Platoon Stability Research Articles

Cooperative control of mixed vehicle platoon based on pinning consensus of heterogeneous multi‐agent system

AbstractThis paper proposes a longitudinal controller for the mixed vehicle platoon in the presence of driver response time‐delay and communication time‐delay based on the pinning consensus of heterogeneous multi‐agent system. Firstly, an adaptive pinning consensus control protocol and derive sufficient conditions for the heterogeneous non‐linear multi‐agent system are designed to achieve pinning consistency. Then, the heterogeneous characteristics of the vehicle are described based on the car‐following model, then the mixed vehicle platoon system model is constructed and a mixed vehicle platoon controller based on heterogeneous multi‐agent pinning consensus is proposed. Besides, the driver response time‐delay and communication time‐delay are introduced into the model, and a controller based on time‐delay heterogeneous multi‐agent pinning consensus is designed. Finally, the effectiveness of the proposed controller is verified by numerical simulations, and the effect of number of connected autonomous vehicle, different types of vehicle order, driver response time‐delay, communication time‐delay and the parameter of the controller on stability of mixed vehicle platoon is also quantitatively demonstrated.

Secure virtual coupling control of connected train platoons under cyber attacks

Virtual coupling of automated trains has emerged as a promising technology to enhance the operational efficiency and line capacity of railway transportation systems. However, the vulnerability of such systems to malicious cyber attacks poses a significant threat to their stability, reliability and applicability. This article addresses the challenge of ensuring secure virtual coupling control of connected train platoons subject to various cyber attacks, including false data injection attacks, denial-of-service attacks, and replay attacks. First, based on the low-dimensional and noisy sensor measurements, novel set-valued observers are designed for each follower train to estimate their inaccessible full longitudinal motion states despite uncertainties and unknown attacks and noises. Then, distributed secure attack-compensation-based virtual coupling control laws are developed to ensure the platoon's stability and resilience against cyber attacks. Additionally, formal stability analysis of the resultant estimation error system and platoon tracking error system is provided. Furthermore, two algorithms are presented to elaborate the offline observer and controller design process as well as their online implementation. Finally, based on the data of a realistic urban rail transit line, simulation experiments are conducted to validate the efficacy of the proposed theoretical findings.

PACC: A platoon-based adaptive cruise control strategy based on leader-following information topology to mitigate traffic oscillations under CAV environment

Traffic oscillations, often induced by repetitive acceleration and deceleration maneuvers in vehicles’ car-following behaviors, can cause many negative impacts on the traffic flow. With the development of connected and automated vehicle (CAV) technologies recently, scholars have made numerous effects on mitigating the propagation of traffic oscillations through a variety of advanced CAV control strategies, especially those related to the CAV platoon control. Different from the previous works, this paper proposed a platoon-based adaptive cruise control (PACC) strategy for CAV platoon to mitigate the traffic oscillations. The strategy is designed based on the novel and unique leader-following (LF) information topology. Built on the classical proportional-derivative (PD) controller that is implemented in the adaptive cruise control (ACC) strategy of autonomous vehicles (AVs), the PACC strategy is exquisitely designed to ensure the string stability of entire CAV platoon and the critically damped condition of each following CAV in the platoon. Credit to the rapid response of following CAV to the vibration of leading CAV’s dynamic status under LF information topology and the thorough consideration of string stability and damping characteristics in the PD controller design, the PACC strategy enables the CAV platoon to mitigate the traffic oscillations more efficiently than the existing cooperative adaptive cruise control (CACC) and ACC strategies. The numerical experiment for the mixed traffic flow on a single-lane ring road indicates that, when the CAV platoon adopts the PACC strategy, the performance of traffic flow in terms of operational efficiency, driving safety, passenger’s comfort, and fuel economy is substantially enhanced, compared with CACC and ACC strategies. In addition, the performance of PACC strategy gradually improves with the increase of market penetration rate (MPR) of CAVs and length of CAV platoon. Overall, the proposed PACC strategy is a promising solution to the mitigation of traffic oscillation under the CAV environment.

