Platoon Stability Research Articles

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.

A Platoon Control Method Based on DMPC for Connected Energy-Saving Electric Vehicles

This article presents a distributed model predictive control (DMPC) algorithm with energy management for the electric vehicle platoon. In addition, a braking force distribution strategy is proposed for the following vehicles (FVs) in the platoon, and the optimal energy recovery braking force distribution is adopted within the limits permitted by braking regulations. The cost function of DMPC includes the following aspects: drive/brake power deviation, vehicle distance deviation, trajectory deviation, and energy consumption. Through the simulation analysis, it is demonstrated that the proposed algorithm has satisfactory speed and trajectory tracking performance, platoon stability, and driving comfort. Two platoon control methods [DMPC without energy management, proportion integration differentiation (PID)] and two single vehicle control methods (single vehicle with or without recovery braking) are designed to verify the proposed method. A semiphysical experimental platform is established to verify the authenticity, accuracy, and effectiveness of the model and the proposed control methods.

Impact of Network Topology on the Resilience of Vehicle Platoons

This paper presents a comprehensive study on the impact of information flow topologies on the resilience of distributed algorithms that are widely used for estimation and control in vehicle platoons. In the state of the art, the influence of information flow topology on both internal and string stability of vehicle platoons has been well studied. However, understanding the impact of information flow topology on cyber-security tasks, e.g., attack detection, resilient estimation and formation algorithms, is largely open. By means of a general graph theory framework, we study connectivity measures of several platoon topologies and we reveal how these measures affect the ability of distributed algorithms to reject communication disturbances, to detect cyber-attacks, and to be resilient against them. We show that the traditional platoon topologies relying on interaction with the nearest neighbor are very fragile with respect to performance and security criteria. On the other hand, appropriate platoon topologies, namely <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> -nearest neighbor topologies, are shown to fulfill desired security and performance levels. The framework we study covers undirected and directed topologies, ungrounded and grounded topologies, or topologies on a line and on a ring. We show that there is a trade-off in the network design between the robustness to disturbances and the resilience to adversarial actions. Theoretical results are validated via simulations.

A geometric approach to analysing the effects of time delays on stability of vehicular platoons with ring interconnections

A geometric approach to analysing the effects of time delays on stability of vehicular platoons with ring interconnections

Stability and Safety of Cooperative Adaptive Cruise Control Vehicular Platoon under Diverse Information Flow Topologies

For the cooperative adaptive cruise control (CACC) vehicular platoon, apart from decentralized controllers, the dynamics of a platoon can be affected substantially by the information flow among connected and automated vehicles (CAVs). Existing research studies mainly focus on the stability analysis of platoons where CAVs only adopt the predecessor-following (PF) communication scheme; however, when CAVs “look” further ahead or behind than one vehicle, the stability of platoons might change. To this end, this study seeks to explore the stability and investigate the rear-end collision risk of CACC vehicular platoon under diverse information flow topologies. The research first comprehensively reviews typical information flow topologies for CAV platoons and platoon stability criteria for analyzing local and string stability of platoons. Moreover, the CACC longitudinal dynamic model is derived using the exact feedback linearization technique, which accommodates the inertial delay of powertrain dynamics. Accordingly, sufficient conditions of stability are mathematically derived to guarantee distributed frequency-domain-based control parameters. Simulation experiments are conducted to verify the correctness of derived sufficient stability conditions. The results show that platoons could better maintain stability with more vehicle information taken into consideration. However, when assessing the safety, it is found that the bidirectional type information flow topology would increase rear-end collision risk for CAV platoon. Further, the information flow topology of two-predecessor-leader following is the most recommended to enhance fully CAV platoon stability.

