Influential factors on injury severity for drivers of light trucks and vans with machine learning methods
G Pillajo-Quijia, B Arenas-Ramírez… - Sustainability, 2020 - mdpi.com
The study of road accidents and the adoption of measures to reduce them is one of the most
important targets of the Sustainable Development Goals for 2030. To further progress in the …
important targets of the Sustainable Development Goals for 2030. To further progress in the …
Modeling road accident severity with comparisons of logistic regression, decision tree and random forest
MM Chen, MC Chen - Information, 2020 - mdpi.com
To reduce the damage caused by road accidents, researchers have applied different
techniques to explore correlated factors and develop efficient prediction models. The main …
techniques to explore correlated factors and develop efficient prediction models. The main …
[HTML][HTML] Machine learning applied to road safety modeling: A systematic literature review
Road safety modeling is a valuable strategy for promoting safe mobility, enabling the
development of crash prediction models (CPM) and the investigation of factors contributing …
development of crash prediction models (CPM) and the investigation of factors contributing …
Single-vehicle crash severity outcome prediction and determinant extraction using tree-based and other non-parametric models
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 …
Road safety performance index: A tool for crash prediction
L Shbeeb - Cogent Engineering, 2022 - Taylor & Francis
The relationship between road infrastructure parameters and road crashes is not widely
investigated in developing countries. The study objective is to create a measure for rating …
investigated in developing countries. The study objective is to create a measure for rating …
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 machine learning techniques for predictions of motorway segment crash risk level
Motorways are typically the safest road environment in terms of injury crashes per million
vehicle kilometres; however, given the high severity of crashes occurring therein, there is still …
vehicle kilometres; however, given the high severity of crashes occurring therein, there is still …
Comparison of traffic accident injury severity prediction models with explainable machine learning
Traffic accidents are still the main cause of fatalities, injuries and significant delays in
highways. Understanding the accident contributing factor is imperative to increase safety in …
highways. Understanding the accident contributing factor is imperative to increase safety in …
Applications of deep learning in severity prediction of traffic accidents
This study investigates the power of deep learning in predicting the severity of injuries when
accidents occur due to traffic on Malaysian highways. Three network architectures based on …
accidents occur due to traffic on Malaysian highways. Three network architectures based on …
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 …