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IEEE Transactions on intelligent Vehicles 2024年 1-15页

作者： Xie, Yizhou Zhang, Yong Yin, Chengliang Huang, Hongcheng dai, Kunpeng National Engineering Laboratory for Automotive Electronic Control Technology Shanghai Jiao Tong University Shanghai China Shanghai Intelligent and Connected Vehicle R&D Center Shanghai China

Scenario-based test is recognized as an effective way to evaluate and verify the Safety of the Intended Functionality (SOTIF) of an autonomous driving system, and a critical-scenario is beneficial to foreground the system defect more obviously. However, for the state of the art, time consumption of critical-scenario-search in a real-time test is still high, especially for searching critical-scenarios with dissimilarities, which assists designers in discovering more failure modes of autonomous in limited time. To address above challenges, in this paper, we improve our previous scenario-searching approach considering dissimilarity assessments in iterations, we present a searching framework which combines control and exploration approaches, and implement the efficient evolution of scenarios with a backward target-tree search. We carry out a Vehicle-in-the-Loop (VIL) test with a real vehicle to verify our new approach, and the results show that the approach is able to search for scenarios directly against a black-box system in a real-time test, and achieve scenarios with both high criticality and dissimilarity, including unknown-unsafe cases. In our time-limited test, compared with different methods, our approach can achieve 1.9 times the amount of diversified scenarios with the almost same (slightly higher) criticality, either achieve 1.5 times the amount attached with 75% improvement in criticality. IEEE

关键词： real time systems

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A Line Complex-Based Evolutionary Algorithm for Many-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1150-1167页

作者： Liang Zhang Qi Kang Qi deng Luyuan Xu Qidi Wu the Department of Control Science and Engineering Tongji UniversityShanghai 201804 the Jiangsu Province Support Software Engineering R&D Center for Modern Information Technology Application in Enterprise Suzhou 215104China the Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 200092China

In solving many-objective optimization problems(MaO Ps),existing nondominated sorting-based multi-objective evolutionary algorithms suffer from the fast loss of selection *** candidate solutions become nondominated during the evolutionary process,thus leading to the failure of producing offspring toward Pareto-optimal front with *** we find a more effective way to select nondominated solutions and resolve this issue?To answer this critical question,this work proposes to evolve solutions through line complex rather than solution points in Euclidean ***,Plücker coordinates are used to project solution points to line complex composed of position vectors and momentum *** position vectors of the solution points,momentum vectors are used to extend the comparability of nondominated solutions and enhance selection ***,a new distance function designed for high-dimensional space is proposed to replace Euclidean distance as a more effective distancebased *** on them,a novel many-objective evolutionary algorithm(MaOEA)is proposed by integrating a line complex-based environmental selection strategy into the NSGAⅢ*** proposed algorithm is compared with the state of the art on widely used benchmark problems with up to 15 *** results demonstrate its superior competitiveness in solving MaOPs.

关键词： Environmental selection line complex many-objective optimization problems(MaOPs) Plücker coordinate

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Open-source dataset of vehicle state for an electric vehicle on a low-adhesion road

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Science China(Information Sciences) 2022年第3期65卷 258-259页

作者： Shuo CAI Haitao dING Yunfeng HU Lin ZHANG Qin LI Hong CHEN State Key Laboratory of Automotive Simulation and Control Jilin University Department of Control Science and Engineering Jilin University School of Automotive Studies Tongji University Collaborative Innovation Center of Electric Vehicles in Beijing Beijing Institute of Technology GAC R&D Center

This study demonstrates and opens for academic research six sets of electric vehicle data collected during experiments on a low-adhesion road. The 11-dimensional data were collected from a small, single-motor SUV with front-wheel *** data collected for vehicles on low-adhesion roads are crucial for research on system dynamics modeling,stability control system design, and vehicle state estimation. Indeed, all vehicle control systems must be validated on low-adhesion roads, including vehicle models,

关键词： vehicle experimental data dynamics modeling state estimation control system design low adhesion road

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Axial Assembled Correspondence Network for Few-Shot Semantic Segmentation

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 711-721页

作者： Yu Liu Bin Jiang Jiaming Xu School of Automation Science and Engineering South China University of TechnologyGuangzhou 510640 R&D Center of Precision Electronic Manufacturing Technology Guangzhou Institute of Modern Industrial Technologyand also with the High Performance Motor and Intelligent Control Engineering Technology Research Center of Guangdong ProvinceGuangzhou 511458China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510640China IEEE

Few-shot semantic segmentation aims at training a model that can segment novel classes in a query image with only a few densely annotated support *** remains a challenge because of large intra-class variations between the support and query *** approaches utilize 4d convolutions to mine semantic correspondence between the support and query ***,they still suffer from heavy computation,sparse correspondence,and large *** propose axial assembled correspondence network(AACNet)to alleviate these *** key point of AACNet is the proposed axial assembled 4d kernel,which constructs the basic block for semantic correspondence encoder(SCE).Furthermore,we propose the deblurring equations to provide more robust correspondence for the aforementioned SCE and design a novel fusion module to mix correspondences in a learnable *** on PASCAL-5~i reveal that our AACNet achieves a mean intersection-over-union score of 65.9%for 1-shot segmentation and 70.6%for 5-shot segmentation,surpassing the state-of-the-art method by 5.8%and 5.0%respectively.

