Comparing prediction performance for crash injury severity among various machine learning and statistical methods
Crash injury severity prediction is a promising research target in traffic safety. Traditionally,
various statistical methods were used for modeling crash injury severities. In recent years …
various statistical methods were used for modeling crash injury severities. In recent years …
Comparison of four statistical and machine learning methods for crash severity prediction
A Iranitalab, A Khattak - Accident Analysis & Prevention, 2017 - Elsevier
Crash severity prediction models enable different agencies to predict the severity of a
reported crash with unknown severity or the severity of crashes that may be expected to …
reported crash with unknown severity or the severity of crashes that may be expected to …
Prediction and factor identification for crash severity: comparison of discrete choice and tree-based models
Crash severity is one of the most widely studied topics in traffic safety area. Scholars have
studied crash severity through various types of models. Using the publicly available 2017 …
studied crash severity through various types of models. Using the publicly available 2017 …
Single-vehicle crash severity outcome prediction and determinant extraction using tree-based and other non-parametric models
X Yan, J He, C Zhang, Z Liu, B Qiao, H Zhang - Accident Analysis & …, 2021 - Elsevier
Single-vehicle crashes are more fatality-concentrated and have posed increasing
challenges in traffic safety, which is of great research necessity. Tremendous previous …
challenges in traffic safety, which is of great research necessity. Tremendous previous …
A literature review of machine learning algorithms for crash injury severity prediction
Introduction: Road traffic crashes represent a major public health concern, so it is of
significant importance to understand the factors associated with the increase of injury …
significant importance to understand the factors associated with the increase of injury …
Using machine learning models to forecast severity level of traffic crashes by R Studio and ArcGIS
This study describes crash causes, conditions, and distribution of accident hot spots along
with an analysis of the risk factors that significantly affect severity levels of crashes and their …
with an analysis of the risk factors that significantly affect severity levels of crashes and their …
Crash injury severity analysis using a two-layer Stacking framework
Crash injury severity analysis is useful for traffic management agency to further understand
severity of crashes. A two-layer Stacking framework is proposed in this study to predict the …
severity of crashes. A two-layer Stacking framework is proposed in this study to predict the …
An analytic framework using deep learning for prediction of traffic accident injury severity based on contributing factors
Vulnerable road users (VRUs) are exposed to the highest risk in the road traffic environment.
Analyzing contributing factors that affect injury severity facilitates injury severity prediction …
Analyzing contributing factors that affect injury severity facilitates injury severity prediction …
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 …
Predicting road crash severity using classifier models and crash hotspots
The rapid increase in traffic volume on urban roads, over time, has altered the global traffic
scenario. Additionally, it has increased the number of road crashes, some of which are …
scenario. Additionally, it has increased the number of road crashes, some of which are …