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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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Autonomous Traffic Prediction for LEO Satellite-Based IoT Based on Satellite Spatiotemporal Features Mapping

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IEEE Internet of Things Journal 2025年

作者： Gong, Lizeng Chen, Quan Yang, Lei Yin, Zhenglong Wang, Yi National University of Defense Technology State Key Laboratory of Space System Operation and Control College of Aerospace Science and Engineering Changsha410073 China Nanjing Research Institute of Electronics Technology Nanjing210013 China

The traffic prediction method for Low Earth Orbit (LEO) satellite-based Internet of Things (IoT) provides prior conditions for addressing challenges in resource allocation and management of LEO satellite-based IoT. However, traditional methods rely on the pre-generation of terrestrial centers, leading to substantial computational complexity and delays when applying prediction results to LEO satellite-based IoT. Therefore, achieving autonomous LEO satellite-based IoT traffic prediction is essential. Unlike the spatiotemporal features of terrestrial IoT, LEO satellite-based IoT traffic is influenced by both satellite dynamics and terrestrial user behavior. Fortunately, real IoT traffic information can be shared between adjacent satellites through Inter-satellite Links (ISL). Inspired by the above, this paper proposes, for the first time, an autonomous LEO satellite-based IoT traffic prediction method. A Spatiotemporal Fusion Neural Network (SFNN) employing a four-layer hybrid neural network architecture is designed to accommodate the unique spatiotemporal features of LEO satellite-based IoT traffic. The simulation results demonstrate that the proposed method has low computational complexity and achieves a better prediction performance than the five baseline methods in LEO constellations. Further simulations demonstrate that the proposed method achieves higher accuracy in large-scale LEO constellations, and the algorithm remains applicable under ISL instability and satellite failure conditions. © 2014 IEEE.

关键词： Resource allocation

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Aggregation Modeling of system Frequency Response Under Inertia control of Grid-following Direct-drive Wind Turbine

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Dianli Xitong Zidonghua/Automation of Electric Power systems 2025年第10期49卷 39-48页

作者： Jiang, Chao Yang, Dongfeng Guo, Shujia Liu, Xiaojun Zhou, Shuyu Cao, Zhichong Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China School of Automation and Electrical Engineering Zhejiang University of Science and Technology Hangzhou310023 China State Grid Jilin Electric Power Research Institute Changchun130000 China

The inertia control of grid-following direct-drive wind turbines significantly influences the system frequency response pattern afrer disturbances. However, current research has not clearly identified the dominant response link of direct-drive wind turbines in frequency regulation, while the modeling is too complicated to be suitable for frequency characteristic analysis. Therefore, the linearized models under inertia control are derived for two typical types of direct-drive wind turbines according to the aerodynamic equations, generator models, power control link, and control circuit structure. The fast physical process of current control-boost circuit/stator voltage dynamic loop is clearly understood and reasonably ignored. It is revealed that the two types of direct-drive wind turbines have a common frequency response mechanism which can be described as the cascade effect of the speed regulator-wind rotor motion equation. Furthermore, combined with the frequency response model of synchronous unit, the aggregation model of system frequency response under the inertia control of grid-following direct-drive wind turbines is constructed, and the aggregation model is reduced to a second-order model by the balance truncation method for analytical calculation of frequency extremes. The accuracy and applicability of the aggregation model and its reduced-order model are verified by MATLAB/Simulink simulation, and the influence of control parameters and system states on frequency dynamic characteristics and stability margin is analyzed. © 2025 Automation of Electric Power systems Press. All rights reserved.

关键词： Electric power system control

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Concept-Level Semantic Transfer and Context-Level Distribution Modeling for Few-Shot Segmentation

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IEEE Transactions on Circuits and systems for Video Technology 2025年

作者： Luo, Yuxuan Chen, Jinpeng Cong, Runmin Ip, Horace Ho Shing Kwong, Sam City University of Hong Kong Department of Computer Science Hong Kong Shandong University School of Control Science and Engineering Jinan250061 China Ministry of Education Key Laboratory of Machine Intelligence and System Control Jinan250061 China Lingnan University Hong Kong