关键词： Artificial intelligence computer vision deep convolutional neural network few-shot semantic segmentation

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control, Modeling and Stability Analysis of drU-based Grid-forming Converter

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Chinese Journal of Electrical engineering 2025年第1期11卷 83-92页

作者： Wencong Wu Minzhi Wang Liang Tu Haiqing Cai Guanglei Yan Xiaohui Qu Haohan Gu Wei Chen State Key Laboratory of HVDC China Southern Power GridGuangzhou 510663China National Energy Power Grid Technology R&D Center Guangzhou 510663China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power Systems China Southern Power GridGuangzhou 510663China CSG Key Laboratory for Power System Simulation China Southern Power GridGuangzhou 510663China School of Electrical Engineering Southeast UniversityNanjing 210096China

diode rectifier unit(drU)-based high-voltage direct current(HVdC)transmissionsystems areeffectivein achieving the stableandeconomical operation of offshore *** theuncontrollable characteristicsof drUs,a grid-forming(GFM)strategy forwind-turbine converters isnecessary to support offshore AC voltageand ***,the active power-synchronization control in traditional GFM converters is unsuitable for drU-based GFM ***,the stability issue for drU-based HVdC systems involving drU-based GFM and grid-following(GFL)converters has not yet been *** solve these issues,this study begins with the characteristics of a drU-based HVdC system and presents a control scheme for drU-based GFM converters for power ***,the dq-frame impedance model of the drU-based GFM converteris proposed for the stability analysis of the entire HVdC ***,a simulation platform is built to verify the model accuracy and system stability.

关键词： diode rectifier unit offshore wind-powergeneration grid-forming converter impedance model stabilityanalysis

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Nonlinear Moving Horizon Longitudinal control for Electric Vehicles Based on Tire Force Prediction in Snow Environment 41

Nonlinear Moving Horizon Longitudinal Control for Electric V...

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第41届中国控制会议

作者： Chang Liu Yang Liu Xu Zhao Qikun dai Qingyu Meng Hongyan Guo China FAW Group Corporation R&D Center Department of Control Science and Engineering Jilin University State Key Laboratory of Automotive Simulation and Control Jilin university

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper uses a nonlinear longitudinal control method for distributed drive electric vehicles（ddEV） to solve the safety problem of ddEV when driving on snow-covered ***,an optimal slip control scheme based on tire force prediction is ***,use the Burckhardt tire model to draw μ-κ,curve,use the magic formula to draw F-κcurve,get the maximum longitudinal tire force that can be provided under different road types *** calculate the tire force required for stable driving of the vehicle,predict the state of the vehicle in *** paper aims at the situation that tire force is not saturated during the driving process of the vehicle,the lower layer uses the nonlinear model predictive control（NMPC）algorithm to design the optimal slip *** main purpose is to control the torque of the four wheels simultaneously so that the slip rate can follow the optimal value,thereby effectively preventing the wheels from over-slipping during driving or locking during braking,enhancing the maneuverability and stability of the vehicle in extreme ***,the dynamic simulation software CarSim is used for simulation verification under various working *** results show that the controller designed in this paper can effectively track the optimal slip value of each wheel,play a driving assistance function,and realize the multi-objective requirements of "safety-power-comfort".

关键词： distributed drive Electric Vehicle Tire Force Prediction Slip control Nonlinear Model Predictive control

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Multi-Channel Based on Attention Network for Infrared Small Target detection

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 414-427页

作者：张彦军王碧云蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Shanghai Institute of Aerospace Control Technology Shanghai 201109China Infrared Detection Technology R&D Center of China Aerospace Science and Technology Corporation Shanghai 201109China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

Infrared detection technology has the advantages of all-weather detection and good concealment,which is widely used in long-distance target detection and tracking ***,the complex background,the strong noise,and the characteristics of small scale and weak intensity of targets bring great difficulties to the detection of infrared small targets.A multi-channel based on attention network is proposed in this paper,aimed at the problem of high missed detection rate and false alarm rate of traditional algorithms and the problem of large model,high complexity and poor detection performance of deep learning ***,given the difficulty in extracting the features of infrared multiscale and small dim targets,the multiple channels are designed based on dilated convolution to capture multiscale target ***,the coordinate attention block is incorporated in each channel to suppress background clutters adaptively and enhance target *** addition,the fusion of shallow detail features and deep abstract semantic features is realized by synthesizing the contextual attention fusion ***,it is verified that,compared with other state-of-the-art methods based on the datasets SIrST and MdFA,the proposed algorithm further improves the detection effect,and the model size and computational complexity are smaller.

