Platoon Stability Research Articles

Discrete Multi-Objective Switching Topology Sliding Mode Control of Connected Autonomous Vehicles With Packet Loss

Information flow topology is crucial in the control of connected autonomous vehicles. It has a substantial influence on the platoon's performance, especially in scenarios with imperfect communication. To address this issue, this study provides a real-time switching topology technique for improving the platoon's performance under various types of imperfect communication situations and constant packet dropout rates. First, a discrete sliding mode controller with a double power reaching law is designed for a nonlinear heterogeneous vehicle dynamic model with packet loss. Then, Lyapunov analysis is applied to ensure the platoon's stability and string stability. Finally, a two-step switching topology framework is introduced. The first step is to design an offline Pareto optimal topology search with some predicted imperfect communication scenarios, where the platoon's tracking ability, fuel consumption, and driving comfort are optimised using a multi-objective evolutionary algorithm based on decomposition with two opposing adaptive mechanisms. In the second step, the optimal topology is switched and selected in real-time from among the previously acquired Pareto optimal topology candidates, to reduce the control cost. To validate the proposed approach, numerical simulations are conducted. According to the results, compared to a standard robust sliding mode controller, the suggested technique enhances platoon tracking ability by 97.73 percent, fuel efficiency by 9.96 percent, and driving comfort by 20.18 percent, respectively.

Privacy-Preserving Platooning Control of Vehicular Cyber–Physical Systems With Saturated Inputs

Metaverse allows the physical reality to tightly integrate with the digital universe. As one typical metaverse application, platooning control of vehicular cyber–physical systems has attracted extensive attention as it is beneficial to improve traffic efficiency, driving safety, and emission reduction. However, due to the open nature of wireless communication networks, the transmitted vehicle-to-vehicle (V2V) data packets become exposed to the public and concomitant data leakage can lead to unintended consequences to vehicular platoons. This article is concerned with the privacy-preserving platooning control issue of vehicular cyber–physical systems with input saturations. First, a novel distributed proportional-integral observer is proposed to estimate the full state of each vehicle, where the integral terms with a forgetting factor facilitate to realize the tradeoff between transient performance and steady-state performance for the platoon. Second, sampled-data-based dynamic encryption and decryption schemes, featuring a dynamic private key, are developed such that the encrypted and decrypted V2V data can be kept private to each platoon vehicle. It is then shown that the platooning control problem over a generic communication topology can be cast into the stability issue of an auxiliary dynamic system. Furthermore, sufficient conditions on the existence of the desired observer and controller gains as well as the private key parameter selection are derived to guarantee the desired platoon stability and privacy preservation requirements. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed control method.

Ecological Cooperative Adaptive Cruise Control for Heterogenous Vehicle Platoons Subject to Time Delays and Input Saturations

Public concerns about energy crisis and environmental issues lead to higher fuel economy standards and more stringent limitations on greenhouse gas emissions for ground vehicles, and ecological cooperative adaptive cruise control (eco-CACC) is considered to be effective in reducing fuel consumption and greenhouse gas emissions of vehicle platoons. In this paper, an eco-CACC strategy is presented for heterogeneous platoons with time delays and input saturations to achieve platoon stability, fuel economy, riding comfort and driving efficiency. The proposed eco-CACC strategy includes distributed linear feedback control (DLFC) for following vehicles and model predictive control (MPC) for the leading one. To obtain platoon stability, the DLFC protocol is designed using state errors between an ego vehicle and its preceding one, and the frequency domain method is employed to derive the sufficient conditions of platoon stability for the DLFC protocol. Then, to achieve fuel economy, passenger comfort and driving efficiency without violating the different input saturations of vehicles, the constrained fuel consumption optimization problem of the leading vehicle (CFCO-LV) is formulated based on delay MPC, where the weighted sum of the overall fuel consumption and velocity band-stop functions of vehicle platoon is minimized. To quickly obtain the MPC controller, an improved particle swarm optimization (PSO) algorithm is used to solve the CFCO-LV problem. Simulations are implemented to validate the effectiveness of the proposed eco-CACC strategy, and the simulation results demonstrate that, compared with benchmark, the proposed strategy can save 2.19%~8.24% of fuel for the heterogeneous platoon under different velocity ranges.

