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Edge-Assisted Flexible Platooning of Connected and Automated Vehicles Under Traffic Anomaly

IEEE Transactions on Vehicular Technology 2025年

作者： Gao, Fengkun Yang, Bo Chen, Cailian Guan, Xinping Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

The platooning of connected and automated vehicles (CAVs) has the great potential to significantly improve travel experience in terms of safety, comfortableness, and energy efficiency. However, constrained by sensing range and prediction accuracy, the performance of CAV platoon can not be guaranteed in the scenario of mixed traffic consisting of CAVs and human-driven vehicles (HDVs). This is not only due to the uncertainty of HDVs but also related to the occurrence of various traffic anomalies, such as emergency braking and accidents. In this paper, we aim to investigate an efficient control strategy to guarantee the operation of the platoon in mixed traffic, especially in the case of traffic anomalies. To tackle the problem, an edge-assisted platoon control strategy, called E-CACC, is proposed. First, an error-aware flexible tracking policy is designed to adapt to HDV uncertainties and speed prediction errors. Based on the tracking policy, a zone model predictive control (ZMPC) method is then designed to guarantee travel safety and avoid undesired acceleration. Further, a coordination strategy of CAV platoon and roadside unit (RSU) is proposed to prevent the platoon from potential collision in the case of traffic anomalies, where an event-based communication trigger is designed to determine whether and when the platoon establishes communication links with RSU to acquire exogenous sensing data of anomaly segment. Finally, the evaluation results illustrate the effectiveness of the proposed method in improving travel safety and comfortableness. © 1967-2012 IEEE.

关键词： Braking performance

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On the Instability Mechanism of PV-Thermal-Bundled Power system Under Different PV Penetration Ratios

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IEEE Transactions on Power Electronics 2025年

作者： Yan, Yiran Ruan, Xinbo He, Yuying Lin, Zhiheng Chen, Yuhang Nanjing University of Aeronautics and Astronautics Center for More Electrical-Aircraft Power System College of Automation Engineering Nanjing211106 China Hohai University College of Electrical and Power Engineering Nanjing211100 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

In the photovoltaic (PV)-thermal-bundled power system, the increasing PV penetration poses instability risk. Through establishing the small-signal model and solving the eigenvalues of return ratio matrix, the system stability can be evaluated with the generalized Nyquist stability criterion. However, the expressions of eigenvalues are irrational functions, which leads to the complexity of analyzing the system stability and the difficulties to accurately reveal the instability mechanism. To address this issue, the stability analysis method based on the admittance matrix elements is proposed, which does not need to calculate the eigenvalues of return ratio matrix, thus simplifying the stability analysis. In addition, this method can describe the system stability margin clearly. With this stability analysis method, the stability of the PV-thermal-bundled power system is clarified under different renewable penetration ratios, and the causes of the system instability are investigated. Finally, the hardware-in-the-loop results confirm the effectiveness of the proposed stability analysis method and the accuracy of the stability analysis results. © 1986-2012 IEEE.

关键词： Electric power system stability

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Analysis of Spiral Scanning Amplitude Modulation Methods for Two-photon Endomicroscopy 10

Analysis of Spiral Scanning Amplitude Modulation Methods for...

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10th Symposium on Novel Optoelectronic Detection Technology and Applications

作者： Cui, Haodong Wang, Conghao Liu, Huilan Zhang, Xiulei Hu, Yanhui Fu, Qiang Wu, Runlong Wang, Aimin Feng, Lishuang School of Instrumentation and Optoelectronic Engineering Beihang University Beijing100191 China Beijing100191 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Beijing Transcend Vivoscope Biotech Co. Ltd. Beijing100049 China Beijing Key Laboratory for Optoelectronics Measurement Technology Beijing Information Science and Technology University Beijing100192 China State Key Laboratory of Advanced Optical Communication System and Networks Department of Electronics Peking University Beijing100871 China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

Two-photon endomicroscopy is a high-resolution label-free imaging technique for biological tissues. This paper analyzes sinusoidal and triangular amplitude modulation methods for spiral scanning two-photon endomicroscopy. In the theoretical modeling section, the mathematical model of PZT fiber scanner is established, and the distortion of fiber scanning trajectory caused by two amplitude modulated sine wave signals is simulated and evaluated. In the experimental verification section, a test platform is constructed to measure the scanning trajectory distortion driven by these amplitude modulated sine wave signals. Finaly, spiral scanning two-photon endomicroscopic imaging of in-vivo GFP mice brain tissues using sinusoidal amplitude modulated signals are demonstrated. © 2025 SPIE.

