Traffic Control Based on Integrated Kalman Filtering and Adaptive Quantized Q-Learning Framework for Internet of Vehicles

Intelligent traffic control requires accurate estimation of the road states and incorporation of adaptive or dynamically adjusted intelligent algorithms for making the decision.In this article,these issues are handled by proposing a novel framework for traffic control using vehicular communications and Internet of Things data.The framework integrates Kalman filtering and Q-learning.Unlike smoothing Kalman filtering,our data fusion Kalman filter incorporates a process-aware model which makes it superior in terms of the prediction error.Unlike traditional Q-learning,our Q-learning algorithm enables adaptive state quantization by changing the threshold of separating low traffic from high traffic on the road according to the maximum number of vehicles in the junction roads.For evaluation,the model has been simulated on a single intersection consisting of four roads:east,west,north,and south.A comparison of the developed adaptive quantized Q-learning(AQQL)framework with state-of-the-art and greedy approaches shows the superiority of AQQL with an improvement percentage in terms of the released number of vehicles of AQQL is 5%over the greedy approach and 340%over the state-of-the-art approach.Hence,AQQL provides an effective traffic control that can be applied in today’s intelligent traffic system.

Key technologies and applications of intelligent dispatching command for high-speed railway in China

Purpose–The intelligent Central Traffic Control(CTC)system plays a vital role in establishing an intelligent high-speed railway(HSR)system.As the core of HSR transportation command,the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching.This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.Design/methodology/approach–This paper first briefly introduces the functions and configuration of the intelligent CTC system.Some new servers,terminals and interfaces are introduced,which are plan adjustment server/terminal,interface for automatic train operation(ATO),interface for Dynamic Monitoring System of Train Control Equipment(DMS),interface for Power Supervisory Control and Data Acquisition(PSCADA),interface for Disaster Monitoring,etc.Findings–The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans,safety control of train routes and commands,traffic information data platform,integrated simulation of traffic dispatching and ATO function.These technologies have been applied in the Beijing-Zhangjiakou HSR,which commenced operations at the end of 2019.Implementing these key intelligent functions has improved the train dispatching command capacity,ensured the safe operation of intelligent HSR,reduced the labor intensity of dispatching operators and enhanced the intelligence level of China’s dispatching system.Originality/value–This paper provides further challenges and research directions for the intelligent dispatching command of HSR.To achieve the objectives,new measures need to be conducted,including the development of advanced technologies for intelligent dispatching command,coping with new requirements with the development of China’s railway signaling system,the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

Optimal Distribution of N-Team Interacting Decision Makers with Hierarchical Command Inputs That Are Predicated on Order Statistics

The spectral analysis of simulated N-team of interacting decision makers with bounded rationality constraints of Oladejo, which assumes triangular probability density function of command inputs is hereby restructured and analysed, to have hierarchical command inputs that are predicated on order statistics distributions. The results give optimal distributions.

A framework of force of information influence and application for C4KISR system

The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.

Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.

Cooperative control and communication of intelligent swarms:a survey

Individuals exchange information,experience and strategy based on communication.Communication is the basis for individuals to form swarms and the bridge of swarms to realize cooperative control.In this paper,the multirobot swarm and its cooperative control and communication methods are reviewed,and we summarize these methods from the task,control,and perception levels.Based on the research,the cooperative control and communication methods of intelligent swarms are divided into the following four categories:task assignment based methods(divided into market-based methods and alliance based methods),bio-inspired methods(divided into biochemical information inspired methods,vision based methods and self-organization based methods),distributed sensor fusion and reinforcement learning based methods,and we briefly define each method and introduce its basic ideas.Based on WOS database,we divide the development of each method into several stages according to the time distribution of the literature,and outline the main research content of each stage.Finally,we discuss the communication problems of intelligent swarms and the key issues,challenges and future work of each method.

面向易行的高速铁路智能平行调度系统构架及关键技术

针对我国高铁成网运行、管控列车数量和种类多、运营方式复杂等特点,以构建新一代智能动态调度系统为目标,探讨面向易行的高速铁路智能平行调度系统构架,从5个方面提炼出高速铁路智能平行调度系统的技术特征。总结目前高速铁路智能平行调度系统研究亟待解决的关键技术,介绍智能高铁平行调度一体化仿真原型系统研制及实现的部分场景功能。研究工作可为建立面向易行服务的,适应中国高铁“效率变革”“质量变革”需求的智能动态调度理论与技术体系,实现我国高速铁路智能调度系统和运输服务水平的升级发展提供参考。