Joint Sliding-Mode Controller and Observer for Vehicle Platoon Subject to Disturbance and Acceleration Failure of Neighboring Vehicles

This article designs a jointly distributed adaptive sliding-mode controller (DASMC) and disturbance observer (DO) for a heterogeneous platoon of connected vehicles (CVs) subject to disturbance and acceleration failure of neighboring vehicles under the multifold common communication topologies. To circumvent the effects of disturbance and acceleration failure of neighboring vehicles, the disturbance arising from the vehicle heterogeneity and nonlinearity as well as the acceleration of neighboring vehicles is jointly estimated as a lumped disturbance by a DO. In particular, the sliding-mode surface with adaptive law is designed based on the defined lumped errors to support the diversity of communication topologies. Then, the DASMC with DO is designed according to the vehicle dynamic model. Meanwhile, the stability of the designed DASMC with DO is analyzed based on the Lyapunov technique. In addition, the string stability of the CV platoon is proved. Finally, the capabilities of the developed control scheme are demonstrated by the simulation and experiment under different communication topologies and compared with existing methods.

Longitudinal Control-Oriented Spectrum Sharing Based on C-V2X for Vehicle Platoons

Combined with the development of wireless communication, the vehicle platoon will play a key role in the field of intelligent transportation system, due to its significant advantages in improving traffic safety, increasing road capacity, decreasing energy consumption, etc. In a vehicle platoon, the driving-related information is collected through vehicle-to-vehicle (V2V) communication to guarantee safety and improve control performance. However, it has been proved that the delay and reliability of V2V communication greatly affect the platoon stability. In this article, we investigate the spectrum-sharing problem for a vehicle platoon satisfying longitudinal control requirements. Particularly, we derive the communication delay constraints that guarantee plant stability and string stability. Then, using the obtained delay constraint, the wireless resource management, including the optimal power allocation and selection of spectrum sharing of the involved vehicles, is carried out in consideration of intracell interference and heterogeneous communication requirements. Finally, simulation results demonstrated the feasibility and effectiveness of the proposed scheme in vehicle-following control and wireless resource allocation.

State-Estimation-Based Control Strategy Design for Connected Cruise Control With Delays

The research on connected and automated vehicles attracts much attention recently. In connected vehicle systems, connected cruise control (CCC) is a wildly concerned technique to improve traffic safety and mitigate congestion. In this article, an optimal state-estimation-based (SE-based) control algorithm is proposed in a backward recursion manner to regulate CCC vehicle's longitudinal motion under stochastic communication delays, state noises, and channel interferences. Based on the analysis of error dynamics of vehicles and optimal state estimation strategy, the SE-based system dynamics is first formulated by using the Kalman filtering method. Then, a two-step SE-based control algorithm aiming at minimizing the quadratic system cost is proposed to enhance the vehicular platoon stability. In particular, the optimal control strategy can be generated online as a linear function of the estimated state information and previous control signals, and the corresponding coefficient can be iteratively calculated in an offline step. Finally, the results are successfully extended to the case of arbitrary communication delays, and the condition for the asymptotically mean square stability of the proposed optimal SE-based CCC algorithm is derived. Simulation results indicate that the proposed SE-based control algorithm has better system performance and control stability compared with existing works.

Stability of connected and automated vehicles platoon considering communications failures

As a form of a future traffic system, a connected and automated vehicle (CAV) platoon is a typical nonlinear physical system. CAVs can communicate with each other and exchange information. However, communication failures can change the platoon system status. To characterize this change, a dynamic topology-based car-following model and its generalized form are proposed in this work. Then, a stability analysis method is explored. Finally, taking the dynamic cooperative intelligent driver model (DC-IDM) for example, a series of numerical simulations is conducted to analyze the platoon stability in different communication topology scenarios. The results show that the communication failures reduce the stability, but information from vehicles that are farther ahead and the use of a larger desired time headway can improve stability. Moreover, the critical ratio of communication failures required to ensure stability for different driving parameters is studied in this work.

