Platoon Control Research Articles

Integrated Localization and Planning for Cruise Control of UGV Platoons in Infrastructure-Free Environments

This paper investigates the cruise control problem of unmanned ground vehicle (UGV) platoons from the implementation perspective. Unlike most existing works related to platoon cruise control which rely on positioning infrastructures such as lane markings, roadside units, and global navigation satellite systems (GNSS), this paper explores a new problem: platoon cruise control in environments without positioning infrastructures. The introduction of this constraint disables most existing cruise control approaches. To address this problem, an integrated localization and planning framework is proposed, which is composed of three modular algorithms. Firstly, to localize multiple vehicles in a common coordinate system, a collaborative localization algorithm is developed through matching local perceptions of different vehicles. Secondly, to maintain the desired platoon configuration, the historical trajectory of the preceding vehicle is reconstructed, based on which the target state is planned for the following vehicle. Finally, a virtual controller based algorithm is designed to generate feasible trajectories for the following vehicle in real time. The proposed framework has two salient features. Firstly, it does not depend on positioning infrastructures and does not introduce additional positioning sensors, such as GNSS/INS modules, ultra-wideband (UWB) devices, magnetic meters and so on, as long as each vehicle is equipped with a perception sensor (Lidar, radar or camera), which however is essential equipment for nowaday autonomous systems. Secondly, the proposed framework does not depend on direct observations between vehicles to achieve relative localization, making it applicable in non-line-of-sight (non-LOS) situations. Real-world experiments have been conducted to validate the effectiveness, robustness and practicality of the proposed framework.

Data-Mechanism Adaptive Switched Predictive Control for Heterogeneous Platoons With Wireless Communication Interruption

Benefiting from the advancement of intelligent transportation systems (ITSs), intelligent connected vehicles (ICVs) are ushering in a once-in-a-generation development opportunity. Considering the widespread presence of heterogeneous vehicles with disturbances and uncertain dynamics in actual platoon scenarios as well as the multimodel switching produced by unavoidable interruptions in the communication process, this paper proposes a data–mechanism adaptive switched predictive (DASP) control strategy. The characteristics of the mechanism model are mapped based on state data to more accurately describe the system’s dynamic characteristics and improve the interpretability of variables. The introduction of Givens rotations and switching criteria enables online adaptive switching of the controller. A robustness analysis of heterogeneous platoon switching control under bounded disturbance is presented, and sufficient conditions for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal{L}_{2}$</tex-math> </inline-formula> string stability are provided. Finally, CarSim simulations and real-time bench experiments are reported to demonstrate the effectiveness of the DASP algorithm for heterogeneous multivehicle regulation with communication interruptions.

Fast Distributed Platooning of Connected Vehicular Systems With Inaccurate Velocity Measurement

Fast and smooth driving is a preferable consideration in platooning algorithm development for intelligent autonomous vehicular systems. It can improve traffic efficiency while guaranteeing passenger comfort. To this end, this work investigates the fast distributed platooning problem of connected vehicular systems. Taking the inaccurate velocity measurement into consideration, an extended state observer (ESO) based on a fractional order faster nonsingular terminal sliding mode (FNTSM) is proposed for velocity and disturbance estimation simultaneously. An FNTSM control algorithm based on the double power reaching law is developed to reach fast platooning while guaranteeing string stability of the connected vehicular systems regardless of zero or nonzero initial spacing error conditions. The salient features of the proposed platoon controller are that system convergence can be achieved in finite time and the time-varying external disturbances can be estimated accurately. Finally, simulation and experiment studies are conducted to demonstrate the effectiveness and efficiency of the proposed control algorithm.

Driving safety zone model oriented motion planning framework for autonomous truck platooning

A driving-safety-zone-model-oriented motion planning framework (DSZMF) is proposed for autonomous platoons in heterogeneous driving environments with complex driving behaviors and interactions between human-driven and autonomous vehicles. As an extension of the responsibility-sensitive-safety (RSS) model, the driving safety zone model ensures that autonomous truck platoons adhere to explicit and implicit traffic rules as rational traffic participants.It consists of three zones created by safe distances and artificial potential field (APF), namely the restricted zone, the coordinated zone, and pre-cautionary zone. The Rational Traffic Participant (RTP) module is created by using a Finite State Machine (FSM) to provide an optimized platooning behavioral strategy based on the dynamic states of surrounding vehicles. Furthermore, the distributed model predictive controllers are utilized for motion planning, while the H infinity controller is developed to maintain the string stability of the autonomous platoon. The proposed DSZMF generates behavioral decisions by thoroughly considering the driving safety zone model, string stability, and multiple vehicle dynamics constraints. Finally, three critical scenarios are co-simulated for case studies, and the simulation results demonstrate that the DSZMF improves the safe time integration rate over the existing MCF by 18.9%, 11.1%, and 11.6% in three scenarios, respectively. In addition, DSZMF increases the minimum longitudinal and lateral Time to Collision (TTC) values to reduce collision risks. The case studies validate the efficacy of the proposed method for safety assurance and collaborative control of the autonomous platoon.

