Information Flow Topology Research Articles

Cooperative Spacing Control of Vehicle Platoon via Relative Output Feedback Considering Analog Fading Networks

ABSTRACTThe influence of analog fading channels on platoon control performance is studied via relative output feedback. The main goal is to determine the existence of a distributed output feedback controller capable of achieving mean square stability (MSS) for the underlying vehicle platoon systems over analog fading channels. First, the conditions, closely associated with the statistical characteristics of fading channels, for achieving platoon MSS are derived for three cases: undirected information flow (UIF) topology with identical fading channels, balanced directed information flow (BDIF) topology with identical fading channels, and general information flow topology (IFT) with nonidentical fading channels, respectively. These conditions explicitly reveal how the statistical characteristics of fading channels and IFT jointly affect vehicular stability. Second, in order to mitigate the impact of fading channels on platoon MSS, some feasible dynamic observer‐based controllers by using the relative output feedback, are proposed for each one of the former two situations by solving the corresponding modified Riccati inequalities (MRIs); and in the last situation, by employing edge Laplacian to model the vehicle platoon dynamics, a sufficient condition based on the solution of an LMI, and a feasible state‐based controller based on the solution of an MRI, are provided. Finally, simulations are carried out to compare three distinct fading channels, namely the Nakagami channel, Rician channel, and Rayleigh channel. The outcomes substantiate the superior and effective performance of the implemented control methods in guaranteeing the platoon MSS.

Reducing Time Headway for Cooperative Vehicle Following in Platoon via Information Flow Topology

Reducing Time Headway for Cooperative Vehicle Following in Platoon via Information Flow Topology

Distributed vehicular platoon control considering communication delays and packet dropouts

The influence of both inter-vehicular communication delays and packet dropouts on platoon control performance is studied. First, the conditions for achieving platoon mean square stability (MSS) are derived for three cases: undirected information flow (UIF) topology with time delays and identical packet losses, general information flow topology (IFT) with time delays and identical packet losses, and general IFT with time delays and non-identical packet losses. These conditions explicitly reveal how packet dropout rates, time delays, and IFT jointly affect vehicular stability. Second, in order to mitigate the impact of time delays and packet dropouts on platoon MSS, some feasible controllers are proposed for each one of the three cases by solving the corresponding modified Riccati inequalities (MRIs). In comparison with existing results, the provided conditions are easily determinable, and the offered controllers are simple to implement, with low computational complexity. Furthermore, they expand upon existing research findings. Finally, simulations are conducted to compare different time delays and packet loss rates, which validate the theoretical discoveries, also demonstrate the robustness and feasibility of the proposed methods using a platoon of passenger cars and realistic vehicle dynamics.

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.

Modeling and analysis of heterogeneous traffic flow considering dynamic information flow topology and driving behavioral characteristics

Connected vehicles (CVs) have demonstrated significant potential for addressing traffic issues. This paper presents a mathematical framework for stochastic heterogeneous traffic flow, integrating regular vehicles (RVs) and CVs, considering stochasticity, driver’s dynamic time headway (DTH) characteristics, and the information flow topology (IFT) of CVs. We develop a novel car-following model (CFM) for RVs, accounting for both driver’s stochasticity and DTH characteristics. Furthermore, we propose a dynamic model for CVs by integrating connected assisted driving strategies (CADS) into the RVs’ model, which includes a dynamic information flow topology (DIFT) based on the time headway (TH) between vehicles within the communication range. We derive second-order exponential stability conditions for both RVs and CVs by employing the Lyapunov stochastic stability theory. We investigate the impact of driver stochasticity, DTH characteristics, and CADS on heterogeneous traffic flow characteristics through extensive numerical experiments. Model calibration results indicate that, in comparison to the state-of-the-art model, the proposed model exhibits superior prediction accuracy, achieving a 9.09% improvement at the group-driver level and a 10.47% improvement at the individual-driver level. Theoretical and numerical experimental results demonstrate that CVs with the proposed assisted driving strategy effectively mitigate traffic oscillations, and traffic flow stability improves as the CV penetration rate increases. Moreover, CVs can efficiently suppress stochasticity in traffic flow, with the strength of traffic fluctuations decreasing as the CV penetration rate grows. Different CV spatial distributions result in different propagation strengths of disturbances in traffic flow, adhering to a specific dual Gaussian distribution. Under various conditions, the average decline rates of speed fluctuations and energy consumption for traffic with the increasing CV penetration rate are 20%–50% and 10%–30%, respectively.

