This paper presents a data-driven framework to quantitatively analyze the disturbance
amplification behavior of automated vehicles in car-following (CF). The data-driven …

This paper develops a stochastic and unifying framework to examine variability in car-
following (CF) dynamics of commercial automated vehicles (AVs) and its direct relation to …

This paper proposes an anti-disturbance car-following strategy for attenuating (i) exogenous
disturbances from preceding traffic oscillations and (ii) endogenous disturbances in …

Dedicated left‐turn lanes are traditionally used at intersections. This practice may not be
optimal where heavy traffic exists from multiple directions. As is well known, the capacity can …

Deep reinforcement learning (DRL) algorithms often face challenges in achieving stability
and efficiency due to significant policy gradient variance and inaccurate reward function …

This study proposes a reliable longitudinal distributed control strategy for connected and
automated vehicles (CAVs) in the presence of communication cyberattacks. The proposed …

Connected and automated vehicles will characterize the future of the mobility, featured by
Smart Roads and Internet of Things technologies. Vehicles will behave as mobile nodes of a …

Connected and Automated Vehicles (CAVs) offer a promising solution to the challenges of
mixed traffic with both CAVs and Human-Driven Vehicles (HDVs). A significant hurdle in …

This paper aims to ensure the string stability of a mixed vehicle group composed of
connected and automated vehicles and traditional human-driven vehicles on the road. To …

With a growing complexity of the intelligent traffic system (ITS), an integrated control of ITS
that is capable of considering plentiful heterogeneous intelligent agents is desired …