关键词： Amplitude modulation

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Data-driven approach for optimizing the Czochralski process and predictive modeling: A finite element and machine learning analysis

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International Journal of Advanced Manufacturing Technology 2025年 1-11页

作者： Maurya, Swami Nath Dezfoli, Amir Reza Ansari Lin, Li-Shang Department of Intelligent Automation Engineering National Chin-Yi University of Technology Taichung Taiwan Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taiwan Micro Precision System Research & Development Section Metal Industries Research & Development Centre Kaohsiung Taiwan

The ever-growing demand for semiconductors, fueled by advancements in integrated circuits (ICs), necessitates innovative approaches for efficient and high-quality growth of large-scale silicon single crystals using the Czochralski (CZ) method. In this context, machine learning emerges as a transformative tool to predict and optimize the complex, nonlinear CZ silicon growth process. A novel hybrid finite element method–machine learning (FEM-ML) model is proposed to enhance the accuracy of thermal stress predictions. The FEM simulation, incorporating 3D Navier–Stokes and thermal elastic stress equations, was used to evaluate the effects of four key process features: insulation thermal conductivity (0.184–0.736 W/m·K), melt level (448–672 mm), crucible rotation speed (1–7.5 rpm), and crystal rotation speed (7.5–12.5 rpm). Then, machine learning analyses including LASSO regression for feature selection and regression decision trees for predictive modeling, achieving a high coefficient of determination (R² > 0.97) through tenfold cross-validation is employed. Results identified insulation thermal conductivity as the most significant factor, accounting for 75.4% of predictive performance, while melt level had negligible impact. Individual Conditional Expectation (ICE) results highlighted non-linear dependencies, such as the sharp increase in thermal stress with crucible rotation speeds up to 2.4 rpm. The hybrid model demonstrated superior performance in capturing key parameter interactions and predicting thermal stress distributions. This work underscores the potential of hybrid FEM-ML approaches for addressing complex industrial challenges in crystal growth. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Czochralski process Finite element method (FEM) Hybrid modeling Machine learning models Thermal stress prediction

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Preserving Location Privacy of IoT Devices in Heterogeneous Edge Computing Architecture Through Deniability-Based Authentication

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IEEE Transactions on Consumer Electronics 2025年

作者： Ali, Ikram Li, Jianqiang Chen, Jie Chen, Yong Ullah, Shamsher Wakeel, Abdul Shenzhen University National Engineering Laboratory of Big Data System Computing Technology Shenzhen518060 China Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China National University of Sciences and Technology Military College of Signals Department of Electrical Engineering Islamabad Pakistan

Edge computing moves cloud services closer to consumer Internet of Things (IoT) devices, reducing latency and bandwidth usage. This setup enables faster responses but also introduces new security challenges, particularly concerning location privacy when sender and receiver use different security techniques. The authentication process in such architectures can expose the location of IoT devices. To address this issue, researchers have proposed various privacy-preserving schemes. However, these are computationally heavy for IoT devices. To tackle this issue, we propose two novel heterogeneous deniable authentication schemes: HDA-IoT-I and HDA-IoT-II. These schemes use public-key infrastructure and identity-based cryptography to protect the location privacy of IoT devices in heterogeneous edge computing environments. Our schemes enable the designated edge device to verify the source of a message without being able to prove its origin to a third party, thus preserving privacy. Additionally, they incorporate a batch verification method, which speeds up the verification of multiple deniable authenticators. The proposed schemes are formally proven secure in the random oracle model based on the hardness assumption of elliptic curve inverse computational Diffie-Hellman problem. The performance evaluation demonstrate that our schemes significantly enhance computational and communication efficiency, making them suitable for IoT devices. © 2025 IEEE.

