Collision avoidance command governor for multi‐vehicle unmanned systems

In this paper, we consider the problem of coordinating a collection of autonomous unmanned vehicles while guaranteeing collision avoidance. Each vehicle is regulated by a local controller that ensures stability and provides desired path tracking performance in the absence of constraints. The fulfillment of coordination tasks (e.g., collision avoidance) and local constraints (e.g., input saturation constraints) is achieved through a command governor (CG) strategy that, whenever necessary, modifies the nominal paths of the vehicles. First, a centralized CG approach is proposed and fully analyzed. Then, a more interesting distributed implementation requiring low communication rates is discussed. Both approaches make use of a receding horizon strategy and require the on‐line solution of mixed‐integer optimization programs. Finally, an example is given for illustration purposes. Copyright © 2013 John Wiley & Sons, Ltd.     

Event-triggered-based finite-time cooperative path following control for underactuated multiple marine surface vehicles

This paper develops an event-triggered-based finite-time cooperative path following (CPF) control scheme for underactuated marine surface vehicles (MSVs) with model parameter uncertainties and unknown ocean disturbances. First, a finite-time extended state observer (FTESO) is proposed, in which the FTESO can estimate the velocities and compound disturbances in finite time. Then, the finite-time LOS guidance law based on velocity estimation values is designed to obtain the desired surge velocity and the desired yaw rate. In order to realize the cooperative control of multiple paths in finite time, the cooperative control law for the path variable is designed. In addition, the relative threshold event-triggered control (ETC) mechanism is incorporated into the formation control algorithm, and an event-triggered-based finite-time CPF controller is designed, which not only effectively reduces the update frequency of controller and the mechanical loss of actuator but also improves the control performance of system. Furthermore, by using homogeneous method, Lyapunov theory, and finite-time stability theory, it is proved that under the proposed finite-time CPF control scheme, the formation errors can converge to a small neighborhood around origin in finite time. Finally, numerical simulation results illustrate the effectiveness of the proposed control scheme.     

Cooperative control of multiple surface vessels with discrete‐time periodic communications

This paper addresses the problem of cooperative path‐following of networked autonomous surface vessels with discrete‐time periodic communications. The objective is to steer a group of autonomous vehicles along given spatial paths, while holding a desired inter‐vehicle formation pattern. For a given class of marine vessels, we show how Lyapunov‐based techniques, graph theory, and results from networked control systems can be brought together to yield a decentralized control structure where the dynamics of the cooperating vessels and the constraints imposed by the topology of the inter‐vehicle communication network are explicitly taken into account. Cooperation is achieved by adjusting the speed of each vessel along its path according to information exchanged periodically on the positions of a subset of the other vessels, as determined by the communications topology adopted. The closed‐loop system that is obtained by putting together the path‐following and cooperation strategies takes an interconnected feedback form where both systems are input‐to‐state stable with respect to the outputs of each other. Using a small‐gain theorem, stability and convergence of the overall system are guaranteed for adequate choices of the controller gains. Copyright © 2011 John Wiley & Sons, Ltd.     

Predictive car-following scheme for improving traffic flows on urban road networks

Driving behavior is one of the main reasons that causes bottleneck on the freeway or restricts the capacity of signalized intersections. This paper proposes a car-following scheme in a model predictive control (MPC) framework to improve the traffic flow behavior, particularly in stopping and speeding up of individual vehicles in dense urban traffic under a connected vehicle (CV) environment. Using information received through vehicle-to-vehicle (V2V) communication, the scheme predicts the future states of the preceding vehicle and computes the control input by solving a constrained optimization problem considering a finite future horizon. The objective function is to minimize the weighted costs due to speed deviation, control input, and unsafe gaps. The scheme shares the planned driving information with the following vehicles so that they can make better cooperative driving decision. The proposed car-following scheme is simulated in a typical driving scenario with multiple vehicles in dense traffic that has to stop at red signals in multiple intersections. The speeding up or queue clearing and stopping characteristics of the traffic using the proposed scheme is compared with the existing car-following scheme through numerical simulation.     