不平衡数据下基于SVM增量学习的指挥信息系统状态监控方法

针对指挥信息系统历史状态样本有限的特点,基于支持向量机(support vector machines,SVM)设计了一种面向不平衡数据的SVM增量学习方法。针对系统正常/异常状态样本不平衡的情况,首先利用支持向量生成一部分新样本,然后通过分带的思想逐带产生分布更加均匀的新样本以调节原样本集的不平衡比。针对系统监控实时性要求高且在运行过程中会有新样本不断加入的特点,采用增量学习的方式对分类模型进行持续更新,在放松KKT(Karush-Kuhn-Tucker)更新触发条件的基础上,通过定义样本重要度并引入保留率和遗忘率的方式减少了增量学习过程中所需训练的样本数量。为了验证算法的有效性和优越性,实验部分在真实系统中获得的数据集以及UCI数据集中3类6组不平衡数据集中与现有的算法进行了对比。结果表明,所提算法能够有效实现对不平衡数据的增量学习,从而满足指挥信息系统状态监控的需求。

预警机装备形态演变的新特征

自1945年投入使用以来,预警机装备经过近80年的发展,其在作战体系和杀伤链构建中,经历了从低空补忙雷达向空中C2节点的转变。现今,一方面,有人预警机的核心节点作用愈发凸显,主要担负空战场管理任务;另一方面,无人化预警机形态正在加速出现,重点发挥预警探测而不是指挥控制作用,作为有人预警机的重要补充。在产品形态上,未来的预警机将具备敏捷性、协同性以及自主性等重要特征。

Optimal control of automated left-turn platoon at contraflow left-turn lane intersections

Purpose–This study aims to propose a centralized optimal control model for automated left-turn platoon at contraflow left-turn lane(CLL)intersections.Design/methodology/approach–The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness.The proposed model is cast into a mixed-integer linear programming problem and then solved by the branch-and-bound technique.Findings–The proposed model has a promising control effect under different geometric controlled conditions.Moreover,the proposed model performs robustly under various safety time headways,lengths of the CLL and green times of the main signal.Originality/value–This study proposed a centralized optimal control model for automated left-turn platoon at CLL intersections.The lateral lane change control and the longitudinal acceleration in the control horizon are optimized simultaneously with the objective of maximizing traffic efficiency and smoothness。

Robotic Smart Prosthesis Arm with BCI and Kansei/Kawaii/Affective Engineering Approach.Pt I: Quantum Soft Computing Supremacy

A description of the design stage and results of the development of the conceptual structure of a robotic prosthesis arm is given.As a result,a prototype of man-made smart prosthesis on a 3D printer as well as a foundation for computational intelligence presented.The application of soft computing technology(the first step of IT)allows to extract knowledge directly from the physical signal of the electroencephalogram,as well as to form knowledge-based intelligent robust control of the lower performing level taking into account the assessment of the patient’s emotional state.The possibilities of applying quantum soft computing technologies(the second step of IT)in the processes of robust filtering of electroencephalogram signals for the formation of mental commands of robotic prosthetic arm discussed.Quantum supremacy benchmark of intelligent control simulation demonstrated.

智能化分布式指挥与控制建设及关键技术应用

为厘清智能化分布式指挥与控制体系的发展态势及其关键技术,基于系统工程思维,通过收集开源情报、整合体系架构与建设进展等方式,对美军典型案例进行深入研究。同时,对其在特定作战场景中的应用进行阐释。结果表明,面向未来大规模、快节奏、多样化的战争,美军通过构建联合战术网、布局无人控制平台、研发智能决策辅助系统的方式增强作战指挥与控制的智能性。通过具体案例分析可知,分布式指挥与控制的智能化主要依赖边缘云、人工智能、无人自主系统及先进网络通信等关键技术。

An executable modeling and analyzing approach to C4ISR architecture

To analyze the behavioral model of the command,control,communication,computer,intelligence,surveillance,reconnaissance(C4ISR)architecture,we propose an executable modeling and analyzing approach to it.First,the meta concept model of the C4ISR architecture is introduced.According to the meta concept model,we construct the executable meta models of the C4ISR architecture by extending the meta models of fUML.Then,we define the concrete syntax and executable activity algebra(EAA)semantics for executable models.The semantics functions are introduced to translating the syntax description of executable models into the item of EAA.To support the execution of models,we propose the executable rules which are the structural operational semantics of EAA.Finally,an area air defense of the C4ISR system is used to illustrate the feasibility of the approach.