Platoon Control of Connected Vehicles from a Networked Control Perspective: Literature Review, Component Modeling, and Controller Synthesis

The platooning of connected and automated vehicles has the potential to significantly benefit the road traffic, including enhancing highway safety, improving traffic capacity, and reducing fuel consumption. This paper presents a four-component analysis framework for platoon systems from a networked control perspective, including a literature review by network awareness, unified models of key components, and two application cases for controller synthesis. The networked control perspective naturally decomposes a platoon into four interrelated components, namely, 1) node dynamics (ND), 2) information flow topology (IFT), 3) formation geometry (FG), and 4) distributed controller (DC). The existing literature is categorized under this framework and analyzed according to the component features. The unified mathematical models are derived for platoons with linear dynamics and distributed controllers. As a case study, a distributed controller synthesis method is introduced for homogeneous platoons, which guarantees the internal stability in the presence of a broad class of topologies with/without uniform time-delays. The effectiveness is demonstrated by numerical simulations.

A Stochastic Binary Vertex-Triggering Resetting Algorithm for Global Synchronization of Pulse-Coupled Oscillators

In this paper, we propose a novel stochastic binary resetting algorithm for networks of pulse-coupled oscillators (or, simply, agents) to reach global synchronization. The algorithm is simple to state: Every agent in a network oscillates at a common frequency. Upon completing an oscillation, an agent generates a Bernoulli random variable to decide whether it sends pulses to all of its out-neighbours or it stays quiet. Upon receiving a pulse, an agent resets its state by following a binary phase update rule. We show that such an algorithm can guarantee <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">global</i> synchronization of the agents almost surely as long as the underlying information flow topology is a rooted directed graph. The proof of the result relies on the use of a stochastic hybrid dynamical system approach. Toward the end of the paper, we present numerical demonstrations for the validity of the result and, also, numerical studies about the units of time needed to reach synchronization for networks with various information flow topologies.

On the assessment of the dynamic platoon and information flow topology on mixed traffic flow under connected environment

It has been well documented that the mixed traffic flow of human-driven vehicles (HDVs) and connected and automated vehicles (CAVs) causes an unsound communication environment and weakens the beneficial effect of CAVs. However, the communication heterogeneity in the mixed traffic, which leads to incomplete information flow topology (IFT) and further affects the processes of vehicle control and platoon operation, did not receive its deserved attention. In contrast to previous research related to the IFT and platoons in static size, this study introduced the multi-anticipation and dynamic platoons into a more complex mixture of CAVs and HDVs and jointly considered the mode transition and driver uncertainties, e.g., estimation error and driving compliance. Specifically, we proposed multi-class generic controls to represent the basic longitudinal maneuver for each type of vehicle and developed customized car-following dynamics for each controller. In order to better adapt to the communication heterogeneity in the mixed traffic, we defined a novel controller for CAVs, namely mixed AV-CAV vehicle (MACV) controller and developed the corresponding control algorithm, namely AV-CAV integrated control (ACIC) with multi-source information from both sensors system and inter-vehicle communication. Besides, another important point worth considering in mixed traffic is the spatial distribution of CAVs in platoons. As such, three platoon policies, i.e., the cross policy, the continuum policy, and the random policy, were investigated. To our best knowledge, this is a new attempt to discuss the impact of platoon policies on mixed traffic, with a combination of different IFTs. Finally, multiple traffic flow characteristics, covering robustness, efficiency, safety, and emission, were assessed by calculating their corresponding surrogate measures. Results showed that the proposal of MACV controller and ACIC was expected to efficiently prevent the deleterious degradation from the CAV controller to AV controller and construct a more stable transition for changes in vehicle controls. Furthermore, a high proportion of communicable vehicles could significantly reduce the heterogeneity of mixed traffic and improve traffic flow characteristics. Besides, this study demonstrated the outstanding performance of multi-anticipative IFTs compared to the single-anticipative IFT and revealed the advantage of cross policy in traffic robustness and safety. These findings can help provide feasible solutions for IFTs, platoon operation, and vehicle control in the mixed traffic flow and identify their respective benefits in terms of traffic flow characteristics.