Research on Obstacle Avoidance Strategy of Automated Heavy Vehicle Platoon in High-Speed Scenarios

Amidst the rapid progression of the road transport industry, the safety and efficiency of heavy-vehicle platoons have garnered significant attention. The study tackles the challenge of obstacle avoidance presented by vehicles owing to their considerable mass, delayed response times, and line-of-sight impediments, by introducing a cooperative obstacle avoidance system for heavy-vehicle platoons based on deep reinforcement learning. The system comprises three primary modules: perception, decision-making, and control. Initially, the perception module acquires real-time environmental data. Subsequently, the decision-making module formulates obstacle avoidance decisions based on the acquired data. Specifically, it implements a two-stage braking obstacle avoidance strategy under low collision risk scenarios, while employing a fifth-degree polynomial for planning and tracking obstacle avoidance paths under high collision risk conditions suitable for steering maneuvers. The control module utilizes the local multi-agent deep deterministic policy gradient (LADDPG) algorithm to train the heavy-vehicle platoon agents, ensuring the formation’s maintenance while mitigating collisions with other vehicles and obstacles. The effectiveness of the proposed system is substantiated through simulation experiments, demonstrating its adaptability to various traffic conditions, selection of suitable obstacle avoidance strategies, and significant enhancement of obstacle avoidance performance and heavy-vehicle platoon stability.

Compensation control of commercial vehicle platoon considering communication delay and response lag

The real-time accurate control of vehicle is of great significance for the stability of platoon driving. To address the impact of random time-varying communication delays, communication packet loss, data disorder, and significant response lag of commercial vehicle on platoon control performance in non-ideal communication environment, a novel compensation control method for commercial vehicle platoon is proposed to overcome the abovementioned issues. The proposed method significantly improves the impact of communication issues and vehicle response lag on platoon control, ensuring platoon safety while reducing inter-vehicle spacing and spacing error, and maintaining platoon stability. In addition, this method combines the comprehensive compensation mechanism with the Distributed Model Predictive Controller (DMPC), avoiding the establishment of additional compensation control modules and effectively reducing the computational burden. The results under emergency braking condition show that, compared with the method without compensation, the proposed method significantly reduces inter-vehicle spacing and spacing error, reducing the average maximum spacing error from 29.25 m to 1.44 m, shortening the error convergence time of the platoon by 28 %, and ensuring platoon stability. Additionally, compared to the compensation method based on Kalman Filtering (KF) and Smith predictor, the proposed method can reduce the average maximum spacing error by 60 % while maintaining similar convergence time and platoon stability.

Observer‐based adaptive control of vehicle platoon with uncertainty and input constraints

AbstractThis study focuses on the highway platoon driving mode and proposes a distributed adaptive control algorithm based on an observer. Firstly, the adaptive observer is designed to compensate for the effect of unknown driving resistance and thus enhance the adaptation ability of the system to uncertainty. Secondly, an auxiliary system is introduced to specifically address actuator saturation constraints, ensuring the stability of the platoon driving in extreme conditions. Lastly, combining an event‐triggered mechanism, a control strategy is designed to achieve the stability of the entire platoon while maximizing the conservation of communication resources. The algorithm's viability and efficiency are confirmed through simulation outcomes.

Adaptive event-triggered sliding mode control for platooning of heterogeneous vehicular systems and its [formula omitted] input-to-output string stability