Pareto Optimal Information Flow Topology for Control of Connected Autonomous Vehicles

Information flow topology plays a crucial role in the control of connected autonomous vehicles. This paper proposes an approach to search for the Pareto optimal information flow topology off-line for the control of connected vehicles’ platoon using a non-dominated sorting genetic algorithm. Based on the obtained Pareto optimal information flow topology, the platoon's overall performance in terms of three main performance indices: tracking index, acceleration standard deviation, and fuel consumption, are all improved. Numerical simulations are used to validate the effectiveness of the proposed approach. In the simulation, the impact of different information flow topologies on the performance of the connected autonomous vehicles platoon is firstly investigated. The results show that more communication links can lead to better tracking ability. The smoothness of the velocity profile is consistent with fuel economy, while velocity profile's smoothness, fuel economy and communication efficiency are in contrary to the tracking index. Then, five cases are discussed using the Pareto optimal information flow topology. The results indicate that while ensuring the platoon's stability, the obtained Pareto optimal information flow topology can improve the tracking ability by 33.67% to 49.35%, and fuel economy by 7.181% to 16.93% and driving comfort up to 14.9%.

Robustness Analysis of Platoon Control for Mixed Types of Vehicles

Currently, with the development of driving technologies, driverless vehicles gradually are becoming more and more available. Therefore, there would be a long period of time during which self-driving vehicles and human-driven vehicles coexist. However, for a mixed platoon, it is hard to control the formation due to the existence of the manual vehicles resulting in weak robustness and slow consensus rate on this system of platoons because of uncertainties caused by human factors for manual vehicles. In order to solve this problem, we establish models of mixed platoons with mixed types of connected and automated vehicles (CAVs), human-driven vehicles (HDVs) and HDVs without the vehicle awareness device (HDVWs). We subsequently design <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_{\infty} $ </tex-math></inline-formula> controllers for the mixed platoons to realize the formation consensus. In addition, we use the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {H}_{\infty} $ </tex-math></inline-formula> norm of mixed platoons as the control objective investigating the robustness of the control algorithms in alleviating the platoon uncertainties. Furthermore, conditions are proved to maintain the stability of the mixed platoons, and the stability is analyzed based on the variation of the penetration rate of the manual vehicles. Finally, we formulate conditions for parameters according to the definition of string stability to avoid the collisions of vehicles. The results in this study are tested with simulations and suggest that the presented controllers can ensure the consensus of mixed platoons under uncertainties.

Hybrid Cost Function Distributed MPC for Vehicle Platoons With Stability and String Stability Properties

Distributed MPC schemes for control of vehicle platoons typically employ a p-norms based cost function to achieve stability and string stability. Quadratic cost functions yield smoother trajectories, but they are not aligned with string stability conditions. Hence, in this paper, we develop distributed MPC controllers for vehicle platoons based on a hybrid cost function, which combines infinity norms and quadratic forms. Sufficient conditions for global platoon stability and leader-follower string stability are derived for the developed hybrid cost function and applied to lateral dynamics control. Simulation results show that the hybrid cost function yields lateral position errors that are 10 times smaller (for the maximum error) compared with an infinity norms based cost function.

Mesoscopic Controller for String Stability of Platoons With Disturbances

This article exploits macroscopic information for the control of autonomous vehicles in platoon formation in case of external disturbances. The use of such information leads to smoother platooning. A mesoscopic controller is proposed, and disturbance string stability is proven through input-to-state stability concepts. Simulations prove the efficacy of the proposed approach by showing its robustness with respect to the presence of perturbations acting on the platoon vehicles.

Decentralized Energy Management for Wireless Power Transfer Assisted Platoon Autonomous Driving: A Leader-to-Follower Approach

By platooning, a string of autonomous electric vehicles (AEVs) is instructed to accept simultaneous driving control to facilitate the autonomous driving with improved traffic safety and efficiency. However, an AEV with limited battery capacity cannot stably travel with the platoon if its energy is exhausted, which leads to unexpected platoon splitting and further influences the platoon stability. To overcome the bottleneck of platoon lifetime, we integrate wireless power transfer (WPT) into platooning and propose WPT assisted platoon autonomous driving based on a leader-to-follower approach. Specifically, an energy-rich AEV plays as a leader in the platoon to provide reliable and trusted energy replenishment for energy-deficient platoon members who play as followers. We introduce the implementation of the leader-to-follower WPT and study its decentralized energy management. A user-oriented energy allocation problem is formulated, and a Nash mechanism is proposed to solve the problem through a game-based interaction among the noncooperative users. Numerical results demonstrate that the proposed mechanism can obtain the optimal solution in a privacy-friendly way and has great advantages in improving the overall satisfaction of users.

