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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Shao, Chen Duan, Xuting Zhou, Jianshan Zhao, Dezong School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Zhongguancun Laboratory Beijing China James Watt School of Engineering University of Glasgow Glasgow United Kingdom

ISBN: (纸本)9798350316308

A proposed obstacle avoidance trajectory planning method for autonomous vehicles considers social behavior characteristics to address the interaction problem with human drivers in mixed traffic environments. The method integrates graph theory and centrality functions to classify and predict driver behavior, employing model predictive control (MPC) to plan the autonomous vehicle's trajectory. By combining these social behaviors, the method ensures safe completion of the driving task based on probability. Experimental results from an interactive obstacle avoidance scenario in a curved environment confirm the successful completion of the task, validating the proposed method's feasibility and effectiveness, supporting its potential for real-world application. © 2023 IEEE.

关键词： Model predictive control

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RPBFT: A Scalab.e Consensus Mechanism for Large Blockchain systems 19th

RPBFT: A Scalable Consensus Mechanism for Large Blockchain S...

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19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Wang, Weizhe Tian, Daxin Duan, Xuting Zhou, Jianshan School of Transportation Science and Engineering Beihang University Beijing China State Key Lab of Intelligent Transportation System Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9783031651250

As an emerging technology, blockchain has enabled trustworthy data sharing and efficient cooperation in many industries. It can also make data traceable and auditable, which perfectly meets the regulatory demands for data security and privacy. However, the employment of blockchain is limited in some fields due to the poor scalab.lity of the consensus mechanism. Therefore, this paper introduces a scalab.e consensus mechanism called RPBFT to improve the performance of large-scale systems. To demonstrate the advantage of RPBFT over classic consensus mechanism, we find a way to implement it in blockchain systems and conduct performance tests to evaluate the throughput and latency of the established systems. The results show that RPBFT is superior and more suitable for large-scale blockchain systems. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Blockchain Consensus mechanism Scalab.lity

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Detection of Stealthy False Data Injection Attacks Against Cyber-Physical systems:A Stochastic Coding Scheme

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Journal of systems Science & Complexity 2022年第5期35卷 1668-1684页

作者： GUO Haibin PANG Zhonghua SUN Jian LI Jun State Key Lab of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongging Innovation Center Chongqing 401120China Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China

This paper,from the view of a defender,addresses the security problem of cyber-physical systems(CPSs)subject to stealthy false data injection(FDI)attacks that cannot be detected by a residual-based anomaly detector without other defensive *** detect such a class of FDI attacks,a stochastic coding scheme,which codes the sensor measurement with a Gaussian stochastic signal at the sensor side,is proposed to assist an anomaly detector to expose the FDI *** order to ensure the system performance in the normal operational context,a decoder is adopted to decode the coded sensor measurement when received at the controller *** this detection scheme,the residual under the attack can be significantly different from that in the normal situation,and thus trigger an *** design condition of the coding signal covariance is derived to meet the constraints of false alarm rate and attack detection *** minimize the trace of the coding signal covariance,the design problem of the coding signal is converted into a constraint non-convex optimization problem,and an estimation-optimization iteration algorithm is presented to obtain a numerical solution of the coding signal covariance.A numerical example is given to verify the effectiveness of the proposed scheme.

关键词： Attack detection cyber-physical systems(CPSs) stealthy FDI attacks stochastic coding

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Evolution of Cooperation in Snowdrift Game with Multi-Memory Mechanism 42

Evolution of Cooperation in Snowdrift Game with Multi-Memory...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Yaojun Liu, Xingwen Tashi, Nyima College of Electrical Engineering Southwest Minzu University Lab. of Complex Systems & Intelligent Control Key Lab. of Electronic Information of State Ethnic Affairs Commission Sichuan Chengdu610225 China Engineering Research Center for Tibetan Information Processing School of Information Science and Technology Tibet University Lhasa850000 China