Platooning of vehicular systems is an effective technique for enhancing transportation efficiency. As the scale of the vehicular platoon systems increases, disturbances on individual vehicles can affect the whole platoon through their connections. Besides, excessive vehicles impose a significant burden on communication devices. Towards this end, this work investigates the distributed platoon control problem of connected vehicular systems subject to disturbances by employing a resource-efficient communication mechanism. The proposed adaptive event-triggered mechanism (AETM) avoids periodic data transmission and reduces communication burden among vehicles. Besides, the AETM regulates the triggered threshold dynamically via the perception of spacing errors and avoids continuous inter-vehicle communication. Next, an AETM-based finite-time extended state observer (AFESO) is designed to alleviate the impact of the external disturbances. Then, an adaptive event-triggered distributed sliding mode control (DSMC) framework is developed to guarantee platoon stability. It is approved that, under the proposed control method, the closed-loop system subject to the disturbances satisfies the L2 input-to-output string stability (L2-IOSS). The salient feature of the AETM-based DSMC is that the AETM can effectively reduce communication consumption, while DSMC mitigates the performance degradation caused by triggering errors and disturbances. Finally, numerical simulations demonstrate the effectiveness of the proposed algorithm.

Abnormal communication internet-connected vehicle platoon dynamical modeling and characteristics study

With the advent of the vehicle interconnection era, all the internet-connected vehicles (i.e. ICVs) can communicate with each other through the whole platoon, and great changes of the dynamical motion characteristics in traffic flow system is happening. The wireless communication system plays more and more important roles to keep traffic flow system stable and safe. However, communication failure is a common and unevitable phenomenon, and an ICV in a platoon will inevitably lose its connection with other vehicles sometimes. So it is necessary and meaningful to study ICV’s dynamical characteristics under abnormal communication conditions. The study firstly analyzed the information exchange mechanism among ICVs and classify communication failure into three modes. Secondly, by considering normal and abnormal communication conditions, a car-following model for internet-connected vehicle flows with bidirectional mean expected velocity field was proposed. Thirdly, the ICV platoon system stable state condition was deduced based on linear stability theory. Finally, full simulation logical scenarios were set to support the theoretical analysis results considering the ICV system’s stability and communication states comprehensively. As for the abnormal communication state simulations, the leading vehicle, last vehicle, and middle vehicle communication failure scenarios were selected as typical examples. The study conclusions are (i) for bidirectional communication ICV platoon system, forward-looking and backward-looking mean expected velocity field terms show different influences on its stability, (ii) sudden abnormal communication failures can dramatically destroy the vehicle platoon stability, and (iii) different vehicle position communication failure has different effects on the system stability.

Stability and Intervehicle Distance Analysis of Vehicular Platoons: Highlighting the Impact of Bidirectional Communication Topologies

Stability and Intervehicle Distance Analysis of Vehicular Platoons: Highlighting the Impact of Bidirectional Communication Topologies

Unknown input observer based neuro-adaptive fault-tolerant control for vehicle platoons with sensor fault and output quantization

Sensor fault and output quantization are common issues acting on vehicle platoon, and they may lead to performance deterioration, instability and even insecurity of the platoon. Therefore, this paper investigates the fault-tolerant control (FTC) problem of vehicle platoons with regard to the above two issues. Considering the probabilistic sensor fault and quantized measurement signals, an unknown input observer (UIO) based fault detection algorithm with adaptive threshold is developed for sensor health status monitoring. Then, an augmented vehicle platoon model is constructed by introducing a low-pass output filter, and a robust UIO is established for state reconstruction. Based on the above results, a fault-tolerant control scheme is exploited by employing the back-stepping control method and adaptive radial basis function neural network (RBF NN) approximation technique, which is proved to be capable of achieving the time-domain string stability (TSS) of vehicle platoons in the presence of sensor fault and output quantization. Simulation results demonstrate the effectiveness of the proposed algorithms.