Mean square stability conditions for platoons with lossy inter-vehicle communication channels

This paper studies the mean-square stability of heterogeneous LTI vehicular platoons with inter-vehicle communication channels affected by random data loss. We consider a discrete-time platoon system with predecessor following topology and a constant time-headway spacing policy. Lossy channels are modeled by Bernoulli processes and allowed to be correlated in space. We make use of a class of compensation strategies to reduce the effect of data loss. Necessary and sufficient conditions are derived to guarantee the convergence of the mean and variance of the tracking errors, which depend not only on the controller design but also on the compensation strategy and the probabilities of successful transmission. We illustrate the theoretical results through numerical simulations, describing different platoon behaviors. We also provide insights on the mean-square stability as a necessary condition for string stability in this stochastic setting.

Research on the Impacts of Vehicle Type on Car-Following Behavior, Fuel Consumption and Exhaust Emission in the V2X Environment

The type of vehicles in realistic traffic systems are not homogeneous. Impacts of the preceding vehicle’s type on the car-following behavior, fuel consumption and exhaust emissions are still unclear. This paper presents a study on the impacts of two types of preceding vehicles, heavy vehicles and new energy vehicles, on car-following behavior, traffic flow characteristics, fuel consumption and exhaust emissions. Firstly, an extended car-following model was proposed by incorporating the influence of the preceding vehicle’s type. Secondly, impacts of the preceding vehicle’s type on platoon stability were analyzed by applying linear stability theory. Finally, numerical simulations were carried out to analyze impacts of the preceding vehicles’ type on the characteristics of the car-following platoon, traffic flow operation, and vehicle’s fuel consumption and exhaust emissions. The results reveal that, compared with the normal preceding vehicle, there are negative impacts of the heavy and new-energy preceding vehicles on the platoon stability, traffic flow operation, and vehicle’s fuel consumption and exhaust emissions, and these impacts are related to the corresponding sensitivity parameters and the penetration percentages of the two types of preceding vehicle. The research results of this paper can provide a reference for understanding car-following behavior and traffic-flow characteristics affected by the type of preceding vehicles in the V2X environment.

Data-Injection-Proof-Predictive Vehicle Platooning: Performance Analysis With Cellular-V2X Sidelink Communications

The increasing demand for road freight has raised tremendous attention to vehicle platooning, which reduces air resistance and improves fuel economy. To achieve a small and safe spacing between vehicles while ensuring platoon stability, wireless communication assistance is indispensable. However, the imperfection of communication brings degradation of platooning performance (i.e., spacing error) and more possibilities for adversarial attacks. This article proposes a prediction-assisted platooning mechanism from the perspective of performance optimization, wherein each vehicle establishes its local platoon model based on the information received from the communication network, thereby reducing information latency. Then, to secure the system against malicious vehicles, we carry out analysis and design of a detection algorithm for a typical attack type, i.e., the data-injection attack. The detection is based on three indicators: 1) absolute spacing error; 2) spacing prediction error; and 3) acceleration prediction error. The advantages of the novel platooning mechanism and detection algorithm are ultimately demonstrated on a road-traffic simulation platform that considers the imperfection of realistic vehicle perceptions and Cellular-Vehicle-to-Everything (C-V2X) communication.

Platoon control of connected vehicles with heterogeneous model structures considering external disturbances

This article studies the distributed cooperative control problem with the heterogeneous model structures and external disturbances for the connected vehicle (CV) platoon. We propose a hierarchical framework to separate information flow topology from local dynamics control, which aims to deal with the heterogeneous model structures of CV platoon. This hierarchical framework splits the control scheme into two layers, which include an observer in the upper-level layer and an integral sliding mode (ISM) controller in the lower-level layer. Then, the conditions for the asymptotic stability of the CV platoon are derived and the effectiveness of the ISM controller is demonstrated through the Lyapunov method. The research shows that compared with the traditional methods, the hierarchical framework does not need to specify the topology structure as a commonly used topology. Finally, numerical simulation results are performed to test the effectiveness and superiority of the developed controller.