ISBN: (纸本)9789887581543

Cooperative behavior has been of great concern in evolutionary game researches because of its important role in social life and natural evolution. Since memory can greatly influence the emergence of cooperative behavior, memory-based research on evolutionary games has proliferated in recent years. In the present paper, inspired by the well-known 'Stanford marshmallow experiment' (SME), we proposed a multi-memory mechanism in Snowdrift game (SDG) on spatial lattice networks whose core lies in what follows: Players are divided into two groups according to individual self-control;different memory lengths are set by group and by time in a single realization. The simulation results show that our proposed mechanism promotes cooperation level of the considered evolutionary game. More specifically, as memory length increases to an intermediate length, the cooperation level increases as well. For mechanism with short memory length, the effect of population structure is obvious and small values of adjusting factor can intensively facilitate high-frequency cooperative behavior. These findings may be helpful to understand the connection between population heterogeneity and the emergence of high cooperation. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Behavioral research

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An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers 3

An Optimal Control Based Trajectory Planning Method for Coop...

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3rd International Symposium on intelligent Robotics and systems, ISoIRS 2023

作者： Wang, Qi Ge, Hao Duan, Xuting Zhou, Jianshan School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology Beijing China Nanjing Research Institute of Electronic Engineering State Key Laboratory of Air Traffic Management System and Technology Nanjing China School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China

ISBN: (纸本)9798350339963

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating System (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution. © 2023 IEEE.

关键词： Trajectories

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Parameter Estimation and Tracking control of MIMO Linear systems Without Prior Knowledge of control Signs and Parameter Bounds

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IEEE Transactions on Automatic control 2024年第6期70卷 3695-3710页

作者： Xu, Yuchun Zhang, Yanjun Zhang, Ji-Feng Chinese Academy of Sciences Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Beijing100190 China Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology State Key Lab of Automation Intelligent Unmanned Systems Beijing100081 China University of Chinese Academy of Sciences School of Mathematics Sciences Beijing100149 China Zhongyuan University of Technology School of Automation and Electrical Engineering Zhengzhou450007 China Chinese Academy of Sciences Academy of Mathematics and Systems Science Beijing100190 China

Dealing with the uncertain high-frequency gain matrix, denoted as Kp, is a fundamental problem in multivariable adaptive control systems. In this paper, we propose a new solution for parameter estimation and adaptive control for a general class of multi-input multi-output discrete-time linear time-invariant systems. The proposed scheme does not require any prior knowledge of the sign or bound information of Kp, and thus, significantly relaxes the design conditions in traditional multivariable adaptive control systems. Compared with the commonly used Nussbaum gain or multi-model techniques for addressing the unknown signs of Kp, the proposed scheme does not rely on any additional design conditions or any switching mechanism, while still ensuring closed-loop stability and asymptotic output tracking. Specifically, an output feedback adaptive control law is developed based on a matrix decomposition technique, which leads to derivation of a modified estimation error model. Subsequently, a gradient-based parameter update law is formulated only relying on the non-zero condition of the leading principle minors of Kp. Through designing gain functions and stable filters, the controller is always non-singular and does not involve any causal contradiction problem. Simulation study showcases the design process and demonstrates the effectiveness of the proposed scheme. © 1963-2012 IEEE.

关键词： MIMO systems

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One-Shot Three-Dimensional Measurement Based on Spectral Interferometry Using a Digital Micromirror Device 16

One-Shot Three-Dimensional Measurement Based on Spectral Int...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Zhang, Jinxu Shi, Liheng Gu, Yingying Zhang, Donglai Yin, Lu Wu, Guanhao Tsinghua University State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision Instrument Beijing100084 China Beijing Institute of Control Engineering Space Optoelectronic Measurement and Perception Lab. Beijing100190 China China Academy of Space Technology National Key Laboratory of Space Intelligent Control Beijing100094 China

We present a one-shot 3D spectral interferometry technique using a digital micromirror device. By encoding the distribution of the spatial light field, this approach enables 3D imaging of step structures within 27 ms.... 详细信息

ISBN: (纸本)9798350372076

关键词： Interferometry

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Efficient learning of robust quadruped bounding usingpretrained neural networks

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IET Cyber-systems and Robotics 2022年第4期4卷 331-338页

