For the control of connected and autonomous vehicles (CAVs), most existing methods focus
on model-based strategies. They require explicit knowledge of car-following dynamics of …

Connected and automated vehicles (CAVs) have great potential to smooth mixed traffic flow.
To focus on the fact that the driving styles of HDVs are time-varying, a new control framework …

In this article, we present the first experimental results of data-driven predictive control for
connected and autonomous vehicles (CAVs) in dissipating traffic waves. In particular, we …

Jam-absorption driving (JAD) is a novel connected and automated vehicle-based (CAV-
based) control strategy that uses either a single or several absorbing cars to clear moving …

Data-driven cooperative control of connected and automated vehicles (CAVs) has gained
extensive research interest as it can utilize collected data to generate control actions without …

The development of control methods based on data has seen a surge of interest in recent
years. When applying data-driven controllers in real-world applications, providing theoretical …

Connected and automated vehicles (CAVs) technologies promise to attenuate undesired
traffic disturbances. However, in mixed traffic where human-driven vehicles (HDVs) also …

Data-driven predictive control of connected and automated vehicles (CAVs) has received
increasing attention as it can achieve safe and optimal control without relying on explicit …

We present a methodology of cooperative driving in vehicular traffic, in which for short-time
traffic prediction rather than one of the statistical approaches of artificial intelligence (AI), we …

Traffic waves in traffic flow significantly impact road throughput and fuel consumption and
may even lead to severe safety issues. Currently, in connected and autonomous …