The COVID-19 pandemic continues to have a significant impact on the transport sector
worldwide. Lockdown and physical distancing requirements continue to be enforced in …

Long short-term memory (LSTM) models provide high predictive performance through their
ability to recognize longer sequences of time series data. More recently, bidirectional deep …

Accurate short-term forecasting of public transport demand is essential for the operation of
on-demand public transport. Knowing where and when future demands for travel are …

The IEEE Transactions on Intelligent Transport Systems was founded in 2000 to enhance
the sharing of international research on theoretical and practical technology developments …

To realize the great potential of the intelligent transportation infrastructure, the investment in
the transportation infrastructure in the intelligent transportation system should be rationally …

Accurate traffic volume prediction plays a crucial role in urban traffic control by relieving
congestion through improved regulation of traffic volume. Network‐level traffic volume …

The early prediction of onset labour is critical for avoiding the risk of death due to pregnancy
delay. Low-income countries often struggle to deliver timely service to pregnant women due …

Lithium battery‐based electric vehicles (EVs) are gaining global popularity as an alternative
to combat the adverse environmental impacts caused by the utilization of fossil fuels. State of …

We present Sim-on-Wheels, a safe, realistic, and vehicle-in-loop framework to test
autonomous vehicles' performance in the real world under safety-critical scenarios. Sim-on …

Traffic operation efficiency is greatly impacted by the increase in travel demand and the
increase in vehicle ownership. The continued increase in traffic demand has rendered the …