作者： Zhicheng Wang Anqiao Li Yixiao Zheng Anhuan Xie Zhibin Li Jun Wu Qiuguo Zhu Institute of Cyber-Systems and Control Zhejiang UniversityZhejiangChina Intelligent Robot Research Center Zhejiang LabZhejiangChina Department of Computer Science University College LondonLondonUK State Key Laboratory of Industrial Control Technology Zhejiang UniversityZhejiangChina

Bounding is one of the important gaits in quadrupedal locomotion for negotiating *** authors proposed an effective approach that can learn robust bounding gaits more efficiently despite its large variation in dynamic body *** authors first pretrained the neural network(NN)based on data from a robot operated by conventional model-based controllers,and then further optimised the pretrained NN via deep reinforcement learning(DRL).In particular,the authors designed a reward function considering contact points and phases to enforce the gait symmetry and periodicity,which improved the bounding *** NN-based feedback controller was learned in the simulation and directly deployed on the real quadruped robot Jueying Mini successfully.A variety of environments are presented both indoors and outdoors with the authors’*** authors’approach shows efficient computing and good locomotion results by the Jueying Mini quadrupedal robot bounding over uneven *** cover image is based on the Research Article Efficient learning of robust quadruped bounding using pretrained neural networks by Zhicheng Wang et al.,https://***/10.1049/csy2.12062.

关键词： legged locomotion reinforcement learning robot learning

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Multi-Destination Cooperative Task Offloading in Blockchain-Based Vehicular Edge Computing Networks

Multi-Destination Cooperative Task Offloading in Blockchain-...

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2023 IEEE International Conference on Unmanned systems, ICUS 2023

作者： Lang, Ping Tian, Daxin Duan, Xuting Zhou, Jianshan State Key Lab of Intelligent Transportation System Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China School of Transportation Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798350316308

As a novel computing paradigm, the Vehicular Edge Computing (VEC) network provides an additional avenue for onboard task execution for connected and automated vehicles (CAVs) in unmanned systems. In a VEC network, CAVs can offload tasks to different external servers for execution and obtain results. However, existing task offloading studies only focus on the one-to-one offloading of onboard tasks to edge servers, ignoring the requirements of parallel task execution and security. In this paper, we propose a blockchain-based multi-destination cooperative task offloading architecture in a VEC network. Based on this architecture, we analyze the task offloading and blockchain models and formulate a multi-destination cooperative task offloading optimization problem. Finally, we compare the performance of different multi-destination task offloading methods in simulations and demonstrate the effectiveness of the proposed architecture and optimization. © 2023 IEEE.

关键词： Blockchain

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GNSS/IMU Integrated Navigation Methods with NLOS Mitigation 24

GNSS/IMU Integrated Navigation Methods with NLOS Mitigation

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24th COTA International Conference of Transportation Professionals: Resilient, intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Zuo, Yang Duan, Xuting Xia, Haiying Zhou, Jianshan School of Transportation Science and Engineering Beihang Univ. Beijing China State Key Lab of Intelligent Transportation System Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China Zhongguancun Laboratory Beijing China Key Laboratory of Operation Safety Technology on Transport Vehicles Ministry of Transport Beijing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

With the development of computer technology, intelligent vehicles have become a popular orientation at present. This paper provides a solution for the traditional GNSS/IMU integrated navigation to mitigate the influence of non-line-of-sight (NLOS) environments and achieve high-precision navigation. The LOS/NLOS switching is treated as a transition in a Markov chain, and the DIMM filtering is applied to obtain GNSS-filtered data free from the influence of NLOS. GNSS/IMU integrated navigation is loose coupling in that the method combines IMU information with processed GNSS measurement using the ESKF (Error-state Kalman Filter) to achieve accurate target tracking and positioning by utilizing the state difference as the state variable. Simulation results demonstrate that the proposed method significantly improves tracking and positioning accuracy by effectively mitigating NLOS effects compared to traditional methods. This research provides an effective solution for real-world autonomous vehicle navigation systems and optimizes the city driving experience. © ASCE.

关键词： Markov chains

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