Car-Following Characteristics of Commercially Available Adaptive Cruise Control Systems and Comparison With Human Drivers

Adaptive cruise control (ACC) system, as one of the most fundamental modules of automated vehicles, is widely used in commercially available vehicles. It inevitably influences the traffic flow, from both the individual perspective, that is, its interaction with other traffic participants, and the traffic system perspective, that is, traffic string stability and road capacity. However, subject to limited data availability, no consistent conclusions on these impacts have been reached in the literature. Meanwhile, the similarities and differences between ACC vehicles and human-driven vehicles (HDV) have not been fully discussed and comparisons among different commercially available ACC systems remain to be untangled. Therefore, to fill this gap, this study investigates the car-following characteristics of various ACC systems and compares them with human drivers based on the open-access OpenACC database. We first identify the proper surrogate car-following model for denoting the driving behaviors of ACC vehicles and HDVs from five widely used car-following models, among which the best-fitted one is the intelligent driver model. Then, we implement the Gaussian mixture model and Jensen-Shannon divergence to describe the similarities between ACC systems and human drivers. Moreover, the string stability of different ACC platoons in various traffic conditions are investigated with a series of simulation experiments. Results show that all the ACC systems are string unstable, and more unstable than human drivers. The behavior of the Ford-ACC system is most similar to human drivers with a relative low instability, while the Peugeot-ACC system behaves most differently to human drivers, and aggressively with the highest instability.

Adaptive Resilient Control for Interconnected Vehicular Platoon With Fault and Saturation

This paper investigates the problem of the interconnected heterogeneous vehicular platoon in the presence of actuator fault of a vehicle, actuator saturation, and complex environment disturbances such as road slope, wind gust, and so on. First of all, a quadratic spacing error policy is applied to improve the vehicle platoon stability despite any vehicle suffering from actuator fault. Then, adaptive estimation laws are introduced to tackle the complex environment disturbances and the unknown upper bound of the actuator saturation approximation function. A robust adaptive sliding mode resilient control law is proposed to achieve the resilient ability and ensure the platoon system recover to the stable states in finite-time even if the occurrence of actuator fault. Finally, the string stability in finite-time of the platoon system is proved, the interconnected heterogeneous vehicular platoon system with seven vehicles is utilized to demonstrate the validity of the proposed control scheme.

Real-time deployable and robust cooperative control strategy for a platoon of connected and autonomous vehicles by factoring uncertain vehicle dynamics

In real-world driving environments, a platoon of connected and autonomous vehicles (CAVs) will be subject to many disturbances (e.g., aerodynamic drag, dynamic road gradients) that can prevent them from achieving desired control accurately. These disturbances can cause uncertainties in the vehicle dynamics, reducing platoon safety and mobility. To address this problem, this study proposes a robust cooperative control (RCC) strategy, developed as a minimax problem, to ensure the safe and efficient maneuvering of a CAV platoon in the worst-case situation due to uncertainties in the vehicle dynamics. The maximization subproblem of the minimax problem determines the inputs of the uncertainties to maximize the cost function (i.e., the platoon performance indicator), while the minimization subproblem seeks to optimize the control decisions for all following vehicles in the platoon to minimize the cost function using inputs of the uncertainties from the maximization subproblem. A novel partition-based method of feasible direction is proposed to solve the minimax problem. It is globally convergent and computationally efficient, enabling the RCC strategy to be deployed in real time. The conditions for robust stability of the CAV platoon are also analyzed. Results from numerical studies show that compared to a control strategy that ignores uncertainties in vehicle dynamics, the RCC strategy can substantially improve the platoon performance under disturbances. Hence, it can be used to enable the safe and efficient maneuvering of CAV platoons in a real-world driving environment.

String Stability of Connected Vehicle Platoons Under Lossy V2V Communication

Recent advances in vehicle connectivity have allowed formation of autonomous vehicle platoons for improved mobility and traffic throughput. In order to avoid a pile-up in such platoons, it is important to ensure platoon (string) stability, which is the focus of this work. As per conventional definition of string stability, the power (2-norm) of the spacing error signals should not amplify downstream in a platoon. But in practice, it is the infinity-norm of the spacing error signal that dictates whether a collision occurs. We address this discrepancy in the first part of our work, where we reconsider string stability from a safety perspective and develop an upper limit on the maximum spacing error in a homogeneous platoon as a function of the acceleration maneuver of the lead vehicle. In the second part of this paper, we extend our previous results by providing the minimum achievable time headway for platoons with two-predecessor lookup schemes experiencing burst-noise packet losses. Finally, we utilize throttle and brake maps to develop a longitudinal vehicle model and validate it against a Lincoln MKZ which is then used for numerical corroboration of the proposed time headway selection algorithms.

