[HTML][HTML] Spoken instruction understanding in air traffic control: Challenge, technique, and application

Y Lin - Aerospace, 2021 - mdpi.com
In air traffic control (ATC), speech communication with radio transmission is the primary way
to exchange information between the controller and aircrew. A wealth of contextual …

[HTML][HTML] A systematic review of traffic incident detection algorithms

O ElSahly, A Abdelfatah - Sustainability, 2022 - mdpi.com
Traffic incidents have negative impacts on traffic flow and the gross domestic product of most
countries. In addition, they may result in fatalities and injuries. Thus, efficient incident …

TFGAN: Traffic forecasting using generative adversarial network with multi-graph convolutional network

A Khaled, AMT Elsir, Y Shen - Knowledge-Based Systems, 2022 - Elsevier
Traffic forecasting constitutes a task of great importance in intelligent transport systems.
Owing to the non-Euclidean structure of traffic data, the complicated spatial correlations, and …

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 …

[HTML][HTML] Alternative prioritization of freeway incident management using autonomous vehicles in mixed traffic using a type-2 neutrosophic number based decision …

I Gokasar, V Simic, M Deveci, T Senapati - Engineering Applications of …, 2023 - Elsevier
Traffic incident management is combining the assets of authorities to identify, deal with, and
manage traffic problems as rapidly as possible while providing the safety of on-scene …

Traffic congestion detection from surveillance videos using deep learning

GB Madhavi, AD Bhavani, YS Reddy… - … Engineering & their …, 2023 - ieeexplore.ieee.org
Countless cameras, both public and private, have been installed in recent years for the
objectives of surveillance, the monitoring of anomalous human activities, and traffic …

[PDF][PDF] Anomaly detection in time series using deep learning

MH Sharif, K Gupta, MA Mohammed… - International Journal of …, 2022 - researchgate.net
Time series anomaly detection has ever existed as a fundamental analysis approach. The
early time series anomaly detection techniques are mainly statistical and machine learning …

Improving traffic accident severity prediction using MobileNet transfer learning model and SHAP XAI technique

OI Aboulola - PLoS one, 2024 - journals.plos.org
Traffic accidents remain a leading cause of fatalities, injuries, and significant disruptions on
highways. Comprehending the contributing factors to these occurrences is paramount in …

A novel deep learning approach for anomaly detection of time series data

Z Ji, J Gong, J Feng - Scientific Programming, 2021 - Wiley Online Library
Anomalies in time series, also called “discord,” are the abnormal subsequences. The
occurrence of anomalies in time series may indicate that some faults or disease will occur …

Blockchain-enabled internet of vehicles applications

J Gao, C Peng, T Yoshinaga, G Han, S Guleng, C Wu - Electronics, 2023 - mdpi.com
Internet of Vehicles (IoV) is a network that connects vehicles and everything. IoV shares
traffic data by connecting vehicles with the surrounding environment, which brings huge …