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Computational Experiments for complex Social systems--Part I: The Customization of Computational Model

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2022年第5期9卷 1330-1344页

作者： Xue, Xiao Chen, Fangyi Zhou, Deyu Wang, Xiao Lu, Min Wang, Fei-Yue Tianjin Univ Coll Intelligence & Comp Tianjin 454000 Peoples R China China Univ Geosci Sch Informat Engn Beijing 100083 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100080 Peoples R China

Computational experiments have emerged as a new method for quantitative analysis of complex social systems. It has been applied to many interdisciplinary research fields, such as economics, finance, and epidemiology. Though the representation form of computational experiments is relatively flexible, the real system is more complex. Therefore, it is important to seek a balance between the flexibility of computational modeling and the credibility of conclusion. This article proposes a customized design framework for computational experiment models, so as to meet the diverse application demands of computational experiments in different fields. Finally, this article outlines some typical applications of computational experiments to provide a roadmap for its rapid development and widespread application.

关键词： Computational modeling complex systems Analytical models Tools Adaptation models Standards Solid modeling Artificial society computational experiments computational model customized design framework

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Interval Type-2 Fuzzy Hierarchical Adaptive Cruise Following-control for Intelligent Vehicles

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1658-1672页

作者： Hong Mo Yinghui Meng Fei-Yue Wang Dongrui Wu the College of Electric and Information Engineering Changsha University of Science and TechnologyChangsha 410114China the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 Qingdao Academy of Intelligent Industries Qingda 266109 the Center of China Economic and Social Security University of Chinese Academy of SciencesBeijing 100190China the Ministry of Education Key Laboratory on Image Information Processing and Intelligent Control the School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China

Intelligent vehicles can effectively improve traffic congestion and road traffic *** cruise followingcontrol(ACFC)is a vital part of intelligent *** this paper,a new hierarchical vehicle-following control strategy is presented by synthesizing the variable time headway model,type-2 fuzzy control,feedforward+fuzzy proportion integration(PI)feedback(F+FPIF)control,and inverse longitudinal dynamics model of ***,a traditional variable time headway model is improved considering the acceleration of the lead ***,an interval type-2 fuzzy logic controller(IT2 FLC)is designed for the upper structure of the ACFC system to simulate the driver's operating *** reduce the nonlinear influence and improve the tracking accuracy for the desired acceleration,the control strategy of F+FPIF is given for the lower control ***,the lower control method proposed in this paper is compared with the fuzzy PI control and the traditional method(no lower controller for tracking desired acceleration)***,the proportion integration differentiation(PID),linear quadratic regulator(LQR),subsection function control(SFC)and type-1 fuzzy logic control(T1 FLC)are respectively compared with the IT2 FLC in control performance under different ***,the simulation results show the effectiveness of IT2 FLC for the upper structure and F+FPIF control for the lower structure.

关键词： Adaptive cruise following-control(ACFC) feedforward+fuzzy proportion integration(PI)feedback(F+FPIF) type-2 fuzzy control variable time headway

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Steps Toward Industry 5.0:Building“6S”Parallel Industries With Cyber-Physical-Social Intelligence

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1692-1703页

作者： Xingxia Wang Jing Yang Yutong Wang Qinghai Miao Fei-Yue Wang Aijun Zhao Jian-Ling Deng Lingxi Li Xiaoxiang Na Ljubo Vlacic School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China North Automatic Control Technology Institute Taiyuan 030006China China Huaneng Group Co. Ltd.Beijing 100031China Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis(IUPUI)IndianapolisIN 46202 USA Department of Engineering University of CambridgeCambridgeCB21PZUK School of Engineering and Built Environment Griffith UniversityGold CoastQLD 4222Australia

Very recently,intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers,entrepreneurs,and policymakers from various sectors around the ***,there is no consensus on why and what is Industry 5.0 *** this paper,we define Industry 5.0from its philosophical and historical origin and evolution,emphasize its new thinking on virtual-real duality and human-machine interaction,and introduce its new theory and technology based on parallel intelligence(PI),artificial societies,computational experiments,and parallel execution(the ACP method),and cyber-physical-social systems(CPSS).Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future *** believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart *** are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces,S ecure in cyberspaces,Sustainable in ecology,Sensitive in individual privacy and rights,Service for all,and Smartness of all.

关键词： ACP artificial intelligence CPS CPSS Industry 4.0 Industry 5.0 parallel industries parallel intelligence

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A Novel Parallel control Method for Continuous-Time Linear Output Regulation With Disturbances

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IEEE TRANSACTIONS ON CYBERNETICS 2023年第6期53卷 3760-3770页

作者： Wei, Qinglai Li, Hongyang Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Taipa Macao Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China

In this article, a novel linear parallel control method is developed for output regulation problems with disturbances. The traditional feedback regulators are passive regulation methods. In order to solve this problem, the parallel controllers are presented, where the time variation of the control is constructed instead of the control value itself, to stabilize the output of the system. The main contributions of the developed method include two aspects: 1) a novel parallel regulator structure is presented, which can provide greater flexibility comparing with traditional methods and 2) the necessary and sufficient conditions for the existence of parallel regulators are analyzed. First, the structure of the linear parallel regulators is provided. Next, considering the situations that the full system information is obtained and the information of error is obtained, respectively, the properties of the parallel regulators are analyzed, and the regulator designs for the two situations are provided. Finally, numerical examples are provided to verify the correctness of the present method.

