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 …
Transparent deep machine learning framework for predicting traffic crash severity
Abstract Analysis of crash injury severity is a promising research target in highway safety
studies. A better understanding of crash severity risk factors is vital for the proactive …
studies. A better understanding of crash severity risk factors is vital for the proactive …
A deep learning based traffic crash severity prediction framework
Highway work zones are most vulnerable roadway segments for congestion and traffic
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
collisions. Hence, providing accurate and timely prediction of the severity of traffic collisions …
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 …
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 …
An alternative method for traffic accident severity prediction: using deep forests algorithm
J Gan, L Li, D Zhang, Z Yi… - Journal of advanced …, 2020 - Wiley Online Library
Traffic safety has always been an important issue in sustainable transportation development,
and the prediction of traffic accident severity remains a crucial challenging issue in the …
and the prediction of traffic accident severity remains a crucial challenging issue in the …
An improved deep learning model for traffic crash prediction
Machine‐learning technology powers many aspects of modern society. Compared to the
conventional machine learning techniques that were limited in processing natural data in the …
conventional machine learning techniques that were limited in processing natural data in the …
Learning spatial patterns and temporal dependencies for traffic accident severity prediction: A deep learning approach
Traffic accidents have a substantial impact on human life and property, resulting in millions
of injuries every year. To ensure road safety and enhance the research in this direction, it is …
of injuries every year. To ensure road safety and enhance the research in this direction, it is …
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 …
RFCNN: Traffic accident severity prediction based on decision level fusion of machine and deep learning model
Traffic accidents on highways are a leading cause of death despite the development of traffic
safety measures. The burden of casualties and damage caused by road accidents is very …
safety measures. The burden of casualties and damage caused by road accidents is very …