Few-shot segmentation (FSS) methods aim to segment objects using only a few pixel-level annotated samples. Current approaches either derive a generalized class representation from support samples to guide the segmentation of query samples, which often discards crucial spatial contextual information, or rely heavily on spatial affinity between support and query samples, without adequately summarizing and utilizing the core information of the target class. Consequently, the former struggles with fine detail accuracy, while the latter tends to produce errors in overall localization. To address these issues, we propose a novel FSS framework, CCFormer, which balances the transmission of core semantic concepts with the modeling of spatial context, improving both macro and micro-level segmentation accuracy. Our approach introduces three key modules: (1) the Concept Perception Generation (CPG) module, which leverages pre-trained category perception capabilities to capture high-quality core representations of the target class;(2) the Concept-Feature Integration (CFI) module, which injects the core class information into both support and query features during feature extraction;and (3) the Contextual Distribution Mining (CDM) module, which utilizes a Brownian Distance Covariance matrix to model the spatial-channel distribution between support and query samples, preserving the fine-grained integrity of the target. Experimental results on the PASCAL-5i and COCO-20i datasets demonstrate that CCFormer achieves state-of-the-art performance, with visualizations further validating its effectiveness. Our code is available at ***/lourise/ccformer. © 1991-2012 IEEE.

关键词： Semantic Segmentation

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Two-stage Distributionally robust optimization for hydrogen-IES participation in energy-carbon trading-frequency regulation ancillary services market

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Energy 2025年 328卷

作者： Li, Fei Wang, Dong Guo, Hengdao Liu, Zhan Zhang, Jianhua Lin, Zhifang School of Electrical Engineering and Automation Jiangsu Normal University Jiangsu Xuzhou221116 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangdong Guangzhou510663 China

This study presents a novel hydrogen-Integrated Energy system (HIES) that incorporates hydrogen refinement utilization and participates in the Energy-Carbon Trading Market (CTM)-Frequency Regulation Auxiliary Service Market (FRASM). First, the proposed HIES refines the hydrogen utilization, where the hydrogen produced by surplus electricity is utilized by combustion blending with gas in Combined Heat and Power (CHP) and Gas Boiler (GB), Hydrogen Fuel Cell (HFC), gas synthesis with CO2 and hydrogen storage. Then, multiple markets model, including Energy-FRASM-CTM market are comprehensively and firstly established, where the HIES can aggregate flexible resources to participate in Energy-FRASM, which provide a promising way to reduce operation costs within the CTM. Finally, to mitigate the Renewable Energy (RE) uncertainties within the proposed HIES, the paper implement a two-stage Distributionally Robust Optimization (DRO) method grounded in comprehensive norm ambiguity. A case study is carried out to corroborate the efficacy of the proposed innovations. The results underscore the remarkable performance of hydrogen refinement utilization on RE accommodation, operation costs and carbon emissions. Moreover, the participation in multiple markets can gain the comprehensive effect, which reduce operation costs by 154.47 % within FRASM and carbon emissions by 12.71 % compared to the scenario without CTM. © 2025 Elsevier Ltd

关键词： Hydrogen production

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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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Trigger mechanism and dynamic characteristics of pressure drop oscillation instability within a liquid cooling loop associated with the compressible volume and the condenser

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Applied Thermal engineering 2025年 274卷

作者： Jiang, Erhui Wang, Wen Guo, Yuxiang Xin, Pengfei Miao, Jianyin Zhang, Hongxing Institute of Refrigeration and Cryogenics School of Mechanical Engineering Shanghai Jiao Tong University Shanghai200240 China National Key Laboratory of Spacecraft Thermal Control Beijing Institute of Spacecraft System Engineering China Academy of Space Technology Beijing100094 China

Pressure drop oscillation is an instability phenomenon encountered in liquid cooling loops utilized for electronic thermal management. However, two significant concerns must be addressed with regard to the triggering mechanism and the dynamic characteristics of the pressure drop oscillation instability, which are the compressible volume and the condenser. This study develops a simulation method for the liquid cooling loop system with multiple degrees of freedom, and the simulated results indicate that the upstream compressible volume is a requisite condition for the emergence of pressure drop oscillation instability in the cooling loop. Furthermore, a critical upstream compressible volume is identified. As the heat flux increases from 200 kW/m2 to 400 kW/m2, the critical dimensionless upstream volume is elevated from 0.03 to 0.05. In addition, the combined effect of both upstream and downstream volumes on the flow hydraulic characteristics of the cooling loop is investigated. It can be found that the magnitude of oscillations in the downstream volume is significantly less than those observed in the upstream volume. Moreover, these dynamic oscillations in the downstream volume can be eliminated when it reaches a specific threshold value. The effects of the hydrodynamic characteristics and the internal compressible volume of the condenser are analyzed. It is observed that as both the cooling flux and the hydraulic diameter increase to a specific threshold, the amplitude of the oscillations in the downstream volume increases by 21.4 % and decreases by 88.6 %, respectively. Meanwhile, the internal compressible volume of the condenser contributes to a reduction in the oscillation amplitude and an elevation in oscillation frequency. © 2025 Elsevier Ltd

