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 …

With the growing popularity of the Internet-of-Vehicles (IoV), it is of pressing necessity to
understand transportation traffic patterns and their impact on wireless network designs and …

Traffic prediction plays an essential role in intelligent transportation system. Accurate traffic
prediction can assist route planing, guide vehicle dispatching, and mitigate traffic …

Federated learning has been applied to various tasks in intelligent transportation systems to
protect data privacy through decentralized training schemes. The majority of the state-of-the …

As one of the most important applications of industrial Internet of Things, intelligent
transportation system aims to improve the efficiency and safety of transportation networks. In …

Traffic prediction on road networks is highly challenging due to the complexity of traffic
systems and is a crucial task in successful intelligent traffic system applications. Existing …

Abstract Recently, Temporal Convolution Networks (TCNs) and Graph Convolution Network
(GCN) have been developed for traffic forecasting and obtained promising results as their …

Traffic flow prediction remains an ongoing hot topic in the field of Intelligent Transportation
System. The state-of-the-art traffic flow prediction models can effectively extract both spatial …

Region-level traffic information can characterize dynamic changes of urban traffic at the
macro level. Real-time region-level traffic prediction help city traffic managers with traffic …

Forecasting of multivariate time-series is an important problem that has applications in traffic
management, cellular network configuration, and quantitative finance. A special case of the …