Globally Stable Adaptive Dynamic Surface Control for Cooperative Path Following of Multiple Underactuated Autonomous Underwater Vehicles

The cooperative path following problem of multiple underactuated autonomous underwater vehicles (AUVs) involves two tasks. The first one is to force each AUV to converge to the desired parameterized path. The second one is to satisfy the requirement of a cooperative behavior along the paths. In this paper, both of the tasks have been further studied. For the first one, a simplified path following controller is proposed by incorporating the dynamic surface control (DSC) technique to avoid the calculation of derivatives of virtual control signals. Besides, in order to handle the uncertain dynamics, a new type of neural network (NN) adaptive controller is derived, and then an NN based energy‐efficient path following controller is firstly proposed, which consists of an adaptive neural controller dominating in the neural active region and an extra robust controller working outside the neural active region. For the second one, in order to reduce the amount of communications between multiple AUVs, a distributed estimator for the reference common speed is firstly proposed as determined by the communications topology adopted, which means the global knowledge of the reference speed is relaxed for the problem of cooperative path following. The overall algorithm ensures that all the signals in the closed‐loop system are globally uniformly ultimately bounded (GUUB) and the output of the system converges to a small neighborhood of the reference trajectory by properly choosing the design parameters. Simulation results validate the performance and robustness of the proposed strategy.     

Cooperative control of multiple surface vessels in the presence of ocean currents and parametric model uncertainty

This paper addresses the problem of cooperative path‐following of multiple autonomous vehicles. Stated briefly, the problem consists of steering a group of vehicles along specified paths while keeping a desired spatial formation. For a given class of autonomous surface vessels, it is shown how Lyapunov‐based techniques and graph theory can be brought together to design a decentralized control structure, where the vehicle dynamics and the constraints imposed by the topology of the inter‐vehicle communication network are explicitly taken into account. To achieve path‐following for each vehicle, a nonlinear adaptive controller is designed that yields convergence of the trajectories of the closed‐loop system to the path in the presence of constant unknown ocean currents and parametric model uncertainty. The controller derived implicitly compensates for the effect of the ocean current without the need for direct measurements of its velocity. Vehicle cooperation is achieved by adjusting the speed of each vehicle along its path according to information exchanged on the positions of a subset of the other vehicles, as determined by the communication topology adopted. Global stability and convergence of the closed‐loop system are guaranteed. Illustrative examples are presented and discussed. Copyright © 2009 John Wiley & Sons, Ltd.     

Adaptive neural control for cooperative path following of marine surface vehicles: state and output feedback

This paper addresses the cooperative path-following problem of multiple marine surface vehicles subject to dynamical uncertainties and ocean disturbances induced by unknown wind, wave and ocean current. The control design falls neatly into two parts. One is to steer individual marine surface vehicle to track a predefined path and the other is to synchronise the along-path speed and path variables under the constraints of an underlying communication network. Within these two formulations, a robust adaptive path-following controller is first designed for individual vehicles based on backstepping and neural network techniques. Then, a decentralised synchronisation control law is derived by means of consensus on along-path speed and path variables based on graph theory. The distinct feature of this design lies in that synchronised path following can be reached for any undirected connected communication graphs without accurate knowledge of the model. This result is further extended to the output feedback case, where an observer-based cooperative path-following controller is developed without measuring the velocity of each vehicle. For both designs, rigorous theoretical analysis demonstrate that all signals in the closed-loop system are semi-global uniformly ultimately bounded. Simulation results validate the performance and robustness improvement of the proposed strategy.     

基于图像验证的ETC干扰问题解决方法

电子不停车收费系统(ETC)的干扰问题的原因在于现有的技术验证系统通过微波通信没有获得正确的车辆信息,针对这个问题提出一种基于字符凹凸特征的快速牌照字符验证方法.该方法以系统获得的牌照信息为已知信息,选择当前车辆牌照字符图像的凹凸特征验证其是否来源于当前待交易车辆,无需对牌照图像进行复杂的预处理,也不是直接的牌照字符识别,从而满足了ETC系统的实时性要求.实验结果表明,采用该方法以及车辆颜色和车型验证,能可靠地检查出非法车辆,切实解决ETC系统的干扰问题.     

