Traffic prediction using artificial intelligence: Review of recent advances and emerging opportunities
Traffic prediction plays a crucial role in alleviating traffic congestion which represents a
critical problem globally, resulting in negative consequences such as lost hours of additional …
critical problem globally, resulting in negative consequences such as lost hours of additional …
A broad review on class imbalance learning techniques
S Rezvani, X Wang - Applied Soft Computing, 2023 - Elsevier
The imbalanced learning issue is related to the performance of learning algorithms in the
presence of asymmetrical class distribution. Due to the complex characteristics of …
presence of asymmetrical class distribution. Due to the complex characteristics of …
Crash data augmentation using variational autoencoder
In this paper, we present a data augmentation technique to reproduce crash data. The
dataset comprising crash and non-crash events are extremely imbalanced. For instance, the …
dataset comprising crash and non-crash events are extremely imbalanced. For instance, the …
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 …
Real-time crash prediction on expressways using deep generative models
Real-time crash prediction is essential for proactive traffic safety management. However,
develo** an accurate prediction model is challenging as the traffic data of crash and non …
develo** an accurate prediction model is challenging as the traffic data of crash and non …
Traffic conflict prediction using connected vehicle data
Transportation safety studies have been mostly focused on using crash data that are rare
events. Alternatively, conflict estimation can be used to assess safety. This has been proven …
events. Alternatively, conflict estimation can be used to assess safety. This has been proven …
A study of freeway crash risk prediction and interpretation based on risky driving behavior and traffic flow data
M Guo, X Zhao, Y Yao, P Yan, Y Su, C Bi… - Accident Analysis & …, 2021 - Elsevier
The prediction of traffic crashes is an essential topic in traffic safety research. Most of the
previous studies conducted experiments on real-time crash prediction of expressways or …
previous studies conducted experiments on real-time crash prediction of expressways or …
Bayesian dynamic extreme value modeling for conflict-based real-time safety analysis
C Fu, T Sayed - Analytic methods in accident research, 2022 - Elsevier
Real-time safety analysis and optimization using surrogate safety measures such as traffic
conflicts and techniques such extreme value theory (EVT) models is an emerging research …
conflicts and techniques such extreme value theory (EVT) models is an emerging research …
A multivariate method for evaluating safety from conflict extremes in real time
C Fu, T Sayed - Analytic methods in accident research, 2022 - Elsevier
Several studies have advocated the use of extreme value theory (EVT) traffic conflict models
for real-time crash risk prediction using real-time safety indices such as the risk of crash (RC) …
for real-time crash risk prediction using real-time safety indices such as the risk of crash (RC) …
A real-time crash prediction fusion framework: An imbalance-aware strategy for collision avoidance systems
Real-time traffic crash prediction has been a major concern in the development of Collision
Avoidance Systems (CASs) along with other intelligent and resilient transportation …
Avoidance Systems (CASs) along with other intelligent and resilient transportation …