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 …

Large-scale microsimulations are increasingly resourceful tools for analysing in detail
citywide effects and alternative scenarios of our policy decisions, approximating the ideal of …

Connected and autonomous vehicle (CAV) technologies are expected to change
driving/vehicle behavior on freeways. This study investigates the impact of CAVs on freeway …

Over the past few decades, the increasing number of vehicles and imperfect road traffic
management have been sources of congestion in cities and reasons for deteriorating health …

Abstract Evaluation of the demand for emerging transportation technologies and policies
can vary by time of day due to spillbacks on roadways, rescheduling of travelers' activity …

Proper calibration process is of considerable importance for traffic safety evaluations using
simulation models. Allowing for a pure with and without comparison under identical …

The theoretical analysis of traffic flow with empirical vehicle trajectory data contained within
this study allows for the explanation, reconstruction, and prediction of spatiotemporal …

The parameters of a transportation simulation model need to pass through a careful
calibration process to ensure that the model's output is as close as possible to the actual …

Examining driving behaviour is crucial for traffic operations because of its influence on driver
safety and the potential for increased risk of accidents, injuries, and fatalities. Approximately …

Road traffic poses negative externalities on society and represents a key challenge in
sustainable transportation. However, the existing literature about the assessment of traffic …