Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity
Driven by advancements in data-driven methods, recent developments in proactive crash
prediction models have primarily focused on implementing machine learning and artificial …
prediction models have primarily focused on implementing machine learning and artificial …
Fifty years of accident analysis & prevention: A bibliometric and scientometric overview
Abstract Accident Analysis & Prevention (AA&P) is a leading academic journal established
in 1969 that serves as an important scientific communication platform for road safety studies …
in 1969 that serves as an important scientific communication platform for road safety studies …
Analysis of driver injury severity in single-vehicle crashes on rural and urban roadways
This study analyzes driver injury severities for single-vehicle crashes occurring in rural and
urban areas using data collected in New Mexico from 2010 to 2011. Nested logit models …
urban areas using data collected in New Mexico from 2010 to 2011. Nested logit models …
Crash severity analysis of rear-end crashes in California using statistical and machine learning classification methods
Investigating drivers' injury level and detecting contributing factors that aggravate the
damage level imposed on drivers and vehicles is a critical subject in the field of crash …
damage level imposed on drivers and vehicles is a critical subject in the field of crash …
Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model
Rural non-interstate crashes induce a significant amount of severe injuries and fatalities.
Examination of such injury patterns and the associated contributing factors is of practical …
Examination of such injury patterns and the associated contributing factors is of practical …
Investigating factors influencing rollover crash risk on mountainous interstates
Introduction: The risk of rollover crashes on mountainous roads is a major concern for
transportation authorities due to adverse weather conditions and complex topography. Such …
transportation authorities due to adverse weather conditions and complex topography. Such …
Risk analysis of traffic accidents' severities: An application of three data mining models
Traffic accidents are costing the world more than a million lives yearly alongside monetary
losses, especially in the Gulf Cooperation Council region. This situation raised the need to …
losses, especially in the Gulf Cooperation Council region. This situation raised the need to …
Exploring the forecasting approach for road accidents: Analytical measures with hybrid machine learning
Urban traffic forecasting models generally follow either a Gaussian Mixture Model (GMM) or
a Support Vector Classifier (SVC) to estimate the features of potential road accidents …
a Support Vector Classifier (SVC) to estimate the features of potential road accidents …
Rule discovery to identify patterns contributing to overrepresentation and severity of run-off-the-road crashes
A Montella, F Mauriello, M Pernetti… - Accident Analysis & …, 2021 - Elsevier
The main objective of this paper was to analyse the roadway, environmental, and driver-
related factors associated with an overrepresentation of frequency and severity of run-off-the …
related factors associated with an overrepresentation of frequency and severity of run-off-the …
Application of Extremely Randomised Trees for exploring influential factors on variant crash severity data
F Afshar, S Seyedabrishami, S Moridpour - Scientific reports, 2022 - nature.com
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 …
of traffic crashes. In this study, Extremely Randomised Tree (ERT) is used as a machine …