Fault‐tolerant path‐following control for in‐wheel‐motor‐driven autonomous ground vehicles with differential steering

Over the past several decades, the automobile industry has denoted significant research efforts to developing in‐wheel‐motor‐driven autonomous ground vehicles (IWM‐AGVs) with active front‐wheel steering. One of the most fundamental issues for IWM‐AGVs is path following, which is important for automated driving to ensure that the vehicle can track a target‐planned path during local navigation. However, the path‐following task may fail if the system experiences a stuck fault in the active front‐wheel steering. In this paper, a fault‐tolerant control (FTC) strategy is presented for the path following of IWM‐AGVs in the presence of a stuck fault in the active front‐wheel steering. For this purpose, differential steering is used to generate differential torque between the left and right wheels in IWM‐AGVs, and an adaptive triple‐step control approach is applied to realize coordinated lateral and longitudinal path‐following maneuvering. The parameter uncertainties for the cornering stiffness and external disturbances are considered to make the vehicles robust to different driving environments. The effectiveness of the proposed scheme is evaluated with a high‐fidelity and full‐car model based on the veDYNA‐Simulink joint platform.     

Improving the coordination efficiency of limited‐communication multi–autonomus underwater vehicle operations using a multiagent architecture

This research addresses the problem of coordinating multiple autonomous underwater vehicle (AUV) operations. An intelligent mission executive has been created that uses multiagent technology to control and coordinate multiple AUVs in communication‐deficient environments. By incorporating real‐time vehicle prediction, blackboard‐based hierarchical mission plans, mission optimization, and a distributed multiagent–based paradigm in conjunction with a simple broadcast communication system, this research aims to handle the limitations inherent in underwater operations, namely poor communication, and intelligently control multiple vehicles. In this research, efficiency is evaluated and then compared to the current state of the art in multiple AUV control. The research is then validated in real AUV coordination trials. Results will show that compared to the state of the art, the control system developed and implemented in this research coordinates multiple vehicles more efficiently and is able to function in a range of poor communication environments. These findings are supported by in‐water validation trials with heterogeneous AUVs. © 2010 Wiley Periodicals, Inc.     

Pattern preserving path following of unicycle teams with communication delays

This paper examines the problem of pattern-preserving path following control for unicycle teams with time-varying communication delay. A key strategy used here introduces a virtual vehicle formation such that each real vehicle has a corresponding virtual vehicle as its pursuit target. Under an input-driven consensus protocol, the virtual vehicle formation is forced to stay close to the desired vehicle formation; and a novel controller design is proposed to achieve virtual leader tracking for each vehicle with constrained motion. It is shown that, by the proposed strategy, the pattern can be preserved if the formation speed is less than some computable value that decreases with increasing size of delay, and the exact desired formation pattern can be eventually achieved if this speed tends to zero.     

Continuous Airborne Communication Relay Approach Using Unmanned Aerial Vehicles

As a result of unmanned aerial vehicles being widely used in different areas, studies about increasing the autonomous capabilities of unmanned aerial vehicles are gaining momentum. Today, unmanned aerial vehicle platforms are especially used in reconnaissance, surveillance and communications areas. In this study, in order to achieve continuous long-range communication relay infrastructure, artificial potential field based path planning of Unmanned Aerial Vehicles is discussed. A novel dynamic approach to relay-chain concept is proposed to maintain the communication between vehicles. Besides dynamically keeping vehicles in range and appropriate position to maintain communication relay, artificial potential field based path planning also provides collision avoidance system. The performance of the proposed system is measured by applying a simulation under the Matlab Simulink and Network Simulator environment. Artificial potential field based flight patterns are generated in Matlab, and performance of the communication between vehicles is measured in Network Simulation environment. Finally the simulation results show that an airborne communication relay can be established autonomously by using artificial potential filed based autonomous path planning approach. Continues state communication is provided by obtaining a resistant communication relay which depends on artificial potential field based positioning algorithm.     

