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 …

This paper presents an adaptive leading cruise control strategy for the automated vehicle
(AV) and first considers its impact on the following human-driven vehicle (HDV) with diverse …

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 …

The recently developed DeeP-LCC (Data-EnablEd Predictive Leading Cruise Control)
method has shown promising performance for data-driven predictive control of Connected …

Cooperative control of Connected and Autonomous Vehicles (CAVs) promises great
benefits for mixed traffic. Most existing research focuses on model-based control strategies …

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 …

Cooperative control of connected and automated vehicles (CAVs) promises smoother traffic
flow. In mixed traffic, where human-driven vehicles with unknown dynamics coexist, data …

Connected and autonomous vehicles (CAVs) have great potential to improve road
transportation systems. Most existing strategies for CAVs' longitudinal control focus on …

In the foreseeable future, the coexistence of Connected and Automated Vehicles (CAVs)
and Human-Driven Vehicles (HVs) will continue to be a feature of the traffic landscape for an …

The design of cooperative adaptive cruise control is critical in mixed traffic flow, where
connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) coexist …