Urban Platooning Combined with Dynamic Traffic Lights

Platooning is generally known as a control method for driving a group of connected and automated vehicles in motorway context. Nevertheless, platoon control might also work on urban roads. One possible strategy to increase overall road traffic performance and to reduce congestion in urban traffic networks is to combine platooning with traffic signal control at intersections. The traffic flow can be maximized with coordinated scheduling of traffic signals together with platooning activities, resulting in decreased travel times and fuel consumption. This paper investigates several aspects of this combined control, such as the procedures for coordination and communication between platooning vehicles and traffic signals. Efficient algorithms are suggested to optimize platoon formation and dissolution at junctions and to change traffic signal phases depending on platoon arrival and departure times. The proposed solutions have been tested and verified with SUMO, a high-fidelity microscopic traffic simulator.

Distributed event-triggered adaptive robust platoon control of connected vehicles with uncertainties subject to invalid communication

Distributed event-triggered adaptive robust platoon control of connected vehicles with uncertainties subject to invalid communication

Constrained distributed consensus control of homogeneous vehicle platoons with bidirectional communication

Vehicle platooning is deemed a promising solution to improve traffic safety, reduce fuel consumption and increase traffic throughput and road capacity. Road throughput can be increased by driving at small inter-vehicle distances. Adjusting the spacing with both the preceding and the succeeding vehicles using bidirectional communication can potentially improve the platoon cohesiveness and is crucial when considering the synchronized merging scenario. In this paper, a distributed consensus controller is presented which relies on bidirectional platoon communication. To take into account the constraints of the system state and input constraints are implemented using control barrier functions via linear quadratic programming. Along with the consensus-based controller synthesis, platoon stability proof and string stability analysis, effectiveness of the controller is verified in a simulation study.

Behavioral Decision-Making Approach for Vehicle Platoon Control: Two Noncooperative Game Models

Game theory has been extensively studied in recent years for its potential benefits on solving interactions between autonomous vehicles in platoon control. In this paper, we propose two behavioral decision-making approach based on non-cooperative game theory with both the complete information and incomplete information for cooperative vehicle platoon systems. The non-cooperative game payoff function takes the platooning performances of economy, comfort, safety, and further achieving self-driving functions into consideration. For the driving situations with incomplete information, a belief pool is constructed to represent the action probability for different behavioral types of vehicles, which will be updated by combining the driving intention identification with a Bayesian probability formula. With this, the stable strategies can be obtained for the two potentially conflicting parties, ensuring that neither of them has a motivation to change their driving behavior. Finally, the simulation results demonstrate that with the proposed behavioral decision-making approaches with complete information, the cooperative platoon performance can be markedly improved; with incomplete information, the platoon can determine the behavioral types of conflicting vehicles and complete collaborative decision-making approaches for solving not only the simple road-rights conflicting problems, but also for the extended vehicle platoon driving scenarios in a more complex transportation system.

Distributed Control of a Vehicular Platoon Using Event-Triggered Communication Strategy Based on State Estimation

Distributed Control of a Vehicular Platoon Using Event-Triggered Communication Strategy Based on State Estimation

A futuristic green service computing approach for smart city: A fog layered intelligent service management model for smart transport system

With the widespread adoption of technologies like the Internet of Things (IoT), context awareness, and decentralized computing at the edge of the network, service delivery in smart city parlance has been rapidly evolved. Management of Information and Communication Technologies (ICT) infrastructure for such dynamic environment at scale brings about new challenges. Existing fog layer resource management involves context-sharing and migration for real-time vertical and cross-vertical services. However, improper context migration might affect performance negatively. In this paper, the authors have envisioned improving the Quality of Service (QoS) of smart transportation while employing context-aware computing and Artificial Intelligence, which helps alleviate massive data transfers among Fog nodes and intelligent vehicles in real-time. The proposed Context-Aware Intelligent Transportation System (CAITS) manages the services of intelligent vehicles and manages the road traffic of traditional vehicles in an effective manner, with a three-layered learning model that accounts for on-vehicle, on-co-vehicle, and on-fog-and-vehicle learning by means of a platoon control algorithm as well as federated learning at the Fog level. Simulations are carried out on CloudSim simulator under different scenarios and the results demonstrate that the proposed scheme improves prediction efficacy of contexts at the Fog layer by approximately 8%–24% than existing models which in turn reflects in reduced service time and energy consumption of EVs and reduces the CO2 of environment.