Guest editorial: Decision making and control for connected and automated vehicles

Guest editorial: Decision making and control for connected and automated vehicles

A distributed model predictive control method combined with delay compensator for multiple vehicle platoons

With an increasing number of vehicles on the road, multiple-vehicle platoons have become a new solution under communication constraints. However, the existing studies seldom consider the effect of the tail vehicle on the information transfer and platoon control over long distances, and thus the control performance under time-varying delays is unacceptable. In this study, a hierarchical multi-platoon control architecture considering the backbone platoon and sub-platoons is proposed under non-ideal communication conditions, where the backbone platoon layer communication topology is designed to achieve backbone platoon control and appropriate coordination among sub-platoons. Distributed model predictive controllers (DMPCs) for backbone- and sub-platoons that integrate delay compensation have been proposed. Buffers and delay compensators in the proposed DMPC are designed to reduce the interference caused by non-ideal communications. The asymptotic stability is analyzed at the sub- and multi-platoon levels. The results show that compared with traditional DMPC without a compensator, the proposed DMPC can eliminate the velocity lag and steady-state spacing errors and maintain the maximum velocity and spacing errors within 0.11 m/s and 0.17 m, respectively, under certain operating conditions. Thus, the proposed method guarantees the stability of multiple platoons under both the constant and time-varying delay conditions.

Coordinated control of heterogeneous vehicle platoon stability and energy-saving control strategies

This work presents an overall control strategy for heterogeneous vehicle platoons to minimize energy consumption and improve transportation efficiency by sustaining the string stability of the platoon on signalized arterials under external perturbations. First, the stability criterion is derived by analyzing the string stability of multi-time-lag heterogeneous platoon based on the intelligent driver model (IDM). The optimal model of vehicle platoon consumption is reconstructed to reduce the optimization variables to simplify the solution process. Then, by combining the reconstructed optimal control model with stability, a stable eco-driving model is established for a heterogeneous vehicle platoon consisting of multiple purely electric intelligent connected vehicles (ICVs) and human-driven vehicles (HVs). The overall speed control strategy is proposed by combining the vehicle platoon stability and energy consumption for nonlinear optimization analysis. The platoon is made to pass through the signal intersection with the highest efficiency and the lowest energy consumption to achieve a balance of stability and energy saving. Third, the overall model is optimally solved by a global optimization algorithm, and the numerical simulation has clearly validated the performance of the proposed driving control strategy.

Robust Min-Max Model Predictive Vehicle Platooning With Causal Disturbance Feedback

Platoon-based vehicular cyber-physical systems have gained increasing attention due to their potentials in improving traffic efficiency, capacity, and saving energy. However, external uncertain disturbances arising from mismatched model errors, sensor noises, communication delays and unknown environments can impose a great challenge on the constrained control of vehicle platooning. In this paper, we propose a closed-loop min-max model predictive control (MPC) with causal disturbance feedback for vehicle platooning. Specifically, we first develop a compact form of a centralized vehicle platooning model subject to external disturbances, which also incorporates the lower-level vehicle dynamics. We then formulate the uncertain optimal control of the vehicle platoon as a worst-case constrained optimization problem and derive its robust counterpart by semidefinite relaxation. Thus, we design a causal disturbance feedback structure with the robust counterpart, which leads to a closed-loop min-max MPC platoon control solution. Even though the min-max MPC follows a centralized paradigm, its robust counterpart can keep the convexity and enable the efficient and practical implementation of current convex optimization techniques. We also derive a linear matrix inequality (LMI) condition for guaranteeing the recursive feasibility and input-to-state practical stability (ISpS) of the platoon system. Finally, simulation results are provided to verify the effectiveness and advantage of the proposed MPC in terms of constraint satisfaction, platoon stability and robustness against different external disturbances.