关键词： Regulators Regulation control systems Stability analysis Asymptotic stability Eigenvalues and eigenfunctions control theory Continuous-time linear systems output regulation parallel control theory parallel regulators parallel systems

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A Two-Stream CNN With Simultaneous Detection and Segmentation for Robotic Grasping

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2022年第2期52卷 1167-1181页

作者： Yu, Yingying Cao, Zhiqiang Liu, Zhicheng Geng, Wenjie Yu, Junzhi Zhang, Weimin Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ State Key Lab Turbulence & Complex Syst Dept Mech & Engn Sci BIC ESAT Coll Engn Beijing 100871 Peoples R China Beijing Inst Technol Beijing Adv Innovat Ctr Intelligent Robots & Syst Beijing 100081 Peoples R China

The manipulating robots receive much attention by offering better services, where object grasping is still challenging especially under background interferences. In this article, a novel two-stream grasping convolutional neural network (CNN) with simultaneous detection and segmentation is proposed. The proposed method is cascaded by an improved simultaneous detection and segmentation network BlitzNet and a two-stream grasping CNN TsGNet. The improved BlitzNet introduces the channel-based attention mechanism, and achieves an improvement of detection accuracy and segmentation accuracy with the combination of the learning of multitask loss weightings and background suppression. Based on the obtained bounding box and the segmentation mask of the target object, the target object is separated from the background, and the corresponding depth map and grayscale map are sent to TsGNet. By adopting depthwise separable convolution and designed global deconvolution network, TsGNet achieves the best grasp detection with only a small amount of network parameters. This best grasp in the pixel coordinate system is converted to a desired 6-D pose for the robot, which drives the manipulator to execute grasping. The proposed method combines a grasping CNN with simultaneous detection and segmentation to achieve the best grasp with a good adaptability to background. With the Cornell grasping dataset, the image-wise accuracy and object-wise accuracy of the proposed TsGNet are 93.13% and 92.99%, respectively. The effectiveness of the proposed method is verified by the experiments.

关键词： Grasping Robot kinematics Manipulators Image segmentation Deconvolution Machine learning Global deconvolution network (GDN) robotic grasping simultaneous detection and segmentation two-stream grasping convolutional neural network (CNN)

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From Features Engineering to Scenarios Engineering for Trustworthy AI: I&I, C&C, and V&V

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IEEE INTELLIGENT systems 2022年第4期37卷 18-26页

作者： Li, Xuan Ye, Peijun Li, Juanjuan Liu, Zhongmin Cao, Longbing Wang, Fei-Yue Peng Cheng Lab Shenzhen 518000 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China North Automat Control Technol Inst Taiyuan 030006 Peoples R China Univ Technol Sydney Sydney NSW 2007 Australia Chinese Acad Sci Beijing 100190 Peoples R China

Artificial intelligence (AI)'s rapid development has produced a variety of state-of-the-art models and methods that rely on network architectures and features engineering. However, some AI approaches achieve high accurate results only at the expense of interpretability and reliability. These problems may easily lead to bad experiences, lower trust levels, and systematic or even catastrophic risks. This article introduces the theoretical framework of scenarios engineering for building trustworthy AI techniques. We propose six key dimensions, including intelligence and index, calibration and certification, and verification and validation to achieve more robust and trusting AI, and address issues for future research directions and applications along this direction.

关键词： Systematics Reliability Theory Network Architecture Reliability Engineering Calibration Artificial Intelligence

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Hierarchical Deep Reinforcement Learning With Experience Sharing for Metaverse in Education

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2023年第4期53卷 2047-2055页

作者： Hare, Ryan Tang, Ying Rowan Univ Dept Elect & Comp Engn Glassboro NJ 08028 USA Qingdao Acad Intelligent Ind Inst Smart Educ Qingdao 266000 Peoples R China Chinese Acad Sci Inst Automation State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Dalian Maritime Univ Sch Informat Sci & Technol Dalian 116026 Peoples R China

Metaverse has gained increasing interest in education, with much of literature focusing on its great potential to enhance both individual and social aspects of learning. However, little work has been done to address the systems and technologies behind providing meaningful Metaverse learning. This article proposes a technical framework to address this research gap, where a hierarchical multiagent reinforcement learning approach with experience sharing is developed to augment the intelligence of nonplayer characters in Metaverse learning for personalization. The utility and benefits of the proposed framework and methodologies are demonstrated in Gridlock, a Metaverse learning game, as well as through extensive simulations.