DMPC-based string stable platoon control with robustness against communication delays

Communication delays are inevitable in vehicle platoons and may inhibit control performance. To address this issue, existing delay compensation strategies often resort to a greater time headway based on the delay upper bound, which compromises the benefits on traffic throughput. Moreover, it remains a major challenge to strictly ensure string stability with delays for distributed model predictive control (DMPC)-based controller. This paper presents a DMPC method for the cooperation of heterogeneous platoons subject to time-varying communication delays and greatly improves robustness against communication delays by improving the DMPC mechanism. A third-order heterogeneous vehicle dynamics model is integrated into the proposed method to improve control precision when implemented in the field. A synchronization mechanism is designed and the constant spacing policy is applied, which eliminates the delay dependence of the time headway selection and may thus improve traffic throughput. By incorporating a dual-mode scheme, a robustness constraint and a string stability constraint in the optimization problem, feasibility, closed-loop stability, and string stability are theoretically proved. A sufficient condition on the controller parameters is derived to guarantee closed-loop stability under communication delays. Numerical simulations are conducted to demonstrate the effectiveness of the proposed delay-compensating DMPC controller. The results reveal that the proposed controller outperforms the traditional DMPC controller and delay-involved linear controller on string stability, tracking performance and desired spacing selection.

Event-triggered extended state observer based distributed control of nonlinear vehicle platoons

Event-triggered extended state observer based distributed control of nonlinear vehicle platoons

Platooning Control of Vehicular Systems by Using Sampled Positions

This letter studies the platooning control problem of vehicular systems, where the leader control input is non-zero. In contrast to the existing results with full knowledge of the vehicle state (i.e., position, velocity, and acceleration) for feedback, a new platoon control law is designed, which depends on the currently and most recently sampled positions only. To explore the input-to-state stability (ISS) of the resulting platoon control system, sufficient conditions are presented in the form of linear matrix inequalities (LMIs) by using appropriate Lyapunov functionals. Then a design criterion for the existence of the sampled-position-based controller is derived. Finally, an example illustrates the efficiency of the method.

Adaptive Fixed-Time Sliding Mode Control of Vehicular Platoons With Asymmetric Actuator Saturation

This paper investigates the problem of vehicular platoon control with asymmetric actuator saturation. First, an improved Gaussian error function (IGEF)-based approximation strategy is presented to replace saturation nonlinearity in a smooth way. Then, an adaptive fixed-time control algorithm via sliding mode control is proposed with which the individual vehicle stability and string stability can be guaranteed in a given time, and the settling time can be prescribed in advance as needed. Besides, a set of adaptation laws are introduced to deal with uncertain parameters and unknown disturbances. Finally, the effectiveness of the proposed control scheme is illustrated by numerical simulations.

An extendable maneuver management framework with fault‐tolerant mechanism for vehicle platoon control system in highway scenario

AbstractVehicle platoons can encounter many complex scenarios in practice that were not considered in the design, which reveals the need to add new maneuvers. Platoon control system will face the challenge of the lack of maneuver scalability in practical applications. To address this problem, this study introduces an extendable maneuver management framework with fault‐tolerant mechanism on the basis of the hierarchical architecture for the platoon control system. Maneuvers and roles are two dimensions, based on which the management strategies are decoupled. They enable each vehicle in the platoon to execute management strategies of various maneuvers and make it possible to expanding new behaviors into existing strategies. The fault‐tolerant mechanism is designed as a maneuver triggered by hardware failures to remain safe before taking over. Furthermore, three typical maneuvers are selected for case studies to illustrate the management strategies in this framework. Finally, a comprehensive simulation scenario integrating different maneuvers is designed and a real‐world implementation using micro‐vehicles is conducted. The results demonstrate that the proposed two‐dimensional framework could effectively address various maneuvers and satisfy the computational real‐time requirements.

Distributed MPC of vehicle platoons with guaranteed consensus and string stability

Control of vehicle platoon can effectively reduce the traffic accidents caused by fatigue driving and misoperation, reduce air resistance by eliminating the inter-vehicle gap which will effectively reduce fuel consumption and exhaust emissions. A hierarchical control scheme for vehicle platoons is proposed in this paper. Considering safety, consistency, and passengers’ comfort, a synchronous distributed model predictive controller is designed as an upper-level controller, in which a constraint guaranteeing string stability is introduced into the involved local optimization problem so as to guarantee that the inter-vehicle gap error gradually attenuates as it propagates downstream. A terminal equality constraint is added to guarantee asymptotic consensus of vehicle platoons. By constructing the vehicle inverse longitudinal dynamics model, a lower-level control scheme with feedforward and feedback controllers is designed to adjust the throttle angle and brake pressure of vehicles. A PID is used as the feedback controller to eliminate the influence of unmodeled dynamics and uncertainties. Finally, the performance of longitudinal tracking with the proposed control scheme is validated by joint simulations with PreScan, CarSim, and Simulink.

