardous road
locations:(1) Traditional reactive accident-based approach, resulting in identification of …

Road safety is considered one of the fundamental factors for sustainable mobility, which
requires establishing effective highway safety management programs and processes …

Purpose Czech motorways and national roads form the primary road network, which is
critical in terms of safety. To be able to rationally manage network safety in both planning …

This study aims to evaluate the impact of pavement physical characteristics on the frequency
of single-vehicle run-off-road (ROR) crashes in two-lane separated rural highways. In order …

Network safety ranking (or hotspot identification) is conducted in order to identify hazardous
road locations and develop a priority list for application of effective safety treatments. In this …

Network screening is the process of identifying the sites within the road network that are of
highest priority for detailed safety audits and interventions. Contemporary road safety …

In this paper, we present a crash frequency data augmentation method based on
Conditional Generative Adversarial Networks to improve crash frequency models. The …