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A hybrid approach of traffic simulation and machine learning techniques for enhancing real-time traffic prediction
Accurate traffic prediction is important for efficient traffic operation, management, and user
convenience. It enables traffic management authorities to allocate traffic resources …
convenience. It enables traffic management authorities to allocate traffic resources …
[HTML][HTML] Koopman theory meets graph convolutional network: Learning the complex dynamics of non-stationary highway traffic flow for spatiotemporal prediction
Reliable and accurate traffic flow prediction is crucial for the construction and operation of
smart highways, supporting scientific traffic management and planning. However, accurately …
smart highways, supporting scientific traffic management and planning. However, accurately …
A predictive discrete event simulation for predicting operation times in container terminal
Container terminals (CTs) play a crucial role within the global supply chain in the context of
the global container transportation business. The primary obligation associated with these …
the global container transportation business. The primary obligation associated with these …
Using Machine Learning and Deep learning for traffic congestion prediction: a review
With the acceleration of urbanisation, decreased vehicle prices and increased population in
many cities, traffic demand has been rapidly increasing in recent years. Urban road traffic …
many cities, traffic demand has been rapidly increasing in recent years. Urban road traffic …
Research on the impact of underground excavation metro on surface traffic safety and assessment method
X Chen, QS Zhang, RT Liu, DK Zhao, HZ Li… - Journal of the …, 2023 - Taylor & Francis
This study focuses on a problem that has been seriously troubled urban traffic managers: the
impact of underground excavation metros on surface traffic safety during construction. In …
impact of underground excavation metros on surface traffic safety during construction. In …
[BUKU][B] Big data analytics for smart transport and healthcare systems
SP Ardakani, A Cheshmehzangi - 2023 - Springer
In the information age, big data has become an important tool for us to understand and
improve the world, especially in urban planning and design (Pourroostaei Ardakani and …
improve the world, especially in urban planning and design (Pourroostaei Ardakani and …
Big data analytics and the future of smart transport and healthcare systems
Urban experimentationhas long become a platform of city transitions, where we see
opportunities for smart development. This applies to many sectors, including smart …
opportunities for smart development. This applies to many sectors, including smart …
Comprehensive analysis of UK AADF traffic dataset set within four geographical regions of England
Traffic flow detection plays a significant part in freeway traffic surveillance systems.
Currently, effective autonomous traffic analysis is a challenging task due to the complexity of …
Currently, effective autonomous traffic analysis is a challenging task due to the complexity of …
Predicting the duration of traffic incidents for Sydney greater metropolitan area using machine learning methods
This research presents a comprehensive machine learning approach to predicting the
duration of traffic incidents, classifying them as short-term or long-term, and understanding …
duration of traffic incidents, classifying them as short-term or long-term, and understanding …
[PDF][PDF] Logical structure of actions to reduce the impacts of traffic incidents
MLDB Baltar, VHS De Abreu… - Revista GEINTEC-Gestao …, 2021 - revistageintec.net
Traffic incidents (such as broken-down vehicles, accidents, flat tires and other) constitute an
important concern in the urban context, impacting the sustainable development. Thus …
important concern in the urban context, impacting the sustainable development. Thus …