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IEEE Transactions on Intelligent Vehicles 2023年第2期9卷 3220-3231页

作者： Xiao Wang Ke Tang Xingyuan Dai Jintao Xu Quancheng Du Rui Ai Yuxiao Wang Weihao Gu Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei China Haomo Technology Company Ltd. Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S $^{\text{4}}$ TP) framework. Specifically, S $^{\text{4}}$ TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV's planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S $^{\text{4}}$ TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs' trajectories as input. With the integration of SADRF, S $^{\text{4}}$ TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S $^{\text{4}}$ TP in terms of safety and rationality. S $^{\text{4}}$ TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-Decision of 94.75%.

关键词： Trajectory Safety Vehicles Trajectory planning Autonomous vehicles Risk management Behavioral sciences

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Size-Invariance Matters: Rethinking Metrics and Losses for Imbalanced Multi-object Salient Object Detection

arXiv

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arXiv 2024年

作者： Li, Feiran Xu, Qianqian Bao, Shilong Yang, Zhiyong Cong, Runmin Cao, Xiaochun Huang, Qingming Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Sun Yat-Sen University Shenzhen Campus China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

This paper explores the size-invariance of evaluation metrics in Salient Object Detection (SOD), especially when multiple targets of diverse sizes co-exist in the same image. We observe that current metrics are size-sensitive, where larger objects are focused, and smaller ones tend to be ignored. We argue that the evaluation should be size-invariant because bias based on size is unjustified without additional semantic information. In pursuit of this, we propose a generic approach that evaluates each salient object separately and then combines the results, effectively alleviating the imbalance. We further develop an optimization framework tailored to this goal, achieving considerable improvements in detecting objects of different sizes. Theoretically, we provide evidence supporting the validity of our new metrics and present the generalization analysis of SOD. Extensive experiments demonstrate the effectiveness of our method. The code is available at https://***/Ferry-Li/SI-SOD. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Size-invariance matters: rethinking metrics and losses for imbalanced multi-object salient object detection 24

Size-invariance matters: rethinking metrics and losses for i...

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Proceedings of the 41st International Conference on Machine Learning

作者： Feiran Li Qianqian Xu Shilong Bao Zhiyong Yang Runmin Cong Xiaochun Cao Qingming Huang Institute of Information Engineering Chinese Academy of Sciences Beijing China and School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China Institute of Information Science Beijing Jiaotong University Beijing China and School of Control Science and Engineering Shandong University Jinan China and Key Laboratory of Machine Intelligence and System Control Ministry of Education Jinan China School of Cyber Science and Tech. Shenzhen Campus Sun Yat-sen University School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China and Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China and Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China

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Multi-level Coordinated Energy Management for Energy Hub in Hybrid Markets with Distributionally Robust Scheduling

arXiv

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arXiv 2022年

作者： Cao, Jiaxin Yang, Bo Zhu, Shanying Chung, Chi Yung Guan, Xinping Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China Department of Electrical and Computer Engineering University of Saskatchewan SaskatoonSKS7N 5A9 Canada

Maintaining energy balance and economical operation is significant for multi-energy systems such as the energy hub (EH). However, it is usually challenged by the frequently changing and unpredictable uncertain parameters at different timescales. Under this scope, this paper investigates the coordinated energy management problem for day-ahead and intra-day conditions considering uncertainties of source-load and market prices concurrently. Note that the precise knowledge of distributions about uncertainties may be unaccessible before the decision-making in day-ahead phase. A two-stage chance-constrained model based on distributionally robust approach with ambiguous moment information is proposed to immunize scheduling strategies against the worst-case probability distributions. The first stage is dedicated to obtaining more energy arbitrage and operation flexibility by optimizing bidding strategies in day-ahead power, natural gas and carbon trading markets. The second stage focuses on the optimization of the worst-case expected operation cost. It provides a robust energy equipment and load scheduling strategy for the reference of subsequent intra-day arrangements. With respect to different variations of electrical and thermal components, an intra-day two-timescale coordination is implemented step by step. The energy scheduling is re-dispatched circularly to minimize the operation and penalty costs. The possible energy imbalance is also compensated by this way. As the energy management program is nonlinear, chance-constrained and multi-stage, some linearization and dual transformation techniques are designed to enhance tractability of the program. Experimental results show that the developed multi-level framework results in a carbon emission decrease of 37%, and reduces energy cost averagely 3% compared with corresponding contrasting cases. The obtained strategy validates a good tradeoff between robustness and optimality. Copyright © 2022, The Authors. All rights reser

关键词： Power markets

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Multi-Agent Consensus with Event-Triggered Communication and Relative Output Sensing

Multi-Agent Consensus with Event-Triggered Communication and...

