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This paper studies the synchronization and tracking issue for the connected and automated vehicle (CAV) platoon with mixed-order nonlinear vehicle dynamics. Previous researches have demonstrated that vehicle platoons can improve traffic efficiency and minimize the incidence of traffic collisions. However, vehicles within the same platoon may have different-order dynamics in practical scenarios. The heterogeneity issue of a vehicle platoon caused by the different-order dynamics is difficult to address by existing platoon control methods. Therefore, the platoon synchronization and tracking control problem for the heterogeneous CAV platoon which consists of mixed-order vehicles with a hybrid of second- and third-order dynamics is formulated in this paper. The proposed novel distributed sliding mode (DSM) control protocols for vehicles with second- and third-order dynamics aim to guarantee the convergence of vehicle state errors and the stability of the heterogeneous platoon. The distributed neural network-based adaptive estimation technique are developed in this paper to approximate the unknown uncertainties and compensate for the model nonlinearities of the platoon system. The uniform ultimate boundedness of errors and string stability are substantiated through the Lyapunov theory and infinity-norm technique. The efficacy of the developed platoon control strategies can be verified by the numerical examples.

Automated platooning is gaining increasing attention because it is regarded as a highly efficient transportation mode to solve traffic congestion problem. Although different intraplatoon spacing strategies have been proposed, little research has focused on quantitative optimization of spacing policy from a safety perspective considering differences between automated and human-driven platooning. In addition, there still is a lack of comprehensive research into string stability and delay robustness of cooperative adaptive cruise control (CACC) for heterogeneous platoons. This paper proposes a quantitative spacing policy in quadratic form based on safety index optimization under hard braking scenarios. The expected value of collision severity is taken as the main index for spacing optimization. The CACC strategy then tracks the proposed spacing considering fluctuation of multitime delays and uncertainty of vehicle dynamics. Based on sliding model control theory and frequency stability criteria, the sufficient conditions satisfying CACC stability and string stability were given. The robustness of the CACC system considering communication latency fluctuation was shown using simulation results. Compared with the existing control strategy, the proposed control strategy is more robust to communication latency, and string stability can be guaranteed. The proposed spacing strategy effectively can reduce collision risk, and the proposed CACC strategy improves latency robustness on the premise of ensuring string stability. [ABSTRACT FROM AUTHOR]

This paper investigates a platooning problem of connected vehicles subject to communication interruptions and latency. For a heterogeneous platoon of vehicles, a hybrid reference model with cooperative adaptive cruise control (CACC) and adaptive cruise control (ACC) is established. Then a novel CACC-ACC switching control method is suggested, which activates either a CACC scheme or an augmented ACC strategy depending on the status of communications. By introducing a platoon state tracking error system, a control algorithm is derived using finite-time sliding-mode control theory, which can robustly guarantee string stability and zero steady-state spacing error of the vehicular platoon. Simulations have shown the effectiveness and superiority of the method. [ABSTRACT FROM AUTHOR]

Platooning vehicles are beneficial in comfortable driving, safety, and enhanced transportation efficiency. Platooning vehicles with cooperative adaptive cruise control (CACC) mode can potentially result in a small distance between vehicles with assured string stability. This CACC-based platoon control can be realized by vehicle-to-vehicle (V2V) or vehicle-to-everything (V2X) communication between vehicles. In this regard, the distributed control framework is widely used. It claims robustness to communication uncertainties since each vehicle has its controller. With the rapid research on V2X, the centralized framework is another option for the platooning vehicle control framework. This paper investigates and analyzes the centralized and distributed control framework under platoon uncertainty. In most of the papers, the platoon uncertainty is considered as road slope and vehicle dynamics model. In this paper, the platoon uncertainty refers to the platoon types, namely homogeneous and heterogeneous platoon. The analytical platoon stability is studied for both frameworks under different platoon types. It gives the minimum time gap boundary to guarantee string stability for both frameworks. The numerical string stability is performed by the simulation to verify the analytical. The simulation is done using the integrated PreScan and Matlab/Simulink. Then, the robustness of both frameworks is evaluated under latency and packet loss. Finally, the performance of both frameworks is also evaluated.