关键词： Chilling

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Adaptive Artificial Potential Field Ship Motion Planning Based on DDPG

Adaptive Artificial Potential Field Ship Motion Planning Bas...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Chen, Huimin Liu, Chenguang He, Zhibo Zhang, Guoqing Han, Bing State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan430063 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan430063 China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan430063 China Navigation College Dalian Maritime University Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China National Engineering Research Center of Ship & Shipping Control System Shanghai200134 China

ISBN: (纸本)9789819639601

The paper presents a ship motion planning method that adjusts the attractive and repulsive gain parameters of the artificial potential field (APF) algorithm using the deep deterministic policy gradient (DDPG) algorithm, to address the challenges of parameter design and limited adaptability of traditional APF algorithms. This approach leverages the speed advantage of the APF planning algorithm and the exploration capability of the DDPG reinforcement learning algorithm. By optimizing the parameters of APF with DDPG, the local optima problem can be alleviated in complex obstacle environments. Simulation results demonstrate that the proposed motion planning algorithm can generate reasonable trajectories and exhibit strong adaptability in complex obstacle scenarios. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Motion planning

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Research on Integrating Track-Side PV Power Plant into the Railway Traction Power Supply Network 11th

Research on Integrating Track-Side PV Power Plant into the R...

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11th Frontier Academic Forum of Electrical engineering, FAFEE 2024

作者： Xu, Wenhao Tian, Ao’bo An, Xingkun Jin, Zheming School of Electrical Engineering Beijing Jiaotong University Beijing100044 China Key Laboratory of Vehicular Multi-Energy Drive Systems Ministry of Education Beijing Jiaotong University Beijing100044 China Beijing Zongheng Electro-Mechanical Technology Co. Ltd Beijing100094 China State Key Laboratory for Traction and Control System of EMU and Locomotive China Academy of Railway Sciences Corporation Limited Beijing100081 China

ISBN: (纸本)9789819787791

As a major part of the passenger and goods transportation in China, the railway has been greatly deployed and developed. Currently, with a high level of electrification, integrating distributed photovoltaic (PV) and other renewables will be the main potential method to further reduce the energy consumption of the Chinese railway system and to achieve the transition to carbon neutral transportation system. In this paper, the methodology to integrate the track-side PV power plant is discussed. Based on the unique 27.5kV/50Hz single phase power transmission facility of Chinese railway system, a back-to-back dual-feeder interface of the track-side PV power plant is designed and examined with the traction loads of the railway system. The circuit topology and the control are discussed, and the system performance is demonstrated with simulation. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Electric power plant loads

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UW-DNeRF: Deformable Soft Tissue Reconstruction with Uncertainty-Guided Depth Supervision and Local Information Integration

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IEEE Transactions on Medical Imaging 2025年 PP卷 PP页

作者： Shan, Jiwei Zhang, Zixin Li, Hao Hsieh, Cheng-Tai Li, Yirui Wu, Wenhua Wang, Hesheng School of Electronic Information and Electrical Engineering of Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200240 China Shanghai Jiao Tong University State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China

Reconstructing deformable soft tissues from endoscopic videos is a critical yet challenging task. Leveraging depth priors, deformable implicit neural representations have seen significant advancements in this field. However, depth priors from pre-Trained depth estimation models are often coarse, and inaccurate depth supervision can severely impair the performance of these neural networks. Moreover, existing methods overlook local similarities in input sequences, which restricts their effectiveness in capturing local details and tissue deformations. In this paper, we introduce UW-DNeRF, a novel approach utilizing neural radiance fields for high-quality reconstruction of deformable tissues. We propose an uncertainty-guided depth supervision strategy to mitigate the impact of inaccurate depth information. This strategy relaxes hard depth constraints and unlocks the potential of implicit neural representations. In addition, we design a local window-based information sharing scheme. This scheme employs local window and keyframe deformation networks to construct deformations with local awareness and enhances the model's ability to capture fine details. We demonstrate the superiority of our method over state-of-The-Art approaches on synthetic and in-vivo endoscopic datasets. Code is available at: https://***/IRMVLab/UW-DNeRF. © 2025 IEEE.

关键词： Endoscopy

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