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Stability of connected and automated vehicles platoon considering communications failures

Chinese Physics B 2023年第7期32卷 598-609页

作者：刘润坤于海洋任毅龙崔志勇 School of Transportation Science and Engineering Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety ControlBeihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing 100191China

As a form of a future traffic system,a connected and automated vehicle(CAV)platoon is a typical nonlinear physical *** can communicate with each other and exchange ***,communication failures can change the platoon system *** characterize this change,a dynamic topology-based car-following model and its generalized form are proposed in this ***,a stability analysis method is ***,taking the dynamic cooperative intelligent driver model(DC-IDM)for example,a series of numerical simulations is conducted to analyze the platoon stability in different communication topology *** results show that the communication failures reduce the stability,but information from vehicles that are farther ahead and the use of a larger desired time headway can improve ***,the critical ratio of communication failures required to ensure stability for different driving parameters is studied in this work.

关键词： connected and automated vehicle car-following model communication failures string stability

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Overview of Intrusion Detection in Smart Substation 10

Overview of Intrusion Detection in Smart Substation

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10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

作者： Li, Zecun Ma, Rongkuan Xie, Yaobin Lu, Li State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Shangu Cyber Security Technology Co. Ltd Zhengzhou China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

The development of Cyber-Physical Fusion Technology gradually takes the power grid in the direction of intelligence, making the smart substation a typical cyber-physical fusion system. However, while the introduction of the IEC61850 standard solves the interoperability problem of smart substations, it also brings new types of cybersecurity threats. Therefore, traditional network intrusion detection techniques do not apply to smart substations, and it is particularly important to analyze and summarize the current relevant research on the security of smart substations. The main contribution of this paper is to discuss the security of smart substations in terms of threat behaviors and defense measures. In-depth analysis is carried out from the three attack perspectives of the information domain, physical domain, and cyber-physical intersection domain, and the detection methods, detection objects, and detection evaluation methods for smart substation security are summarized. Finally, the problems to be solved in smart substations and possible future research directions are discussed. © 2022 IEEE.

关键词： Cybersecurity

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Intramolecular Hydrogen Bond Improved Durability and Kinetics for Zinc‑Organic Batteries

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Nano-Micro Letters 2024年第3期16卷 138-148页

作者： Tianjiang Sun Jun Pan Weijia Zhang Xiaodi Jiang Min Cheng Zhengtai Zha Hong Jin Fan Zhanliang Tao Key Laboratory of Advanced Energy Materials Chemistry(Ministry of Education) Renewable Energy Conversion and Storage CenterCollege of ChemistryNankai UniversityHaihe Laboratory of Sustainable Chemical TransformationsTianjin 300071People’s Republic of China School of Physical and Mathematical Sciences Nanyang Technological UniversitySingapore 637371Singapore Shanghai Key Laboratory of Special Artificial Microstructure Materials and Technology School of Physics Science and EngineeringTongji UniversityShanghai 200092People’s Republic of China

Organic compounds have the advantages of green sustainability and high designability,but their high solubility leads to poor durability of zinc-organic ***,a high-performance quinone-based polymer(H-PNADBQ)material is designed by introducing an intramolecular hydrogen bonding(HB)*** intramolecular HB(C=O⋯N-H)is formed in the reaction of 1,4-benzoquinone and 1,5-naphthalene diamine,which efficiently reduces the H-PNADBQ solubility and enhances its charge transfer in *** situ ultraviolet-visible analysis further reveals the insolubility of H-PNADBQ during the electrochemical cycles,enabling high durability at different current ***,the H-PNADBQ electrode with high loading(10 mg cm^(-2))performs a long cycling life at 125 mA g^(-1)(>290 cycles).The H-PNADBQ also shows high rate capability(137.1 mAh g^(−1)at 25 A g^(−1))due to significantly improved kinetics inducted by intramolecular *** work provides an efficient approach toward insoluble organic electrode materials.

关键词： Zn-organic batteries H-PNADBQ polymer Intramolecular hydrogen bond Reduced solubility Improvedπ-conjugated level

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Lateral and Longitudinal Coordinated Control of Intelligent Vehicle Based on High-Precision Dynamics Model under High-Speed Limit Condition

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-18页

作者： He, Zhicheng Gong, Liangke Zhou, Enlin Wei, Baolv Li, Eric Huang, Jin State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle the College of Mechanical and Transportation Engineering Hunan University Changsha China School of Computing Engineering & Digital Technologies Teesside University Middlesbrough U.K School of Vehicle and Mobility Tsinghua University Beijing China

