Severity analysis of wildlife–vehicle crashes using generalized structural equation modeling

I Gharraie, E Sacchi - Transportation research record, 2021 - journals.sagepub.com
Each year, thousands of wildlife–vehicle crashes (WVCs) occur in North America with
negative effects on wildlife welfare, human health, and the economy. Although previous …

Application of Bayesian ordinal logistic model for identification of factors to traffic barrier crashes: considering roadway classification

M Rezapour, SS Wulff, A Mehrara Molan… - Transportation …, 2021 - Taylor & Francis
One of the main objectives of policymakers is to reduce crash severity due to high social
impacts and economic loss associated with severe crashes. One of the most efficient ways to …

Examining driver injury severity in single-vehicle road departure crashes involving large trucks

M Hosseinpour, K Haleem - Transportation research record, 2021 - journals.sagepub.com
Road departure (RD) crashes are among the most severe crashes that can result in fatal or
serious injuries, especially when involving large trucks. Most previous studies neglected to …

The pattern of orthopedic fractures and visceral injury in road traffic crash victims, Addis Ababa, Ethiopia

Z Mengistu, A Ali, T Abegaz - PloS one, 2021 - journals.plos.org
Background Road Traffic crash injury is one of the main public health problems resulting in
premature death and disability particularly in low-income countries. However, there is limited …

Machine Learning Insights for Behavioral Data Analysis Supporting the Autonomous Vehicles Scenario

E Prezioso, F Giampaolo, C Mazzocca… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The advent of the digital innovation era is changing service, use, and resources
management paradigms, offering a wide range of new and essential opportunities. In …

Tackling ordinal regression problem for heterogeneous data: sparse and deep multi-task learning approaches

L Wang, D Zhu - Data mining and knowledge discovery, 2021 - Springer
Many real-world datasets are labeled with natural orders, ie, ordinal labels. Ordinal
regression is a method to predict ordinal labels that finds a wide range of applications in …

Principles for development of safer rural highway systems for conditions prevailing in low and middle-income countries

G Tiwari - Transport and Safety: Systems, Approaches, and …, 2021 - Springer
Road traffic safety has been recognised as a global health problem by all stakeholders in
the new millennium. A disproportionately high burden of road traffic deaths and injuries …

A machine learning approach for building an adaptive, real-time decision support system for emergency response to road traffic injuries

S Taamneh, MM Taamneh - … journal of injury control and safety …, 2021 - Taylor & Francis
In this paper, historical data about road traffic accidents are utilized to build a decision
support system for emergency response to road traffic injuries in real-time. A cost-sensitive …

Severity analysis of heavy vehicle crashes using machine learning models: A case study in New Jersey

AS Hasan, MAB Kabir, M Jalayer - International Conference on …, 2021 - ascelibrary.org
Large trucks are a vital mode for freight transportation. Increasing demand in freight
transportation increases the risk of truck-involved crashes on highways. Truck-involved …

A generalized ordered logit analysis of risk factors associated with driver injury severity

EN Aidoo, W Ackaah - Journal of Public Health, 2021 - Springer
Aim Road traffic crashes remain a major public health issue and have been the subject of
debate in many studies due to their effect on society. This study contributes to the discussion …