In the last few years, there has been an exponential increase in the usage of the
autonomous vehicles across the globe. It is due to an exponential increase in the popularity …

Traffic state prediction is a key component in intelligent transport systems (ITS) and has
attracted much attention over the last few decades. Advances in computational power and …

The development of Internet of Vehicles (IoV) has produced a considerable amount of real-
time traffic data. These traffic data constitute a kind of digital twin that connects the physical …

This study proposes a novel Graph Convolutional Neural Network with Data-driven Graph
Filter (GCNN-DDGF) model that can learn hidden heterogeneous pairwise correlations …

The accurate prediction of real-time traffic flow is indispensable to intelligent transport
systems. However, the short-term prediction remains a thorny issue, due to the complexity …

The ability to timely and accurately forecast the evolution of traffic is very important in traffic
management and control applications. This paper proposes a non-parametric and data …

Daily traffic flow forecasting is critical in advanced traffic management and can improve the
efficiency of fixed-time signal control. This paper presents a traffic prediction method for one …

Accurate short-term flow forecasting is important for the real-time traffic control, but due to its
complex nonlinear data pattern, getting a high precision is difficult. The support vector …

The traffic flow prediction plays a key role in modern Intelligent Transportation Systems (ITS).
Although great achievements have been made in traffic flow prediction, it is still a challenge …

The realization of road traffic prediction not only provides real-time and effective information
for travelers, but also helps them select the optimal route to reduce travel time. Road traffic …