This study focuses on improving the trajectory tracking control for intelligent vehicles in high-speed and large curvature limit conditions. To this end, a high-precision five-degree-of-freedom (5-DOF) dynamics model (HPM) that incorporates suspension characteristics is introduced. Furthermore, a coordinated lateral and longitudinal control system is developed. The lateral model predictive control (MPC) involves two crucial stages: initially, a desired trajectory with associated speed data is generated based on path curvature. Subsequently, using the high-precision 5-DOF dynamics model, an objective function is formulated to minimize the difference between the vehicle's current state and the desired state. This process determines the optimal front wheel steering angle, taking into account vehicle positional constraints and steering limitations. Additionally, a double proportional-integral-derivative (PID) controller for longitudinal control adjusts the throttle and brake pressure based on real-time position and speed data, ensuring integrated control over both lateral and longitudinal movements. The effectiveness of this approach is confirmed through real vehicle testing and simulation. Results show that the high-precision 5-DOF dynamics model markedly enhances the accuracy of vehicle response modeling, and the coordinated control system successfully executes precise trajectory tracking. In extreme scenarios of high-speed and large curvature, the enhanced model substantially improves trajectory accuracy and driving stability, thus promoting safe vehicle operation. IEEE

关键词： Trajectories

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PixelFade: Privacy-preserving Person Re-identification with Noise-guided Progressive Replacement 24

PixelFade: Privacy-preserving Person Re-identification with ...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zhang, Delong Peng, Yi-Xing Wu, Xiao-Ming Wu, Ancong Zheng, Wei-Shi School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangdong Province Key Laboratory of Information Security Technology Guangzhou China

ISBN: (纸本)9798400706868

Online person re-identification services face privacy breaches from potential data leakage and recovery attacks, exposing cloud-stored images to malicious attackers and triggering public concern. The privacy protection of pedestrian images is crucial. Previous privacy-preserving person re-identification methods are unable to resist recovery attacks and compromise accuracy. In this paper, we propose an iterative method (PixelFade) to optimize pedestrian images into noise-like images to resist recovery attacks. We first give an in-depth study of protected images from previous privacy methods, which reveal that the chaos of protected images can disrupt the learning of recovery models. Accordingly, Specifically, we propose Noise-guided Objective Function with the feature constraints of a specific authorization model, optimizing pedestrian images to normal-distributed noise images while preserving their original identity information as per the authorization model. To solve the above non-convex optimization problem, we propose a heuristic optimization algorithm that alternately performs the Constraint Operation and the Partial Replacement Operation. This strategy not only safeguards that original pixels are replaced with noises to protect privacy, but also guides the images towards an improved optimization direction to effectively preserve discriminative features. Extensive experiments demonstrate that our PixelFade outperforms previous methods in resisting recovery attacks and Re-ID performance. © 2024 ACM.

关键词： Differential privacy

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Loc4Plan: Locating Before Planning for Outdoor Vision and Language Navigation 24

Loc4Plan: Locating Before Planning for Outdoor Vision and La...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Tian, Huilin Meng, Jingke Zheng, Wei-Shi Li, Yuan-Ming Yan, Junkai Zhang, Yunong School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangdong Provincial Key Laboratory of Information Security Technology Guangzhou China

ISBN: (纸本)9798400706868

Vision and Language Navigation (VLN) is a challenging task that requires agents to understand instructions and navigate to the destination in a visual environment. One of the key challenges in outdoor VLN is keeping track of which part of the instruction was completed. To alleviate this problem, previous works mainly focus on grounding the natural language to the visual input, but neglecting the crucial role of the agent's spatial position information in the grounding process. In this work, we first explore the substantial effect of spatial position locating on the grounding of outdoor VLN, drawing inspiration from human navigation. In real-world navigation scenarios, before planning a path to the destination, humans typically need to figure out their current location. This observation underscores the pivotal role of spatial localization in the navigation process. In this work, we introduce a novel framework, Locating before Planning (Loc4Plan), designed to incorporate spatial perception for action planning in outdoor VLN tasks. The main idea behind Loc4Plan is to perform the spatial localization before planning a decision action based on corresponding guidance, which comprises a block-aware spatial locating (BAL) module and a spatial-aware action planning (SAP) module. Specifically, to help the agent perceive its spatial location in the environment, we propose to learn a position predictor that measures how far the agent is from the next intersection for reflecting its position, which is achieved by the BAL module. After this locating process, we propose the PSA module to associate visual observations After the locating process, we propose the SAP module to incorporate spatial information to ground the corresponding guidance and enhance the precision of action planning. Extensive experiments on the Touchdown and map2seq datasets show that the proposed Loc4Plan outperforms the SOTA methods. © 2024 ACM.

关键词： Visual languages

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Data quantity governance for machine learning in materials science

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National Science Review 2023年第7期10卷 234-250页

作者： Yue Liu Zhengwei Yang Xinxin Zou Shuchang Ma Dahui Liu Maxim Avdeev Siqi Shi School of Computer Engineering and Science Shanghai University Shanghai Engineering Research Center of Intelligent Computing System Australian Nuclear Science and Technology Organisation School of Chemistry The University of Sydney State Key Laboratory of Advanced Special Steel School of Materials Science and Engineering Shanghai University Materials Genome Institute Shanghai University

Data-driven machine learning(ML) is widely employed in the analysis of materials structure-activity relationships,performance optimization and materials design due to its superior ability to reveal latent data patterns and make accurate ***,because of the laborious process of materials data acquisition,ML models encounter the issue of the mismatch between a high dimension of feature space and a small sample size(for traditional ML models) or the mismatch between model parameters and sample size(for deep-learning models),usually resulting in terrible ***,we review the efforts for tackling this issue via feature reduction,sample augmentation and specific ML approaches,and show that the balance between the number of samples and features or model parameters should attract great attention during data quantity *** this,we propose a synergistic data quantity governance flow with the incorporation of materials domain *** summarizing the approaches to incorporating materials domain knowledge into the process of ML,we provide examples of incorporating domain knowledge into governance schemes to demonstrate the advantages of the approach and *** work paves the way for obtaining the required high-quality data to accelerate materials design and discovery based on ML.

