This study proposes a rotation-based connected automated vehicle (CAV) distributed cooperative control strategy for an on-ramp merging scenario. By assuming the mainline and ramp line are straight, we firstly design a virtual rotation approach that transfers the merging problem to a virtual car following (CF) problem to reduce the complexity and dimension of the cooperative CAVs merging control. Based on this concept, a multiple-predecessor virtual CF model and a unidirectional multi-leader communication topology are developed to determine the longitudinal behavior of each CAV. Specifically, we exploit a distributed feedback and feedforward longitudinal controller in preparation for actively generating gaps for merging CAVs, reducing the voids caused by merging, and ensuring safety and traffic efficiency during the process. To ensure the disturbance attenuation property of this system, practical string stability is mathematically proved for the virtual CF controllers to prohibit the traffic oscillation amplification through the traffic stream. Moreover, as a provision for extending the virtual CF application scenarios of any curvy ramp geometry, we utilize a curvilinear coordinate to model the two-dimensional merging control, and further design a local lateral controller based on an extended linear-quadratic regulator to regulate the position deviation and angular deviation of the lane centerlines. For the purpose of systematically evaluating the control performance of the proposed methods, numerical simulation experiments are conducted. As the results indicate, the proposed controllers can actively reduce the void and meanwhile guarantee the damping of traffic oscillations in the merging control area.@en

This paper presents a car-following control strategy of connected automated vehicles (CAVs) to stabilize a mixed vehicular platoon consisting of CAVs and human-driven vehicles. This study first establishes a string stability criterion for a mixed vehicular platoon. Specifically, a mixed vehicular platoon is decomposed into “subsystems” that are all possible sequential subsets of the platoon. String stability is then defined as the “head-to-tail” string stability for all subsystems: the magnitude of a disturbance is not amplified from the first vehicle to the last vehicle of each subsystem. Based on this definition, distributed frequency-domain-based CAV control is proposed to increase the number of head-to-tail string stable subsystems and consequently dampen stop-and-go disturbances drastically. Specifically, an H-infinity control problem is formulated, where the maximum disturbance “damping ratios” in each subsystem is minimized within the predominant acceleration frequency boundaries of human-driven vehicles. Simulation experiments, embedded with real human-driven vehicle trajectories, were conducted, and results show that the proposed control can effectively dampen stop-and-go disturbances.@en

This work focuses on adaptive neural dynamic surface control (DSC) for an extended class of nonlinear MIMO strict-feedback systems whose control gain functions are continuous and possibly unbounded. The method is based on introducing a compact set which is eventually proved to be an invariant set: thanks to this set, the restrictive assumption that the upper and lower bounds of control gain functions must be bounded is removed. This method substantially enlarges the class of systems for which DSC can be applied. By utilizing Lyapunov theorem and invariant set theory, it is rigorously proved that all signals in the closed-loop systems are semi-globally uniformly ultimately bounded (SGUUB) and the output tracking errors converge to an arbitrarily small residual set. A simulation example is provided to demonstrate the effectiveness of the proposed approach.

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In this paper, a serial distributed model predictive control (MPC) approach for connected automated vehicles (CAVS) is developed with local stability (disturbance dissipation over time) and multi-criteria string stability (disturbance attenuation through a vehicular string). Two string stability criteria are considered within the proposed MPC: (i) the l_∞-norm string stability criterion for attenuation of the maximum disturbance magnitude and (ii) l₂-norm string stability criterion for attenuation of disturbance energy. The l_∞-norm string stability is achieved by formulating constraints within the MPC based on the future states of the leading CAV, and the l₂-norm string stability is achieved by proper weight matrix tuning over a robust positive invariant set. For rigor, mathematical proofs for asymptotical local stability and multi-criteria string stability are provided. Simulation experiments verify that the distributed serial MPC proposed in this study is effective for disturbance attenuation and performs better than traditional MPC without stability guarantee.

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