Concerning the critical role of Intelligent Transportation System (ITS) in tackling the problem
of traffic congestion, and enhancing the safety, mobility and sustainability of the transport …

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 …

This paper presents an innovative method to adaptively optimize traffic signal plans based
on the estimation of traffic situation achieved from the information of various penetration …

Optimal traffic control and signal planning can significantly reduce traffic congestion and
potential delays at intersections. However, a major challenge to optimize traffic signal timing …

Queue length estimation is of great importance for measuring traffic signal performance and
optimizing traffic signal timing plans. With the development of connected vehicle (CV) …

Queue length estimation is imperative as a tool of designing traffic characteristics of an
intersection while queue length prediction enables to identify the traffic congestion in …

This paper combines millimeter-wave radar (MMW) data with connected autonomous
vehicle (CAV) trajectory data to estimate queue length on a second-by-second basis. Firstly …

For the problem of relatively severe lateral vibration found in the vertical electrodynamic
shaker experiment, an electromechanical coupling dynamic model of the electrodynamic …

This study predicts traffic congestion in four US cities using various machine learning
models. The research utilizes different regression-based models to predict congestion …

Congestion in vehicular scenarios has become one of the hot research areas among
researchers. It is one of the most challenging issues, and it occurs when roads or channels …