Optimizing platoon safety through key node selection in pinning control strategy

The advent of Connected and Automated Vehicles (CAVs) and vehicular platooning has ignited high expectations for improving the safety performance of future transportation systems. Present control strategies for CAV platoons primarily concentrate on regulating each vehicle within the platoon. Although theoretically equipped to optimize a variety of performance metrics, this method is heavily dependent on communication and computational resources, which may lead to exorbitant costs. This study proposes a pinning control strategy that focuses on the selection of pivotal nodes, thereby facilitating the optimization of safety indexes for the entire platoon through the control of a select group of vehicles. The strategy encompasses two critical aspects: the identification of key control nodes and the application of node-based control. Initially, a feature matrix that includes both the intrinsic dynamics of the vehicles and the dynamics relative to other vehicles is developed. Spectral clustering is then utilized to identify these pivotal nodes. Subsequently, specialized control mechanisms for these nodes are devised, based on Proportional-Integral-Derivative (PID) controllers, with the objective of improving platoon safety. The efficacy of this strategy is corroborated through numerical simulations. To assess the safety performance, four categories of Surrogate Safety Measures (SSMs), which consider distance and acceleration, are applied. The findings confirm that the pinning control strategy significantly enhances performance across various SSMs, considerably reducing the risk of collisions during platoon operations. Moreover, it improves operational efficiency and platoon stability, establishing its value as an effective method for safety enhancement.

Enhancing vehicular platoon stability in the presence of communication Cyberattacks: A reliable longitudinal cooperative control strategy

This study proposes a reliable longitudinal distributed control strategy for connected and automated vehicles (CAVs) in the presence of communication cyberattacks. The proposed strategy is designed to utilize dependable measurements from onboard sensors to evaluate the reliability of vehicle-to-vehicle (V2V) information and enhance the platoon string stability in an integrated manner. Specifically, this paper proposes a real-time reliability evaluation mechanism for the ego vehicle based on sensing and communication information from multiple predecessors, employing an upper-tailed chi-squared test. The mechanism is then incorporated into a distributed multi-predecessor linear feedback controller to adaptively weigh the preceding vehicles’ information, ensuring robustness against cyberattacks and maintaining the string stability of the vehicular platoon. To better understand the whole framework, sufficient conditions of true string stability and pseudo string stability are theoretically derived, unveiling the disturbance amplification jointly impacted by measurement accuracy of onboard sensors, cyberattack severity in V2V communication, and control parameters. Numerical experiments are conducted to validate the controller across various types of communication cyberattacks. The results suggest that the proposed control strategy can significantly alleviate the impact of cyberattacks and simultaneously dampen traffic oscillations effectively.

Research on collaborative adaptive cruise control based on MPC and improved spacing policy

A Cooperative Adaptive Cruise Control (CACC) algorithm based on Model Predictive Control (MPC) and an improved spacing policy is proposed in this study to address the current issues of low road utilization and inadequate dynamic regulation during platoon driving. First and foremost, the state of the leader vehicle and the minimum safe following distance are incorporated into the spacing policy to create an enhanced constant time headway (CTH) spacing policy. Secondly, following the MPC principle, the optimization problem of vehicle platoon is converted into a constrained quadratic programming problem that fulfills the requirements of driving safety, following distance, and ride comfort in a platoon. Finally, six-homogeneous-vehicle platoon is constructed for simulation verification, and the results show that the designed algorithm can not only ensure the string stability of platoon, but also effectively improve the road utilization rate. And in the vehicle of platoon cut-in/cut-out conditions, CACC is proven to have good ability of dynamically adjusting and restoring platoon stability.

Research on Intelligent Platoon Formation Control Based on Kalman Filtering and Model Predictive Control

Recently, the intelligent platoon has attracted a lot of attention in both academic and industrial research. For each intelligent platoon, all vehicles drive sequentially in a line, which helps to improve fuel economy and road capacity. Consider two adjacent vehicles in the intelligent platoon, and there is no mechanical boundary between them. However, an intelligent platoon may still suffer from the issues of poor vehicle-following performance during the process of vehicle-following, especially when it obtains its own position and other parameters inaccurately. To address this issue, this paper proposes a model predictive control method based on an improved version of Kalman filtering, aiming to enhance the anti-interference capacity of intelligent platoons in scenarios where the following vehicles have acquired inaccurate parameters resulting from environmental disturbances and sensor noise. Firstly, this paper establishes a three-degree-of-freedom single-track model for the following vehicle, conducting dynamic analysis of its lateral, longitudinal, and yaw movements. Then, this paper develops a horizontal and longitudinal formation driving control frame of the intelligent vehicle platoon. Moreover, this paper also has employed Kalman filtering for interference reduction of state parameters and designs an improved model predictive controller. The proposed scheme is verified and evaluated through a joint simulation within Carsim and MATLAB/Simulink, and the results demonstrate that the longitudinal following error is reduced by 37% and the lateral following error is reduced by 51% compared to traditional algorithms, effectively improving the stability of intelligent vehicle platoons during following driving.