Joint Optimization of Platoon Control and Resource Scheduling in Cooperative Vehicle-Infrastructure System

Vehicle platooning technology is essential in achieving group consensus, on-road safety, and fuel-saving. Meanwhile, Vehicle-to-Infrastructure (V2I) communication significantly facilitates the development of connected vehicles. However, the coupled effects of the longitudinal vehicle's mobility, platoon control and V2I communication may result in a low reliable communication network between the platoon vehicle and the roadside unit, there is a tradeoff between the platoon control and communication reliability. In this paper, we investigate a bi-objective joint optimization problem where the first objective is to maximize the success probability of data transmission (communication reliability) and the second objective function is to minimize the traffic oscillation flow. The vehicle's mobility state of the platoon vehicle affects the channel capacity and transmission performance. In this context, we deeply explore the relationship between control signals and resource scheduling and theoretically deduce a closed-form expression of the optimal communication reliability objective. Through this closed expression, we transform the bi-objective model into a single objective MPC model by using <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\epsilon$</tex-math></inline-formula> -constraint method. We design an efficient algorithm for solving the joint optimization model and prove the convergence. To verify the effectiveness of the proposed method, we finally evaluate the spacing error, speed error, and resource scheduling of platooning vehicles through simulation experiments in two experimental scenarios. The results show that the proposed control-communication co-design can improve the platoon control performance while satisfying the high reliability of V2I communications.

Relay-Assisted Platooning in Wireless Networks: A Joint Communication and Control Approach

This paper addresses the problem of the joint design of the mobile communication system and the control scheme for enabling vehicle platooning applications. Vehicles communicate essential information for platooning control through multi-hop vehicle-to-vehicle (V2V) communications and are assisted in this task by Road Side Units (RSU), when available. While classical approaches, adopted in previous and current mobile systems, consider the application needs solely as requirements for the communication network, we advocate a bi-directional interaction of application and communication network. We first study the impact of different communication strategies on the application-level performance, namely the inter-vehicle distance in the platoon. Such schemes introduce a tradeoff between the packet delivery rate and the additional delay introduced by relaying. In order to assess the impact of both metrics, we start by developing a Markov model for the different communication links (inter-vehicle and vehicle-to-RSU). We then propose a cross-layer approach that adapts the application layer (platoon control parameters) to the observed Medium Access Control (MAC) layer performance. We demonstrate via simulations the benefit of the proposed relaying scheme, and that a joint design of application and communication systems is essential for enabling the integration of industrial applications in future generation networks.

Coordination of Mixed Platoons and Eco-Driving Strategy for a Signal-Free Intersection

This paper investigates the collaborative control of vehicular traffic for a signal-free intersection. The traffic under consideration is mixed with connected autonomous vehicles (CAVs) and human-piloted vehicles with advanced driver assistance systems (ADAS). The proposed collaborative control is of two levels. At the upper level, the objective is to minimize total delay via platoon control and dynamic priority control of conflicting movements. We formulate the platoon coordination of mixed traffic as a mixed-integer linear programming problem (MILP). This MILP determines whether adjacent vehicles will form a platoon and prioritize any two conflicting movements subject to lateral safety and rear-end safety constraints. At the lower level, we propose an eco-driving strategy to minimize the energy consumption by optimizing the speed profile of the platoon leading vehicles subject to the dynamic priority control from the upper level, i.e., the entry time to the merging zone. We deduce an analytical solution to the eco-driving problem using optimal control theory. Compared with existing benchmarks, such as the first-come-first-served policy, the proposed method outperforms the state-of-the-art controllers in reducing the total delay. Sensitivity analysis regarding the penetration rate of CAVs shows that substantial improvements can be achieved even at low to medium penetration rates of CAVs.

Resilient Distributed Event-Triggered Platooning Control of Connected Vehicles Under Denial-of-Service Attacks

The security control of a vehicle platoon depends on the network topology and communication quality. Denial of service (DoS) attacks force vehicle formations to destabilize by disrupting digital communications between vehicles. To this end, this paper develops a resilient distributed event-triggered security control strategy to resist the malicious impact of DoS attacks on connected vehicles. By designing a distributed event-triggered mechanism based on sampled data, the controller updating frequency is reduced, thereby promoting utilization rate of network resources. Since the end of the attack is not the sampling instant, this may prolong the duration of the attack. To overcome this problem, a switched sampled-data scheme is proposed to ensure that the control signal acts on the system immediately when the attack ends. Then, a switched system model with artificial delay is established to capture the sampling period, event triggering mechanism and DoS attack purpose. With the analysis methods of switched system and time-delay system, sufficient conditions are obtained to guarantee the same safe distance and speed between vehicles, so that the connected vehicle system can achieve the desired tracking effect. A co-design approach is given with respect to controller gains and triggering parameter. Finally, simulation and experimental studies are provided to demonstrate the effectiveness of the proposed security control method.