On Time Headway Selection in Platoons Under the MPF Topology in the Presence of Communication Delays

For platoons under the multiple-predecessor following (MPF) topology, communication delays can compromise both the internal stability and string stability. The most straightforward solution to guarantee stability is by increasing the time headway. However, time headway plays a significant role in road capacity and increasing its value is in contrast with the idea of platooning. In this study, internal stability and string stability of platoons suffering from communication delays are investigated and a lower bound for the time headway is proposed. Using this bound, platoons do not need to massively increase the time headway in order to compensate for the effects of communications delays. Finally, we evaluate the proposed lower bound on the time headway and the simulation results demonstrate its effectiveness.

Reinforcement Learning based cooperative longitudinal control for reducing traffic oscillations and improving platoon stability

Stop-and-go traffic poses significant challenges to the efficiency and safety of traffic operations. In this study, a cooperative longitudinal control based on Soft Actor Critic (SAC) Reinforcement Learning (RL) is proposed to address this issue. The reward function is carefully designed to consider vehicle cooperation and to achieve three main objectives: safety, efficiency, and oscillation dampening. A global performance metric for oscillation dampening is proposed to evaluate the developed RL and other baseline models. Depending on the number of preceding vehicles that can share maneuver information, two models RL-1 and RL-2 are proposed and compared with human driven (HD) and an adaptive cruise control (ACC) model using the HighD and simulated data. It is found that with information from additional preceding vehicles, RL-2 can dampen shockwaves more efficiently. Specifically, RL-1 and RL-2 decrease traffic oscillation by 15%-36% and 15%-42%, respectively, while HD amplifies the oscillation by 14–37%. The ACC model can also dampen shockwaves but is not as effective as RL-1 and RL-2. The two RL control methods are further evaluated based on data collected using a commercial Model X vehicle. Compared with the commercial Model X ACC vehicle in some controlled settings, the proposed RL methods can better dampen the stop-and-go waves by generating smaller oscillation growth, overshooting, and average acceleration/deceleration rate change, suggesting that they can generalize well in a new but similar environment. Finally, the RL methods are evaluated considering a platoon of vehicles with different RL penetration rates. The results show that they consistently outperform HD and ACC in dampening shockwaves.

Fully Distributed Resilient Cooperative Control of Vehicular Platoon Systems Under DoS Attacks

This letter is concerned with distributed resilient platoon control of multiple vehicles subject to denial-of-service (DoS) attacks. In order to accommodate the effects of DoS attacks, a fully resilient distributed control strategy is presented by designing an adaptive control gain, where any global information of communication topology is no longer required. Then, the conditions of time duration rates and frequency of DoS attacks on stability of vehicular platoons can be characterized. Finally, a numerical simulation example is given to validate the obtained results.

Distributed Formation Control Algorithm for Improved String Stability in Heterogenic Vehicle Platoons

Achieving speed, safety and energy optimization in vehicle platoons is among the important topics of recent years. In this context, this work focuses on improving the string stability (SS) of heterogeneous platoons. Better SS allows for smaller gap between vehicles, which means shorter time headway for Cooperative Adaptive Cruise Control (CACC) or inter-vehicle following-distance for platooning. Shorter time headway or inter-vehicle distance results in better road use and less fuel consumption. Rather than compensating for dynamic differences by means of low level control schemes by implementing pre-compensators at vehicle level, this work takes a different approach, where a higher level of control is preferred to improve SS: The platoon formation. To achieve this, it is important to ensure that each vehicle is in its optimum position in the platoon based on its dynamics for highest string stability. This generally leads to the vehicle with highest inertia to lead the platoon and the lowest one as the last follower. In this study, a platoon formation algorithm is proposed to run on each vehicle, leading to an optimum overall string structure. The efficiency of the algorithm is demonstrated by simulations in Matlab(R) for a four-vehicle platoon.

