Machine learning techniques for pavement condition evaluation
Pavement management systems play a significant role in country's economy since road
authorities are concerned about preserving their priceless road assets for a longer time to …
authorities are concerned about preserving their priceless road assets for a longer time to …
[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 …
The application of XGBoost and SHAP to examining the factors in freight truck-related crashes: An exploratory analysis
Due to the burgeoning demand for freight movement, freight related road safety threats have
been growing substantially. In spite of some research on the factors influencing freight truck …
been growing substantially. In spite of some research on the factors influencing freight truck …
Railway dangerous goods transportation system risk identification: Comparisons among SVM, PSO-SVM, GA-SVM and GS-SVM
W Huang, H Liu, Y Zhang, R Mi, C Tong, W Xiao… - Applied Soft …, 2021 - Elsevier
In this paper, three algorithms are applied to obtain the parameters of Radial Basis Function
(RBF) kernels of Support Vector Machines (SVM), which include: PSO (Particle Swarm …
(RBF) kernels of Support Vector Machines (SVM), which include: PSO (Particle Swarm …
Visualization and analysis of mapping knowledge domain of road safety studies
Mapping knowledge domain (MKD) is an important application of visualization technology in
Bibliometrics, which has been extensively applied in psychology, medicine, and information …
Bibliometrics, which has been extensively applied in psychology, medicine, and information …
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 …
Severity analysis for large truck rollover crashes using a random parameter ordered logit model
Large truck rollover crashes present significant financial, industrial, and social impacts. This
paper presents an effort to investigate the contributing factors to large truck rollover crashes …
paper presents an effort to investigate the contributing factors to large truck rollover crashes …
[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 …
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 …
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 …