To deal with energy crisis and environmental issues, higher fuel economy standards and more stringent limitations on greenhouse gas emissions for ground vehicles have been made. Ecological cooperative adaptive cruise control (Eco-CACC) has been considered as an effective solution to decrease the fuel consumption and greenhouse gas emissions of a platoon of vehicles, and this article proposes an Eco-CACC strategy for a heterogeneous platoon of heavy-duty vehicles with time delays. The proposed Eco-CACC strategy consists of distributed control protocols for the following vehicles and a new model predictive controller for the leading one. Firstly, after the distributed control protocols are designed based on the neighboring vehicle information, the sufficient conditions that guarantee the internal stability and string stability are derived, and the upper bound of the time delays under controller parameters is also obtained. Secondly, assuming the vehicle platoon as a rigid body with followers staying at desired positions, the new model predictive controller is designed in order to further improve the overall fuel economy of vehicle platoon. Simulations are conducted to validate the sufficient conditions of internal stability and string stability, and to explore the fuel saving performance of the proposed control strategy. The simulation results demonstrate that, compared with the benchmark, the proposed Eco-CACC strategy can significantly improve the fuel economy of heterogeneous platoon.

Connected and autonomous (CA) vehicles have been verified to significantly improve traffic efficiency. However, there is still a long lifespan for heterogeneous traffic flow consisting of both human-driven and CA vehicles. Thus a deep understanding of the heterogeneous platoon dynamics is critical to the traffic stability issues for the deployment of CA vehicles in the near future. This paper aims to develop a multiclass microscopic model for a heterogeneous platoon which can explicitly demonstrate the interaction between human-driven and CA vehicles. Specifically, the consensus-based control algorithm is adopted to model the dynamics of CA vehicles and a typical car-following model is used to describe the dynamics of human-driven vehicles. We then theoretically and numerically study the linear stability condition of the heterogeneous platoon which takes into account the probabilistic delay in the communication, the penetration of the CA vehicles, and the relative order of the vehicle types in the platoon. [ABSTRACT FROM AUTHOR]

Cooperative adaptive cruise control (CACC), as an extension of adaptive cruise control, connects multiple vehicles in a platoon via wireless communication. In practice, different vehicles may have different dynamic parameters and their exact values are unknown/uncertain to designers. In this brief, we propose a new control structure that uses an estimate of dynamic parameters to transform the heterogeneous CACC problem into the regulation problem of error dynamics for each vehicle in the platoon. An adaptive optimal control is proposed to learn the optimal feedback based on online data. The position transfer function between adjacent vehicles is further analyzed in the frequency domain. By sum of squares programming, the minimum headway values that ensure the vehicle string stability are found. Experiments on numerical and complex systems validate our method. [ABSTRACT FROM AUTHOR]

This paper deals with the adaptive control and identification of 1-D platoon of non-identical vehicles. Three common different topologies, such as predecessor following, bi-directional leader following, and two predecessors following are considered as the communication structures of platoon. For each topology, a new neighbor-based adaptive control law is introduced to estimate the parameter uncertainties, such as rolling resistance and air drag force coefficients. By presenting a new theorem, we prove that the estimates of unknown parameters converge to the actual values. Constant time headway policy is used to adjust the inter-vehicle spacing. For each topology, it is shown that the closed-loop dynamics of platoon is asymptotically stable. Afterward, the necessary conditions on control parameters assuring the string stability for each topology are derived by presenting further theorems. Moreover, the proposed methods are generalized for the heterogeneous platoons with time-varying network topology. Simulation results with different scenarios are provided to show the effectiveness of the presented approaches. [ABSTRACT FROM AUTHOR]