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.

Human Driving Centered Gain Scheduling Control of Mixed Platoons

Platooning has the potential to significantly improve traffic flow, safety, and fuel consumption. In the foreseeable future, traffic will still be composed mainly of human-driven vehicles (HDVs). Thus, the importance of exploring mixed platoons consisting of automated vehicles (AVs) and HDVs. Mixed platoons control is challenging since HDVs incorporate major uncertainty and stochastic nature. In this paper, human driving stochastic behavior was analyzed. The findings of this analysis were incorporated in all aspects of controller development – modeling, estimation, and controller synthesis. An algorithm to find an optimal controller that attenuates the effect of HDVs stochasticity while keeping predefined safety constraints was developed. Using this algorithm, two <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 are suggested: a robust controller and a gain-scheduling (GS) controller. The controllers were simulated using an information flow topology (IFT) that was suited for mixed-platoons. Results show that both controllers attenuates HDVs stochasticity. Compared to the robust controller, the GS controller improves performance mainly at high velocities.

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%.

Impacts of Information Flow Topology on Traffic Dynamics of CAV-MV Heterogeneous Flow

With the development of Connected Autonomous Vehicle (CAV) technology, different information flow topologies (IFTs) have been applied to CAV Ad Hoc Networks. Firstly, from the perspective of the controller, a general model is proposed to directly reflect the actual communication effect on the controller instead of simply abstracting it into the optimal time interval, which is more feasible. Secondly, linear stability analysis is carried out based on the general model where different time delays are considered, and stability criterion is obtained for subsequent analysis. Finally, we compare the three main IFTs through numerical simulations and analyze the difference in stability region, robustness, traffic safety, and Eco-driving between platoon Cooperative Adaptive Cruise Control (CACC) controllers based on different IFTs. It is found that adopting CACCs can notably improve the traffic capacity and traffic safety relative to Manual Vehicle (MV) no matter what IFT is adopted. As for the difference between the three IFTs, predecessor-leader following (PLF) and multiple-predecessor-leader following (MPLF) are significantly superior to predecessor following (PF), while the choice between PLF and MPLF depends on the communication bandwidth. With higher communication bandwidth or fewer communication vehicles, MPLF will be a better option; on the contrary, PLF is more suitable.

Distributed Finite-Time Fault-Tolerant Control for Heterogeneous Vehicular Platoon With Saturation

This paper investigates the distributed fault-tolerant control problem for the heterogeneous vehicular platoon system (HVPS) suffering from actuator faults, saturation, and external disturbances. Firstly, an exponential spacing policy is developed to tackle the string stability (SS) and traffic flow stability issues when the actuator faults occur. Then, a nonlinear observer is developed to estimate the saturation approximation error, bias fault, and external disturbances. Moreover, to achieve the SS of the whole system in finite-time and fault tolerance ability, a distributed adaptive fault-tolerant control scheme based on bidirectional-leader information flow topology is proposed. Adaptive estimation laws are also involved to estimate and update the unknown parameters, in which the effect of actuator saturation can be compensated. Finally, the SS in finite-time and traffic flow stability of the closed-loop system are proved, respectively. Experiment results and comparisons demonstrate the feasibly and advantages of the method.

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.

Cooperative Spacing Sampled Control of Vehicle Platoon Considering Undirected Topology and Analog Fading Networks

The work on this paper studies the combined effect of vehicle dynamics, sampling period and the quality of inter-vehicle sensing and communication on the performance of platoon control. First, we induce the sampled control protocol from continuous–time linear consensus protocol by employing zero–order hold circuit and periodic sampling technology, then by virtue of the obtained sampled control protocol, the continuous–time platoon system is equivalently transformed into a discrete–time system. Second, for the inter–vehicle communication with ideal channel and under undirected information flow topology (UIFT), the stability thresholds of control gains are explicitly established by solving a discrete–time simultaneous stabilization problem, bilinear transformation and the Routh-Hurwitz stability criterion. Meanwhile, to ensure the fastest asymptotic stability of the platoon dynamics, we propose an optimal asymptotic convergence factor and a correspondingly optimal sampled control protocol. Third, For the inter–vehicle communication with identical fading networks and under UIFT, through solving a modified Riccati inequality, we provide a sampled control protocol depending not only on information flow topology (IFT) and sampling period, but also on the statistics of the inter–vehicle communication channel. Besides, employing Lyapunov inequality in probability theory, we show a necessary condition for the sampled control protocol ensuring the platoon dynamics mean square stable. Finally, simulations are performed to demonstrate the theory’s discoveries.