面向跨域联合作战的平行指挥控制与管理新范式

瞄准制衡强敌“马赛克战”“决策中心战”等新技术驱动的作战概念及威胁挑战,聚焦未来跨域联合作战指挥控制(command and control,C2)全流程决策需求,遵循平行智能理论框架,提出了基于筹划-准备-执行-评估(planning-readiness-execution-assessment,PREA)环与观察-判断-决策-行动(observe-orient-decide-act,OODA)环的平行指挥控制与管理(command&control and management,C2M)新范式,以期实现智能机器辅助指挥员作战全流程的分层次、个性化决策支持,减轻指挥员认知负担、降低决策复杂度,实现机器对指挥员“人脑”的智能扩展与增强,为塑造全局决策优势提供牵引和支撑。

基于网络信息体系的全域联合指挥与控制技术及未来展望

面向现代战争需求,全域联合作战通过打破传统作战区域限制,能够实现不同军种和作战领域的信息共享、军事力量整合和协同作战,从而提升作战效率、增强指挥灵活性、优化资源配置。全域联合有诸多优势,使基于网络信息体系的全域联合指挥与控制技术成为研究重点。本文系统分析了全域联合指挥与控制的发展历程、技术应用、架构设计和关键技术,同时结合国外的研究现状探讨发展方向,旨在为全域联合指挥与控制技术的发展提供参考。

类ChatGPT赋能指挥控制的情报提升和情报局限--基于信息流动模型

[研究目的]研究类ChatGPT赋能指挥控制的情报提升和情报局限,探索未来战争的情报作用发挥机理。[研究方法]引入指挥控制活动的基本范式PREA-OODA循环,提出情报学视角下的信息流动模型,基于该模型分析类ChatGPT应用于指挥控制的情报提升和情报局限。[研究结论]类ChatGPT对指挥控制的情报赋能原理为:优化态势生成过程和辅助决策过程,获得更佳的信息状态或结果。类ChatGPT技术应用于指挥控制系统能带来巨大的情报能力提升,也可能因其情报局限引发灾难性后果。从情报赋能原理和阶段的角度探索类ChatGPT在指挥控制中的应用。

自适应智能人机交互在水下指挥控制系统的应用

智能化指挥控制已经成为现代战争作战指挥的新样式,高动态、强对抗、海量数据的战场环境对指挥效率和任务执行能力提出了更高的要求。传统人机交互模式交互效率低,缺乏以人为中心的交互设计,无法充分发挥水下指挥控制的效能。基于智能人机交互和主成分分析法,设计出一种能够根据用户和业务生成水下指挥控制自适应界面的交互模块。通过搭建水下指挥控制智能仿真平台,证实自适应智能人机交互能够简化指挥控制流程,缩减交互用时,提升作战效率,具有较好的应用价值。

面向软件定义的C~4ISR系统资源建模方法研究

为实现马赛克化的C~4ISR系统构建模式,瞄准系统“元要素”构建,以软件定义技术为驱动,探讨了可定义的资源建模原理,提出了资源建模过程,定义了C~4ISR系统资源概念内涵,基于多视角建立了资源分类框架;围绕资源信息流受控和能力开放共享,提出了模型要素,针对7类资源特点建立了参考模型。通过典型案例下资源实例化建模,验证了模型对软件定义的系统构建的适用性。

配网抢修智慧指挥全流程管控系统设计

为了扩大配网抢修过程中的管控规模、降低风险和损失,设计了配网抢修智慧指挥全流程管控系统。在硬件部分,针对系统实际应用功能设计硬件整体结构,根据IEC 61850标准,利用电缆和三轴磁传感模块优化电子互感器的接口电路,以提升电流与电压信号的传输性能。在软件部分,基于多维数据云调控技术进行数据采集与融合,完成配网抢修智慧指挥全流程管控系统设计,以实现抢修看板可视化管控。测试结果表明,所提方法与理想方法之间的关联度指标优于其他对比方法。该设计可降低配网抢修风险。

未来智能杀伤网构想

大国战争的战场形态朝着高动态、高烈度的方向发展,单一武器系统或其形成的杀伤链难以适应未来的战争形态。杀伤网作为一种高动态、高弹性的新型作战概念,具有极高的自适应性、自组织性和韧性,可以通过极快的反应速度完成作战编组构建和指挥控制,大幅提升决策效率。本文首先针对杀伤网这一作战概念展开研究,然后从杀伤链的产生背景、“链”到“网”的过渡、基本概念、典型案例、关键技术等方面展开分析论述,最后结合智能化技术总结了对未来杀伤网智能化的构想。