关键词： ACP experience sharing metaverse learning reinforcement learning (RL)

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Asynchronous L1-gain Filtering of Nonlinear Positive Semi-Markov Jump systems with Time-varying Delays 41

Asynchronous L1-gain Filtering of Nonlinear Positive Semi-Ma...

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41st Chinese control Conference (CCC)

作者： Ma, Chao Fu, Hang Ji, Yidao Wu, Wei Univ Sci & Technol Beijing Sch Mech Engn Beijing Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China

ISBN: (纸本)9789887581536

In this paper, the L-1-gain based filtering problem for nonlinear positive semi-Markov jump systems is investigated by proposing a novel asynchronous design approach. More precisely, the mode-dependent filters are designed in terms of practical observed modes instead of true system modes, such that less conservatism can be achieved. In addition, the effect of time-varying delays is taken into account for more robustness and applicability. By selecting suitable stochastic Lyapunov-Krasovskii functions and applying the linear programming method, sufficient conditions are established to fulfill the desired L-1-gain performance. Eventually, the illustrative simulation is performed to verify the effectiveness of our developed control scheme.

关键词： Positive semi-Markov jump systems nonlinear semi-Markov jump systems asynchronous filtering L-1-gain

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ChatGPT as Your Vehicle Co-Pilot: An Initial Attempt

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第12期8卷 4706-4721页

作者： Wang, Shiyi Zhu, Yuxuan Li, Zhiheng Wang, Yutong Li, Li He, Zhengbing Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Tsinghua Univ BNRIST Dept Automat Beijing 100084 Peoples R China Tsinghua Univ Tsinghua Shenzhen Int Grad Sch Shenzhen 518055 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China MIT Senseable City Lab Cambridge MA 02139 USA

One of the most challenging problems in human-machine co-work is the gap between human intention and the machine's understanding and execution. Large Language Models (LLMs) have been showing superior abilities in solving such issue. In this article, we design a universal framework that embeds LLMs as a vehicle "Co-Pilot" of driving, which can accomplish specific driving tasks with human intention satisfied based on the information provided. Meanwhile, a utilization workflow is defined to handle the interaction between humans and vehicles, and memory mechanism is introduced to organize the information involved in the tasks. Expert Oriented Black-Box tuning is proposed to improve the performance of the Co-Pilot without finetuning or training the LLMs. In the experiment, the Co-Pilot is applied to two different tasks, i.e., path tracking control and trajectory planning. The Co-Pilot adjusts vehicle operating conditions by selecting a proper controller or planning a certain trajectory to fit human intentions. Simulation tests are conducted to evaluate the performance and generality of the proposed module. The results show that the Co-Pilot can accomplish most of the tasks based on only natural language processing, although it is not flawless. Finally, a discussion about human-machine hybrid intelligence and further applications of LLMs in autonomous driving is made. We believe that such a framework has promising potential in further applications in the field of automous vehicles.

关键词： Task analysis Tuning Closed box Automation Adaptive control Training Autonomous driving Human-machine systems Cognition Human factors human-machine interaction large language model parallel learning

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Development and Testing of Advanced Driver Assistance systems Through Scenario-Based systems Engineering

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第8期8卷 3968-3973页

作者： Li, Xuan Song, Rui Fan, Junfeng Liu, Mingyang Wang, Fei-Yue Peng Cheng Lab Shenzhen 518000 Peoples R China Changan Univ Sch Informat Engn Xian 710064 Peoples R China China Automot Technol Res Ctr Co Ltd Tianjin 300300 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Guangzhou Co Ltd CATARC Automot Test Ctr Guangzhou 511300 Peoples R China

Advanced driver assistance systems (ADAS) hold great promise for improving transportation safety and efficiency. However, the development of these technologies requires a robust and systematic engineering process to ensure their reliable and safe operation in various traffic situations. In this letter, we present a scenario-based systems engineering for the development and test of advanced driver assistance systems, drawing insights from a real automotive proving ground. This letter is the second part of Decentralized and Hybrid Workshop (DHW) on Scenarios Engineering (SE), which aims to improve scenario diversity and representation for advanced driver assistance systems. The article proposes a 5-layer scenario architecture and also describes several key tasks that must be addressed in the ADAS, such as lane keeping assistance (LSK), adaptive cruise control (ACC) and autonomous emergency braking (AEB). Additionally, we elaborate on the testing challenges that the aforementioned tasks entail. Finally, we employ clustering methods to obtain 9 crucial scenarios of LKA, which can be utilized for ADAS testing.

关键词： Roads Testing Vehicles systems engineering and theory Advanced driver assistance systems Meters Autonomous vehicles Scenarios-based system engineering advanced driver assistance systems parallel intelligence lane keeping assistance adaptive cruise control autonomous emergency braking

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