Literature has shown potentials of Connected/Cooperative Automated Vehicles (CAVs) in improving highway operations, especially on roadway capacity and flow stability. However, benefits were also shown to be negligible at low market penetration rates. This work develops a novel adaptive driving strategy for CAVs to stabilise heterogeneous vehicle strings by controlling one CAV under vehicle-to-infrastructure (V2I) communications. Assumed is a roadside system with V2I communications, which receives control parameters of the CAV in the string and estimates parameters imperfectly of non-connected automated vehicles. It determines the adaptive control parameters (e.g. desired time gap and feedback gains) of the CAV if a downstream disturbance is identified and sends them to the CAV. The CAV changes its behaviour based on the adaptive parameters commanded by the roadside system to suppress the disturbance. The proposed adaptive driving strategy is based on string stability analysis of heterogeneous vehicle strings. To this end, linearised vehicle dynamics model and control law are used in the controller parametrisation and Laplace transform of the speed and gap error dynamics in time domain to frequency domain enables the determination of sufficient string stability criteria of heterogeneous strings. The analytical string stability conditions give new insights into automated vehicular string stability properties in relation to the system properties of time delays and controller design parameters of feedback gains and desired time gap. It further allows the quantification of a stability margin , which is subsequently used to adapt the feedback control gains and desired time gap of the CAV to suppress the amplification of gap and speed errors through the string. Analytical results are verified via systematic simulation of both homogeneous and heterogeneous strings. Simulation demonstrates the predictive power of the analytical string stability conditions. The performance of the adaptive driving strategy under V2I cooperation is tested in simulation. Results show that even the estimation of control parameters of non-connected automated vehicles are imperfect and there is mismatch between the model used in analytical derivation and that in simulation, the proposed adaptive driving strategy suppresses disturbances in a wide range of situations. [ABSTRACT FROM AUTHOR]

Under the vehicle-to-vehicle (V2V) environment, the steady-state performance and the dynamic performance are both crucial for the traffic system. This paper proposes an in-depth methodology to provide some insights into the comprehensive changes of steady-state performance and dynamic performance of a heterogeneous platoon, which contains human-driven vehicles (HDVs) and connected and automated vehicles (CAVs). To further understand the impacts of various feedback information, an improved full velocity difference model that incorporates multiple feedback communicating information is developed. Based on the transfer function, the stability and steady-state error are proposed to characterize the steady-state performance, while the degree of fluctuation and duration of fluctuation are used to measure the dynamic performance. On the one hand, a key finding is that there are inconsistencies in steady-state and dynamic performance under particular feedback information. The acceleration or spacing feedback information can enhance the steady-state performance while degrading the dynamic performance. The speed difference feedback information yields the opposite result. On the other hand, it is discovered that compared to several types of feedback information, combining just one type of information is enough to boost the platoon performance. When the number of CAVs is considerable, combining two types of information will considerably increase the duration time. Therefore it is important to find the key feedback information for the platoon performance. The main purpose of this paper is to present a methodology of platoon performance analysis instead of discussing the various traffic scenarios. As a result, while certain results may alter in some specific scenarios, the proposed methodology and core contribution remain applicable to various traffic scenarios. • A methodology is proposed to analyze the steady-state and dynamic performances. • A new car-following model is presented for the feedback information impact study. • Inconsistencies exist between steady-state and dynamic performances for platoon. • Platoon performance is not directly related to the number of information types. • Only one type of information is sufficient to improve the platoon performance. [ABSTRACT FROM AUTHOR]

In this paper, the practical string stability of both homogeneous and heterogeneous platoons of adaptive cruise control (ACC) vehicles, which apply the constant time headway spacing policy, is investigated by considering the parasitic time delays and lags of the actuators and sensors when building the vehicle longitudinal dynamics model. The proposed control law based on the sliding-mode controller can guarantee both homogeneous and heterogeneous string stability, if the control parameters and system parameters meet certain requirements. The analysis of the negative effect of the parasitic time delays and lags on the string stability indicates that the negative effect of the time delays is larger than that of the time lags. This paper provides a practical means to evaluate the ACC systems applying the sliding-mode controller and provides a reasonable proposal to design the ACC controller from the perspective of the practical string stability. [ABSTRACT FROM PUBLISHER]