关键词： infrared image small target detection deep learning attention mechanism feature fusion

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T-KMGA a Two-Stage Approach for Collaborative Task Allocation with Air-Sea Heterogeneous Autonomous Unmanned Systems

T-KMGA a Two-Stage Approach for Collaborative Task Allocatio...

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International Conference on Guidance, Navigation and control, ICGNC 2024

作者： Chen, Xinyu Qi, Juntong Peng, Yan Ping, Yuan Wu, Chong Wang, Mingming Institute of Artificial Intelligence Shanghai University Shanghai China EFY Intelligent Control (Hainan) Technology Co. Ltd. R&D Center Hainan China Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Institute of Electrical and Information Engineering Tianjin University Tianjin China

ISBN: (纸本)9789819622634

This paper introduces a two-stage method, combining K-means++ and a modified genetic algorithm (T-KMGA), aimed at simplifying collaborative task allocation complexity and enhancing operational efficiency within heterogeneous autonomous task allocation unmanned systems. The proposed T-KMGA constructs a solution for task allocation through two stages: task clustering and path planning. In the first stage, we develop a modified K-means++ clustering model sensitive to unmanned aerial vehicle (UAV) endurance radii to tackle the increasing complexity of task allocation as the scale of tasks grows. In the second stage, we propose a modified genetic algorithm to plan paths for multiple UAVs and a single unmanned surface vehicle (USV) to minimize the execution time of cooperative tasks. We adopt a virtual node encoding method to solve the multiple UAV task allocation problem in the second stage. The effectiveness of the proposed approach is assessed through simulation experiments. The results demonstrate that the proposed method can significantly reduce task execution time and computational consumption, especially in large-scale task scenarios. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： air-sea heterogeneous unmanned systems cooperative task allocation genetic algorithms k-means++ Task allocation

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Low-Frequency Structure-Borne Noise Identification Based on FastICA-WPA Algorithm 8

Low-Frequency Structure-Borne Noise Identification Based on ...

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8th IEEE International Conference on Advanced robotics and Mechatronics, ICArM 2023

作者： Liu, Qiang Zhu, Jianxin Sunward Intelligent Equipment Co. Ltd. National Enterprise R&D Center Hunan Research Center of Geotechnical Construction Equipment and Control Engineering Changsha410100 China Central South University State Key Laboratory for High Performance Complex Manufacturing Changsha410100 China

ISBN: (纸本)9798350300178

Low-frequency structure-borne noise in enclosed space is easy to produce booming sensation, which seriously affects the auditory comfort. But its sources are complex and the transmission path is strongly coupled, meanwhile it is difficult to be directly measured by experiments, so making identification difficult. To address the problem of decoupling multi-source mixed signals, this paper proposes a low-frequency structure-borne noise identification method based on FastICA-WPA algorithm. Using FastICA (Fast algorithm of Independent Component Analysis) algorithm to identify the structure-borne noise components in single-channel noise, then WPA (Wavelet Packet Analysis) method is applied to identify the low-frequency components of structure-borne noise. Finally decouple the contribution of low-frequency structure-borne noise. This method is applied to an intelligent excavator cab. The correctness of the method is verified by applying vibration signal correlation analysis. The identification algorithm lays the foundation for developing a low-frequency structure-borne noise control strategy. © 2023 IEEE.

关键词： Independent component analysis

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Estimation of Tire-road Friction Coefficient Based on the Unitire Model 6

Estimation of Tire-Road Friction Coefficient Based on the Un...

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6th CAA International Conference on Vehicular control and Intelligence, CVCI 2022

作者： Gong, Chaofan Zong, Changfu Lu, dang Kaku, Chuyo Zhang, dong Jilin University The State Key Laboratory of Automotive Simulation and Control Changchun China Jiangsu Chaoli Electric Co. Ltd R&d Center Danyang China Brunel University London The Department of Mechanical and Aerospace Engineering London United Kingdom

ISBN: (数字)9781665453745

ISBN: (纸本)9781665453745

The rapid development of autonomous driving technologies places higher demands on the accurate estimation of tire-road friction coefficient (TrFC) in vehicle motion and vehicle dynamics control. A tire model must be built to accurately describe the friction conditions between the tire and road surface. The Unitire model not only holds the advantage of highly accurate representation of tire properties under various complex situations, but it also takes complete account of the relationship between TrFC and road conditions, tire load, and slip speed through dynamic friction characteristics. Therefore, a method based on the Unitire model for TrFC estimation is proposed in this paper. A normalized force calculation method for the Unitire model is proposed subsequently. The simulation experiment results show that the proposed method performs better than the general tire model, which indicates the great potential of the Unitire model for TrFC estimation. © 2022 IEEE.

关键词： Tires

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