关键词： Differential privacy

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Transient Stability Analysis and Fault Clearing Angle Estimation of VSG Based on Domain of Attraction Estimated by Trajectory Reversing Method

arXiv

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arXiv 2025年

作者： Lyu, Jiayue Fang, Tianzhi Lin, Zhiheng Han, Jingxue Zhu, Yantao Center for More-Electrical-Aircraft Power System College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada

The virtual synchronous generator (VSG), with the analogous nonlinear power-angle relationship to the synchronous generator (SG), has attracted much attention as a promising solution for converter-based power systems. In this paper, a large signal model of the grid-connected VSG is first established. The trajectory reversing method (TRM) is then introduced to estimate the domain of attraction (DOA) of VSG. Subsequently, the transient instability mechanism is revealed in detail based on the estimated DOA boundary. The impacts of system parameters on the DOA range are further investigated. It is found that loss of synchronization (LOS) occurs if the system trajectory lies outside the post-fault DOA range. In scenarios where no equilibrium points exist after a grid fault, system stability can be reestablished only when the fault clearing angle (FCA) does not exceed the critical clearing angle (CCA). Finally, the CCA derived from the DOA and that from the conventional equal area criteria (EAC) are compared. The results show that CCA obtained by our solution has a higher accuracy. Time-domain simulations are performed to verify the effectiveness of the proposed transient stability analysis method of grid-connected VSG. Copyright © 2025, The Authors. All rights reserved.

关键词： Transient stability

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A Switched Neural Process for Long-term Postprandial Glucose Trajectory Prediction based on Insulin Sensitivity Estimation

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Chen, Jing Shi, Dawei Cai, Deheng Liu, Wei Ji, Linong Shi, Ling Beijing Institute of Technology MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing China Peking University People’s Hospital Department of Endocrine and Metabolism Beijing China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Kowloon Hong Kong

Advanced sensing technology has enabled the real-time monitoring of blood glucose (BG), making it possible to explore the BG prediction problem based on continuous observations. In this work, we propose a novel switched neural process (NP) approach for long-term postprandial BG prediction, which has the probabilistic inference ability conditioned on preprandial BG measurements. Distinct representative NP models are constructed to capture the nonlinear BG dynamics based on a designed indicator. This indicator is developed to estimate insulin sensitivity (IS) at meal time by using physiological models, in which the effect of preprandial BG variation on IS estimation is evaluated. Besides, a robust model switching mechanism is designed to determine the appropriate NP model for prediction. The effectiveness of the proposed method is illustrated through the comparative results by using both the in silico data from the US Food and Drug Administration (FDA)-accepted UVA/Padova type 1 diabetes mellitus (T1DM) simulator and the clinical data from 47 T1DM subjects. The obtained results indicate that the proposed method outperforms existing methods especially for 3h and 4h prediction, which shows promising potential in predicting postprandial BG levels. © 1963-2012 IEEE.

关键词： Glucose

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Exploring Eye-tracking based Biomarkers to Assess Cognitive Abilities in Autistic Children: A Feasibility Study

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Zhang, Hanlin Hu, Chunchun Wang, Zhiyong Zhou, Bingrui Wang, Xinming Nie, Wei Ye, Qinyi Lin, Ruihan Xu, Xiu Liu, Honghai Children's Hospital of Fudan University Department of Child Health Care Shanghai201102 China Harbin Institute of Technology State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Shenzhen518055 China Peng Cheng Laboratory Shenzhen518000 China