Data partitioning and scheduling schemes for federated platoon-based vehicular cloud

The organization of vehicles into platoons is very promising due to its contributions to intelligent transportation systems, and the reduction in traffic congestion and fuel consumption. As the powerful processing units and other resources embedded in vehicles may not be fully utilized during the entire travel period of vehicular platoons, we claim that the vehicles can collaborate as a single unit to form a federated platoon-based vehicular cloud to meet the high demand for computing resources and services in vehicular environments. In order to make advancements in the deployment of federated platoon-based vehicular cloud, data partitioning and scheduling schemes that distribute data chunks of large and divisible application data among platoon vehicles are proposed considering the characteristics of vehicular resources, network parameters, and the position of vehicles in the platoon. The data partitioning and scheduling schemes, which are modeled based on the different information flow topologies of vehicular platoon, consist of the Bi-Directional Recursive (BD-R), Bi-Directional Interlaced (BD-I), Bi-Directional Lead Recursive (BDL-R), Bi-Directional Lead Interlaced (BDL-I), Bi-Directional Lead Aggregate Recursive (BDLA-R) and the Bi-Directional Lead Aggregate Interlaced (BDLA-I). Performance analysis carried out through realistic simulations showed that while the BDL-R and BDL-I schemes have the best performance in terms of task execution time, the other schemes have the advantage of enforcing priority in unprocessed data transmission and dependency in the aggregation of processed data chunks by each platoon member. Analysis of the impact of the proposed data partitioning and scheduling schemes on platoon string stability will be examined in future studies.

Stability and capacity for heterogeneous traffic flow mixed with vehicles in multiple controls

Cooperative adaptive cruise control (CACC) is regarded as a promising approach to improve traffic stability and capacity by operating vehicle-to-vehicle (V2V) communication. However, the beneficial effect of CACC vehicles is greatly reduced due to the influence of manually driven vehicles (MDVs) in the heterogeneous traffic flow, in which the degradation of CACC vehicles is a considerable problem. One proposed solution is to install communication devices for MDVs, called IMDVs, to propagate information to CACC vehicles and prevent the degradation. This study analyzed the traffic flow configuration by introducing IMDVs and considering multiple traffic flow operations, e.g. vehicle degradation and platoon formation. Then, multiple factors, including market penetration rate, platoon length, and information flow topology, were taken into consideration in the theoretical modelling of linear stability and fundamental diagram. Finally, we verified the high accuracy of theoretical analysis by numerical experiments and gave some reasonable recommendations for traffic management.

Multi-Objective Asymmetric Sliding Mode Control of Connected Autonomous Vehicles

The platoon of connected autonomous vehicles plays an essential role in future intelligent transportation. It can improve traffic efficiency and release traffic congestion. However, there are lots of existing challenging problems of the control of connected autonomous vehicles, such as the negative impact caused by wireless communication and disturbance. To solve these challenges, a multi-objective asymmetric sliding mode control strategy is proposed in this paper. Firstly, the asymmetric degree is introduced in the topological matrix. Then, a sliding mode controller is designed targeting platoon’s tracking performance. Moreover, Lyapunov analysis are used via Riccati inequality to find the controller’s gains and guarantee internal stability and Input-to-output string stability. Finally, a non-dominated sorting genetic algorithm is utilized to find the Pareto optimal asymmetric degree regarding the overall performance of the platoon, including tracking index, fuel consumption, and acceleration standard deviation. Four different information flow topologies, including a random topology are studied. The results indicate that the proposed asymmetric sliding mode controller can ensure platoon’s stability while improving its performance. The tracking ability is improved by 54.61% and 75.17%, fuel economy is improved by 0.78% and 6.34% under the Urban Road and Highway Case Study, respectively.

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.

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.