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 …

In the broad scientific field of time series forecasting, the ARIMA models and their variants
have been widely applied for half a century now due to their mathematical simplicity and …

Traffic flow prediction methods commonly rely on historical traffic data, such as traffic volume
and speed, but may not be suitable for high-capacity expressways or during peak traffic …

The artificial intelligence (AI) revolution offers significant opportunities to capitalise on the
growth of digitalisation and has the potential to enable the 'system of systems' approach …

Short-term traffic flow prediction is a core branch of intelligent traffic systems (ITS) and plays
an important role in traffic management. The graph convolution network (GCN) is widely …

Artificial intelligence (AI) technologies are increasingly applied to traffic flow prediction (TFP)
to enhance prediction accuracy. This study utilizes bibliometric methods and network …

Introduction: COVID-19 has disrupted daily life and societal flow globally since December
2019; it introduced measures such as lockdown and suspension of all non-essential …

Accurate traffic congestion estimation and prediction are critical building blocks for smart trip
planning and rerouting decisions in transportation systems. Over the decades, there have …

Buildings account for a significant portion of the global energy consumption. Forecasting
personnel occupancy is critical for reducing energy consumption in buildings. This study …

In this paper, a new practice-ready method for the real-time estimation of traffic conditions
and travel times on highways is introduced. First, after a principal component analysis …