Cognitive assessment can reveal a person's cognitive processing and behavioral patterns, making it an indispensable component of autism intervention and prognosis. Existing machine-assisted cognitive assessment methods primarily focus on children's performance outcomes, overlooking distinctive behavioral models, particularly characteristics of eye movement behavior, which have been demonstrated as the most direct indicators of cognitive abilities. In this study, we explore eye-tracking biomarkers for assisting cognitive assessment through a series of meticulously designed multi-level human-computer interaction protocols, encompassing three cognitive abilities: pairing and categorization, emotion recognition, and social interaction. A platform embedded with an eye-tracking module has been developed to reliably collect and analyze eye movement data, even in the presence of unrestricted large head movements in children. Experimental results indicate that there are significant group differences between autism and typically developing children in the eye-tracking features of total fixation duration, response latency, time to first fixation, mean fixation duration, and visit count in the absence of significant intergroup differences in the Wechsler Preschool and Primary Scale of Intelligence (WPPSI) and Wechsler Intelligence Scale for Children (WISC) assessment results. In addition, certain eye movement features in each group are correlated with WPPSI/WISC scale scores, enabling clinical cognitive assessments within each group based on these eye movement features. This study suggests that using eye-tracking features as biomarkers to assist detailed cognitive assessments holds significant potential for the intervention and prognosis of autism. © 2013 IEEE.

关键词： Diseases

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Sharing energy in wider area: A two-layer energy sharing scheme for massive prosumers

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Applied Energy 2025年 392卷

作者： Su, Yifan Yang, Peng Kang, Kai Wang, Zhaojian Qi, Ning Liu, Tonghua Liu, Feng State Key Laboratory of Power Transmission Equipment Technology School of Electrical Engineering Chongqing University Chongqing400044 China School of Electronics and Information Xi'an Polytechnic University Xi'an710048 China State Key Laboratory of Power System Operation and Control Department of Electrical Engineering Tsinghua University Beijing100084 China Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Automation Shanghai Jiao Tong University Shanghai200240 China Department of Earth and Environmental Engineering Columbia University New YorkNY10027 United States

The popularization of distributed energy resources transforms end-users from consumers into prosumers. Inspired by the sharing economy principle, energy sharing markets for prosumers are proposed to facilitate the utilization of renewable energy. This paper proposes a novel two-layer energy sharing market for massive prosumers, which can promote social efficiency by wider-area sharing. In this market, there is an upper-layer energy sharing market (U-ESM) in the distribution system and numerous lower-layer energy sharing markets (L-ESMs) in local communities. Prosumers in the same community share energy with each other in the L-ESM, which can be uncleared. The energy surplus and shortage of L-ESMs are cleared in the U-ESM. Thanks to the wider-area two-layer structure, the market outcome is near-social-optimal in large-scale systems. However, the proposed market forms a complex mathematical program with equilibrium constraints (MPEC). To solve the problem, we propose an efficient and hierarchically distributed bidding algorithm. The proposed two-layer market and bidding algorithm are verified on the IEEE 123-bus system with 11,250 prosumers, which demonstrates the practicality and efficiency for large-scale markets. © 2025 Elsevier Ltd

关键词： Game theory

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A Stackelberg Game Approach for Signal Temporal Logic Control Synthesis with Uncontrollable Agents

arXiv

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arXiv 2025年

作者： Cui, Bohan Yu, Xinyi Giua, Alessandro Yin, Xiang Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai200240 China Thomas Lord Department of Computer Science University of Southern California Los AngelesCA90089 United States Department of Electrical and Electronic Engineering University of Cagliari Cagliari09123 Italy

In this paper, we investigate the control synthesis problem for Signal Temporal Logic (STL) specifications in the presence of uncontrollable agents. Existing works mainly address this problem in a robust control setting by assuming the uncontrollable agents are adversarial and accounting for the worst-case scenario. While this approach ensures safety, it can be overly conservative in scenarios where uncontrollable agents have their own objectives that are not entirely opposed to the system’s goals. Motivated by this limitation, we propose a new framework for STL control synthesis within the Stackelberg game setting. Specifically, we assume that the system controller, acting as the leader, first commits to a plan, after which the uncontrollable agents, acting as followers, take a best response based on the committed plan and their own objectives. Our goal is to synthesize a control sequence for the leader such that, for any rational followers producing a best response, the leader’s STL task is guaranteed to be satisfied. We present an effective solution to this problem by transforming it into a single-stage optimization problem and leveraging counterexample guided synthesis techniques. We demonstrate that the proposed approach is sound and identify conditions under which it is optimal. Simulation results are also provided to illustrate the effectiveness of the proposed framework. © 2025, CC BY.

关键词： Control system synthesis

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