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 …

Background Currently, two models of artificial neural network (ANN) and logistic regression
(LR) are known as models that extensively used in medical sciences. The aim of this study …

Traffic accidents involving children and adolescents present complex challenges from both
the medico-legal and orthopedic standpoints. Despite the implementation of road traffic …

Introduction Even though cycling is an activity whose benefits in terms of urban mobility and
health are globally recognized, its disproportional growth during the past few decades has …

Introduction Although daily walking implies several potential benefits for the health and well-
being of people, and, besides the raise of more “walkable” cities, it is currently being …

The controlled study of pedestrians' crossing decision-making is relevant to the search for
better safety conditions for this class of vulnerable road users. Several risk factors have been …

The advent of virtual driving instructors has the potential to revolutionize driver education by
providing real-time, unbiased feedback to learner drivers. This paradigm shift aims to …

When assessing trainees' progresses during a driving training program, instructors can only
rely on the evaluation of a trainee's explicit behavior and their performance, without having …

Identifying critical safety management drivers with high driver-level risks is essential for
traffic safety improvement. Previous studies commonly evaluated driver-level risks based …

Although traffic crashes are the eighth leading cause of death in the world, and are linked to
vehicle and infrastructure-related factors, crash-related fatality rates are much higher in low …