关键词： machine learning data governance data quantity materials science

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Confidence-Guided Feature Alignment for Cloth-Changing Person Re-identification 27th

Confidence-Guided Feature Alignment for Cloth-Changing Pers...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Huang, Sirong Zheng, Huicheng School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education Guangzhou China Guangdong Province Key Laboratory of Information Security Technology Guangzhou China

ISBN: (纸本)9783031781094

Much progress has been made in the field of person re-identification, but changes in clothing have hindered the practical application of long-term person re-identification. Cloth-changing person re-identification (CC-ReID) aims to address this problem, with the main challenge being the extraction of discriminative features unrelated to clothing. Existing methods, which mainly focus on introducing clothing-irrelevant cues such as key points, contours, and 3D shapes, require additional modules for feature extraction, resulting in increased complexity and potential inaccuracies due to dependence on the performance of external models. Few studies directly use the original RGB images to make the model constantly focus on clothing-independent information. In this paper, we propose a Confidence-Guided Feature Alignment Network (CGFA) for CC-ReID. Specifically, we design a confidence module that automatically learns to make confidence adjustments to fine-grained information, prompting the model to mine clothing-independent discriminative features without introducing other modal cues. By transferring knowledge, we encourage the model to learn discriminative identity features that are independent of clothing bias. As a result, the confidence module can be removed during the inference phase. The proposed simple but efficient method uses only RGB modality without additional cues, and can serve as a powerful baseline for CC-ReID to drive future research. Extensive experiments on the CC-ReID datasets demonstrate the effectiveness of the proposed method, which achieves state-of-the-art performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Feature extraction

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Improving CoatNet for Spatial and JPEG Domain Steganalysis

Improving CoatNet for Spatial and JPEG Domain Steganalysis

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Hao Li Xiangyang Luo Yi Zhang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Advanced Computing and Key Laboratory of Cyberspace Situation Awareness of Henan Provinc Zhengzhou China

The covert communication technology represented by image steganography can realize the safe and reliable information transmission over an open network. Steganalysis is an important way to measure the security of steganography. The application of deep learning in the field of steganalysis has begun to emerge and achieved certain results. However, the existing steganalysis methods based on deep learning extract limited global features and the detection accuracy still needs to be improved. Therefore, this manuscript proposes an improving CoatNet for spatial and JPEG domain steganalysis (IMCoatNet). Firstly, the SKAttention structure is used to extract fine-grained features. Then, the convolution layer, Transformer layer and the pyramid squeezed attention is used to capture multi-scale spatial features. Finally, a weighted loss is designed to enhance the expression ability of the model. The results show that compared with the traditional Spatial Rich Model (SRM) method, the classical deep residual network for steganalysis (SRNet), and the latest siamese CNN for steganalysis (SiaStegNet), the detection accuracy of the proposed CoatNet method for WOW steganography is improved by 19.61%, 4.33% and 5.04%, respectively; The proposed IMCoatNet is also superior on JPEG domain detection.

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Automatic protocol reverse engineering for industrial control systems with dynamic taint analysis

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Frontiers of Information Technology & Electronic engineering 2022年第3期23卷 351-360页

作者： Rongkuan MA Hao ZHENG Jingyi WANG Mufeng WANG Qiang WEI Qingxian WANG State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001China Zhejiang University NGICS Platform Hangzhou 310000China

Proprietary(or semi-proprietary)protocols are widely adopted in industrial control systems(ICSs).Inferring protocol format by reverse engineering is important for many network security applications,e.g.,program tests and intrusion *** protocol reverse engineering methods have been proposed which are considered time-consuming,tedious,and ***,automatical protocol reverse engineering methods have been proposed which are,however,neither effective in handling binary-based ICS protocols based on network traffic analysis nor accurate in extracting protocol fields from protocol *** this paper,we present a framework called the industrial control system protocol reverse engineering framework(ICSPRF)that aims to extract ICS protocol fields with high *** is based on the key insight that an individual field in a message is typically handled in the same execution context,e.g.,basic block(BBL)*** a result,by monitoring program execution,we can collect the tainted data information processed in every BBL group in the execution trace and cluster it to derive the protocol *** evaluate our approach with six open-source ICS protocol *** results show that ICSPRF can identify individual protocol fields with high accuracy(on average a 94.3%match ratio).ICSPRF also has a low coarse-grained and overly fine-grained match *** the same metric,ICSPRF is more accurate than AutoFormat(88.5%for all evaluated protocols and 80.0%for binary-based protocols).

关键词： Industrial control system(ICS) ICS protocol reverse engineering Dynamic taint analysis Protocol format

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