Robust controller design for uncertain delayed systems and its applications to hypersonic vehicles

The longitudinal dynamics of hypersonic flight vehicles involves strong nonlinearity and coupling, uncertainties including parametric uncertainties, unmodeled uncertainties, external disturbances, and time‐varying input and state time delays. In this paper, a robust controller design method is proposed for the longitudinal stabilization of these vehicles by the signal‐compensation‐based control idea. Theoretical analysis is given to prove the robustness properties of the designed closed‐loop control system subject to multiple time‐varying uncertainties and time‐varying input and state delays. Simulation results are performed to show the validness and advantages of the proposed robust control approach.     

T-CPS下考虑人驾车行为影响的混行车辆协同控制

由于传统人驾车(traditional human-driven vehicles,HVs)驾驶行为会受到驾驶员的心理和生理活动的不确定性影响,可能使得车辆频繁地加减速,进而导致混合交通条件下网联自动车(connected and automated vehicles,CAVs)很难快速跟踪此行为.针对这一问题,首先提出一种提前预测传统人驾车行为的组合神经网络.在此基础上,考虑通信时延和车辆运动学特性,设计一种基于交通信息物理系统(transportation-cyber physical system,T-CPS)的混行车群内车辆协同控制策略,使其能够快速跟踪上传统人驾车行为,并对混行车群内网联自动车之间的串稳定性进行分析.最后,在混合交通条件下设置由1辆传统人驾车、1辆领头网联自动车和4辆跟随网联自动车形成的混行车群,利用下一代交通仿真(next generation simulation,NGSIM)车辆轨迹数据选出高质量传统人驾车状态,并通过仿真实验验证所提协同控制策略的有效性和可行性.由仿真实验结果可知,所提协同控制策略可以保证所有的网联自动车能够快速跟踪上传统人驾车行为,为解决新型混合交通带来的新问题提供一定的理论指导和借鉴.     

基于协助车组的车联网多信道协助下载方法

针对目前车联网中单信道协助下载方法的吞吐量低和通信域叠加的问题,提出一种基于对向协助车车组的车联网多信道协助下载方法McDvg。此方法利用对向协助车车组相遇概率大、通信多次重传以及延长数据传输时间的特点在局部范围内形成车组,并设计选车策略选择一组合适的对向车辆携带用户所需的数据为目标车辆提供协助下载;利用对向协助车组可有效延长目标车的协助下载时间,并采用多信道的策略解决单信道情况下的通信冲突问题。最后本文通过相应的仿真实验对该方案进行验证,仿真结果表明该方法可以在高速移动环境中显著提高下载吞吐量,降低盲区的通信时延,从而为当前的车联网提供有效的服务支撑。     

Synchronization of Instantaneous Coupled Harmonic Oscillators With Communication and Input Delays

This paper investigates the synchronization issue of instantaneous coupled harmonic oscillators with communication and input delays. A distributed synchronization algorithm is proposed for such oscillator systems, and some general algebraic criteria on exponential convergence are established for the algorithm. The main contributions of the present investigations include: (i) the directed network topology is first considered in the case of instantaneous interaction; (ii) both the time‐varying communication and input delays are simultaneously addressed; (iii) the effects of communication and input delays on synchronization performance of coupled harmonic oscillators are discussed. It is shown the communication delays have a more important impact than the input delays on determining synchronization dynamics of coupled harmonic oscillators. Explicitly, in absence of communication delays, coupled harmonic oscillators can achieve synchronization oscillatory motion, whereas, so long as communication delays are nonzero at infinite multiple impulsive times, its synchronization (or consensus) state is zero. Finally, numerical examples demonstrate the obtained theoretical results.     