Scalable and Resilient Platooning Control of Cooperative Automated Vehicles

This paper addresses the problem of distributed cooperative longitudinal control of automated vehicle platoons subject to a variety of uncertainties, including unknown engine time lags, external disturbances, measurement noises, and actuator anomaly in follower vehicles as well as unknown leader control. First, a unified framework is proposed for accomplishing resilient vehicle platooning, which empowers longitudinal vehicle state estimation, anomaly signal estimation and compensation, and adaptive platoon controller design to be addressed in a comprehensive way. Second, a novel scalable platooning control design approach is developed to guarantee desired platoon stability and resilience over generic communication topologies and various spacing policies. A salient feature of the approach is that the design procedure does not depend on any global information of the associated topology, and thus preserves essential scalability for large and/or size-varying platoons. Third, it is shown that the proposed longitudinal platooning control approach is promising for performing flexible cooperative maneuvers such as platoon splitting and merging that are beyond the capacity of most existing longitudinal platooning strategies. Finally, simulation results for different platoon maneuvers are elaborated to substantiate the efficacy of the proposed approach.

Connected and automated vehicle platoon maintenance under communication failures

Connected and automated vehicles (CAVs) use vehicle-to-vehicle (V2V) wireless communication to drive in platoons, which can improve traffic efficiency and reduce energy consumption. However, some vehicles in a platoon may experience communication failures for various reasons, such as packet loss, signal blocking, or damage to vehicle communication module hardware. This will result in two phenomena: the platoon communication topology will be changed, and the behavior of vehicles without communication capabilities will degenerate to that of automated vehicles (AVs). The platoon will be unstable under the influence of these two phenomena. To mitigate the impact of these two phenomena on platoons, we propose a dynamic communication topology-based CAV-following model. This model takes into account changes in communication topology in a platoon due to communication failures or perceptual errors resulting from vehicle degradation. Two core features ensure that this model is able to perform platoon maintenance under communication failure. First, the CAVs in a platoon dynamically adjust the weight values of the acquired driving information based on the communication topology. Second, an adaptive Kalman filter (AKF) method is applied to reduce perceptual error. The effectiveness of the platoon maintenance scheme proposed in this study is verified by a series of simulation experiments. The results show that the proposed model can effectively maintain CAV platoons regardless of communication failures under steady-state or non-steady-state traffic flows. This finding indicates that CAV designers should design control schemes that take into account possible changes in the communication topology. Furthermore, our method has potential advantages for improving the platoon stability of CAVs driving on roads where communication is poor.

Heavy Road Vehicle Platoon Control Considering Brake Fade With Adaptive Mass and Road Gradient Estimation

Heavy commercial road vehicle (HCRV) platoons are viable logistic solutions to freight movement. During long haul platoon operation, it is common to encounter roads of different gradients. This paper investigates the effect of brake fade phenomenon, which happens due to the continuous application of brake during downgrade operation on the string stability of HCRV platoons. A brake actuator model incorporating temperature effects during braking and characterizing brake fade has been used. A Sliding Mode Control (SMC) based string stable controller, which compensates for brake fade, has been designed. Since the brake fade factor and hence platoon stability directly depend upon the road gradient and vehicle mass, which are not directly measurable quantities, an algorithm that adaptively estimates the same has been integrated with the controller design. The algorithm could estimate the mass and gradient values with less than 2% mean absolute percentage error. The stability of the proposed fade compensated controller has been analyzed and its efficacy has been tested for various road conditions and for homogeneous and heterogeneous (overloaded cases) platoon operations. The proposed approach was seen to ensure string stability for all the considered test scenarios.

An Approach to Compensate for Heterogeneous Feedback and Actuation Delays in Platooning Systems

Feedback information and actuation delays in Connected and Automated Vehicle (CAV) systems are detrimental to the string stability of CAV platoons. A generic approach is proposed to design platooning controllers that explicitly compensate for delays in communication, sensors and vehicle actuators and can be applied to platoons with different communication topology and different spacing policies. The main mechanism behind the delay-compensating design is to facilitate the host vehicle's future status (thus compensating for actuation delay) to track the preceding vehicles’ history status (thus compensating for communication and sensing delays). This is realized by reformulating the desired spacing policies. Controller analysis shows the string stability of the proposed framework is guaranteed under delays from heterogeneous sources. Simulation is carried out to compare the string-stability performance of the designed systems with the baseline controllers without delay compensation. Simulation results verify that our approach generates controllers that require smaller time gap/spacing to keep the string stability of the systems than baseline controllers.