Detection and mitigation of vehicle platooning disruption attacks

In response to the escalating challenges posed by traffic bottlenecks, accidents, and intersection delays, the deployment of platooning mechanisms emerges as an imperative remedy. This investigation revolves around a pivotal scenario wherein a closely-knit platoon of cooperative vehicles approaches an intersection. Orchestrated by a lead vehicle, this convoy navigates the traffic light to expedite the journey of its followers towards their respective destinations. However, given that the size of the platoon can be increased, it will become difficult for the leader to manage it smoothly. Therefore, dividing the platoon into small groups led by co-leaders who deal directly with the leader is considered an ideal solution to speed up and facilitate the process of maintaining platoon stability. In this paper, we propose a Cooperative Adaptive Platooning Control Algorithm (CAPCA) for the hybrid communication topology in platooning. In fact, CAPCA aims to achieve stability in the platoon by distributing tasks in a parallel manner to mini-platoons. Moreover, inherent complexities arise as select members within the platoon strive to undermine its stability. Within this context, the research addresses the intricacies of Vehicle Platooning Disruption (VPD) attacks, a menacing phenomenon characterized by deliberate efforts to destabilize or seize control of a platoon. These attacks manifest through tactics such as false data injection (FDI) and replaying of control messages. In response, a robust and multifaceted countermeasure is conceptualized. The Vehicle Platooning Disruption Attacks Detection Protocol (VPD-ADP) takes center stage as a foundational component. By identifying instability within the platoon's dynamics model, VPD-ADP lays the essential groundwork for mitigating the repercussions of FDI and replay attacks. Employing advanced stochastic time series analysis, the impact of VPD attacks is scrutinized via anomalies in the Cartesian coordinates of vehicles deviations from the trajectory anticipated by the platoon. Moreover, the study introduces the Reputation-based Reliable Mitigation Protocol (RRMP), a pioneering approach that leverages collaborative data gleaned from neighboring vehicles. RRMP is devised to assess the veracity of received messages and gauge their reliability in real-time. Through extensive simulations and experiments, the proposed approach's effectiveness in fortifying the resilience of vehicle platooning systems against an array of disruption attacks is convincingly demonstrated.

Exponential mean‐square string stability of vehicular platoon with stochastic disturbance and time delay

AbstractPlatooning is an effective way to reduce air resistance and fuel consumption in vehicular transportation. However, stochastically generated disturbances can significantly impact the string stability of platoons. This article proposes a novel control law, based on sliding mode control and leader‐predecessor communications, designed to improve the exponential mean‐square string stability of platoons with Ito‐type stochastic disturbances that consider friction force. Specifically, our approach employs a third‐order nonlinear dynamic model to capture the relevant spatiotemporal correlations present in vehicle platoons. The proposed longitudinal control strategy effectively stabilizes the platoons with time delay and was verified through simulation experimentation. In this study, the stability of sliding mode motion is thoroughly investigated by means of sub‐reachable and practical stability analysis with sliding mode control. The findings of this study provide a theoretical foundation for further research on vehicle platoons with increasingly complicated interference and time delays. Overall, our results demonstrate that our approach can achieve significant improvements in both fuel economy and exhaust emissions while maintaining high levels of string stability, further contributing to the development of efficient and sustainable transportation systems.

Exploring Safety-Stability Tradeoffs in Cooperative CAV Platoon Controls with Bidirectional Impacts.

