Applications of machine learning methods in traffic crash severity modelling: current status and future directions
As a key area of traffic safety research, crash severity modelling has attracted tremendous
attention. Recently, there has been growing interest in applying machine learning (ML) …
attention. Recently, there has been growing interest in applying machine learning (ML) …
[HTML][HTML] Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review
Accurately modelling crashes, and predicting crash occurrence and associated severities
are a prerequisite for devising countermeasures and developing effective road safety …
are a prerequisite for devising countermeasures and developing effective road safety …
Temporal stability of factors affecting injury severity in rear-end and non-rear-end crashes: A random parameter approach with heterogeneity in means and variances
Rear-end crashes have become a serious global issue, with increasing injuries and fatalities
accounting for massive property loss. The purpose of this study is to investigate the variation …
accounting for massive property loss. The purpose of this study is to investigate the variation …
Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study
A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …
prediction and effective implementation of appropriate mitigation strategies. Traditional …
Investigation on the injury severity of drivers in rear-end collisions between cars using a random parameters bivariate ordered probit model
The existing studies on drivers' injury severity include numerous statistical models that
assess potential factors affecting the level of injury. These models should address specific …
assess potential factors affecting the level of injury. These models should address specific …
Road safety research in the context of low-and middle-income countries: Macro-scale literature analyses, trends, knowledge gaps and challenges
Road users in low-and middle-income countries (LMICs) are overrepresented in road
trauma statistics. Despite the relative success of many high-income countries (HICs) in …
trauma statistics. Despite the relative success of many high-income countries (HICs) in …
Constructing a Bayesian network model for improving safety behavior of employees at workplaces
Introduction Unsafe behavior increases the risk of accident at workplaces and needs to be
managed properly. The aim of the present study was to provide a model for managing and …
managed properly. The aim of the present study was to provide a model for managing and …
Prioritizing influential factors for freeway incident clearance time prediction using the gradient boosting decision trees method
Identifying and quantifying the influential factors on incident clearance time can benefit
incident management for accident causal analysis and prediction, and consequently …
incident management for accident causal analysis and prediction, and consequently …
Investigating driver injury severity patterns in rollover crashes using support vector machine models
Rollover crash is one of the major types of traffic crashes that induce fatal injuries. It is
important to investigate the factors that affect rollover crashes and their influence on driver …
important to investigate the factors that affect rollover crashes and their influence on driver …
Analysis of injury severity of rear-end crashes in work zones: A random parameters approach with heterogeneity in means and variances
M Yu, C Zheng, C Ma - Analytic methods in accident research, 2020 - Elsevier
Rear-end crash is the predominant crash type in work zones. This study employs a random
parameters logit approach with heterogeneity in means and variances to investigate factors …
parameters logit approach with heterogeneity in means and variances to investigate factors …