车载网络环境下消息携带车辆的选择方案

针对城市车载自组织网络拓扑的动态性,现有消息传播方案单个车辆较难在某路边接入点(AP)通信范围内完全进行文件下载,具有只能在等待下个AP进行文件通信的长时延局限性,提出利用多个车辆在多个空闲AP通信范围内协同地对同一文件进行分片下载传播,将消息送达时延分为直接相遇时延和间接相遇时延分别进行讨论,并给出了具体的消息携带车辆选择方案。通过对实验结果中消息丢包率和时延分析说明,在环境中加入该方案能够有效提高文件下载的可靠性,减少下载到目的车辆的时延,不会使网络产生较大的额外负载。     

Sampled-data synchronisation of coupled harmonic oscillators with communication and input delays subject to controller failure

This paper considers the sampled-data synchronisation problems of coupled harmonic oscillators with communication and input delays subject to controller failure. A synchronisation protocol is proposed for such oscillator systems over directed network topology, and then some general algebraic criteria on exponential convergence for the proposed protocol are established. The main features of the present investigation include: (1) both the communication and input delays are simultaneously addressed, and the directed network topology is firstly considered and (2) the effects of time delays on synchronisation performance are theoretically and numerically investigated. It is shown that in the absence of communication delays, coupled harmonic oscillators can achieve synchronisation oscillatory motion. Whereas if communication delays are nonzero at infinite multiple sampled-data instants, its synchronisation (or consensus) state is zero. This conclusion can be used as an effective control strategy to stabilise coupled harmonic oscillators in practical applications. Furthermore, it is interesting to find that increasing either communication or input delays will enhance the synchronisation performance of coupled harmonic oscillators. Subsequently, numerical examples illustrate and visualise theoretical results.     

Precedence-constrained path planning of messenger UAV for air-ground coordination

This paper addresses an unmanned aerial vehicle (UAV) path planning problem for a team of cooperating heterogeneous vehicles composed of one UAV and multiple unmanned ground vehicles (UGVs). The UGVs are used as mobile actuators and scattered in a large area. To achieve multi-UGV communication and collaboration, the UAV serves as a messenger to fly over all task points to collect the task information and then flies all UGVs to transmit the information about tasks and UGVs. The path planning of messenger UAV is formulated as a precedence-constrained dynamic Dubins traveling salesman problem with neighborhood (PDDTSPN). The goal of this problem is to find the shortest route enabling the UAV to fly over all task points and deliver information to all requested UGVs. When solving this path planning problem, a decoupling strategy is proposed to sequentially and rapidly determine the access sequence in which the UAV visits task points and UGVs as well as the access location of UAV in the communication neighborhood of each task point and each UGV. The effectiveness of the proposed approach is corroborated through computational experiments on randomly generated instances. The computational results on both small and large instances demonstrate that the proposed approach can generate high-quality solutions in a reasonable time as compared with two other heuristic algorithms.     

Optimal coordination in logistics warehousing with sensing and communication limits: A distributed differential game approach

Optimal coordination is essential for multi-automated guided vehicle (AGV) systems, particularly in logistic transportation cases, where the system task completion time needs to be minimized, with the guarantee of safe operation. This is because an optimal coordination strategy (OCS), if achieved, can significantly improve the transportation system's efficiency. In this paper, to deal with the dynamic interaction process among AGVs, and sensing and communication range limits, we formulate the optimal coordination problem into a distributed differential game (DDG) framework, where individual AGVs only use information communicated from nearby AGVs to design their optimal operation trajectories. This helps to significantly reduce the computational and communication requirements for the multi-AGV logistic transportation systems. Targeting operation safety and working efficiency requirements, we incorporate collision avoidance and trajectory optimization objectives into the proposed framework. It is shown that local OCS, obtained by solving the DDG problem for each AGV, will converge to the global Nash equilibrium, which represents the most efficient operating condition for the entire logistic transportation system. Finally, the efficacy of the proposed method is demonstrated, based on simulations and experiments, benchmarked with existing logistic warehousing planning and differential game methods. Compared with conventional methods, the proposed framework successfully helps reduce the task completion time by up to 16%.