Advanced sensing technologies and communication capabilities of Connected and Autonomous Vehicles (CAVs) empower them to capture the dynamics of surrounding vehicles, including speeds and positions of those behind, enabling judicious responsive maneuvers. The acquired dynamics information of vehicles spurred the development of various cooperative platoon controls, particularly designed to enhance platoon stability with reduced spacing for reliable roadway capacity increase. These controls leverage abundant information transmitted through various communication topologies. Despite these advancements, the impact of different vehicle dynamics information on platoon safety remains underexplored, as current research predominantly focuses on stability analysis. This knowledge gap highlights the critical need for further investigation into how diverse vehicle dynamics information influences platoon safety. To address this gap, this research introduces a novel framework based on the concept of phase shift, aiming to scrutinize the tradeoffs between the safety and stability of CAV platoons formed upon bidirectional information flow topology. Our investigation focuses on platoon controls built upon bidirectional information flow topologies using diverse dynamics information of vehicles. Our research findings emphasize that the integration of various types of information into CAV platoon controls does not universally yield benefits. Specifically, incorporating spacing information can enhance both platoon safety and string stability. In contrast, velocity difference information can improve either safety or string stability, but not both simultaneously. These findings offer valuable insights into the formulation of CAV platoon control principles built upon diverse communication topologies. This research contributes a nuanced understanding of the intricate interplay between safety and stability in CAV platoons, emphasizing the importance of information dynamics in shaping effective control strategies.

A cooperative interaction strategy for vehicle platoons to obtain merging gaps in connected environments

Vehicle platoons can significantly improve traffic throughput and reduce fuel consumption and emissions. In the formation of platoons, it is crucial to generate safe merging gaps. This process requires appropriate cooperative management and control strategies. This study proposes a cooperative interaction strategy for vehicle platoons, including a communication management system and vehicle control strategies. These strategies can reduce velocity fluctuation in the process of gap generation and improve traffic performance. First, a communication management system within a platoon was developed, according to the standard communication protocol (SAE J2735), ensuring that external vehicles can join the platoon efficiently and orderly. Next, a cooperative adaptive cruise control (CACC) system was designed, which adopts feedforward and feedback control. Furthermore, the influence of increasing gaps on the stability of the platoon was considered. A cooperative control strategy for a virtual guiding vehicle (VGV) was introduced to switch the following target and linearly change the distance input of the controller. In this way, the downstream vehicles were guided to smoothly generate a safe merging gap, which can reduce speed fluctuation, and ensure the stability and safety of the platoon. Finally, the entire process of interaction in a vehicle platoon was tested in a simulation environment. The results showed that, compared with the parameter adaptive control strategy, the maximum velocity overshoot of the platoon vehicles was reduced by 56%, recovery stabilization time was reduced by 47%, and vehicle jitter was reduced by 43%. The driving security and platoon stability were both within the control boundaries set for evaluation.

Communication Resource-Efficient Vehicle Platooning Control With Various Spacing Policies

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the inter-vehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

A detection and rerouting mechanism for platoon control of non‐linear autonomous vehicles under denial of service attacks

AbstractThis paper presents a novel detection and rerouting mechanism for distributed adaptive platoon control of non‐linear autonomous connected vehicles under denial of service (DoS) attacks. DoS attacks can cause delays or losses of data packets due to blocked communication channels, leading to reducing platoon performance or even collisions among vehicles. To tackle this issue, the proposed mechanism detects and reroutes communication topology depending on the real‐time topology and the number of link failures. Real‐time detection divides the scenario of DoS attacks into three parts. According to the different scenarios, rerouting mechanisms will be utilized. A controller adapted to real‐time variable communication topology is also designed in this scheme. The adjacency matrix of the real‐time communication topology generated by the rerouting mechanism is used to update the controller so that the platoon can remain in a stable state without being affected by DoS attacks. In addition, the sliding mode controller and the observer are designed by solving linear matrix inequalities, and the platoon stability and internal stability are proven. Numerical simulation studies demonstrate that the proposed mechanism and control design can reduce the vehicle state estimate error and platoon‐tracking error to ideal states under DoS attacks. The proposed method solves the problem that the existing methods have not considered the number of link failures and the inability to restore communication when the communication topology is paralyzed.