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第40届中国控制会议

作者： Xianwei Li Shaoyuan Li Wei Xing Zheng Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Computer Data and Mathematical Sciences Western Sydney University

This paper investigates the consensus problem of linear multi-agent systems with event-triggered(ET) communication on undirected graphs. More practically, it is assumed that each agent can only access the relative output about its ***, the existing event-triggered(ET) protocols based on relative state sensing or absolute output sensing are not *** by this, an ET output-feedback protocol based on relative output sensing is developed. By a new Lyapunov function with more augmented states, it is proved that the resulting closed-loop system can reach consensus and the protocol states converge to zero. It is also shown that Zeno behavior is excluded from the triggering process. Furthermore, a method for reconstructing the continuous-time relative output from sampled data is formulated, based on which, the protocol can be implemented without continuous monitoring of neighbors. Finally, the effectiveness of the theoretic developments is illustrated by a numerical example.

关键词： Multi-agent system(MAS) Consensus Relative information Output feedback Event-triggered(ET) communication

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Dynamic Multi-objective Optimization via Sliding Time Window and Parallel Computing 12th

Dynamic Multi-objective Optimization via Sliding Time Window...

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12th International Conference on Advances in Swarm Intelligence, ICSI 2021

作者： Fan, Qinqin Wang, Yihao Ersoy, Okan K. Li, Ning Chu, Zhenzhong Logistics Research Center Shanghai Maritime University Shanghai201306 China School of Electronic and Computer Engineering Purdue University West LafayetteIN47906 United States Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai200240 China Logistics Engineering College Shanghai Maritime University Shanghai201306 China

ISBN: (纸本)9783030788100

Tracking changing Pareto front (PF) in the objective space and Pareto set (PS) in the decision space is an important task in dynamic multi-objective optimization (DMO). Similarly, maintaining population diversity and reusing previous evolutionary information are useful to explore promising regions and to find high-quality solutions quickly in time-varying environments. To this end, a sliding time window based on parallel computing (STW-PC) is introduced in the present study. In the STW-PC, obtained time-sequence solution sets aim to preserve the diversity and facilitate a fast convergence since problems in successive time/environments are usually related. The parallel computing method is also employed to reduce the computational time. The STW-PC is incorporated into a multi-objective evolutionary algorithm and is compared with two competitors on 12 dynamic multi-objective optimization problems. The results show that the STW-PC can both improve the tracking performance of the selected algorithm in different degrees of changes, and significantly reduce the calculation time compared with transfer learning. © 2021, Springer Nature Switzerland AG.

关键词： Multiobjective optimization

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Towards Energy-Efficiency: Integrating MATD3 Reinforcement Learning Method for Computational Offloading in RIS-Aided UAV-MEC Environments

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IEEE Internet of Things Journal 2025年

作者： Wu, Liangshun Zhang, Cong Zhang, Bin Du, Jianbo Qu, Junsuo Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai201804 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai201210 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Xi'an Key Laboratory of Advanced Control and Intelligent Process School of Automation Xi'an University of Posts & Telecommunications Xi'an710061 China Xinjiang University of Political Science and Law Tumushuke832003 China School of Remote Sensing and Information Engineering Wuhan University Wuhan430079 China Department of Computer City University of Hong Kong 999077 Hong Kong School of Communications and Information Engineering Xi'an University of Posts & Telecommunications Xi'an710061 China

With the proliferation of IoT devices, there is an escalating demand for enhanced computing and communication capabilities. Mobile Edge Computing (MEC) addresses this need by relocating computing resources to the network edge, thereby delivering swifter and more efficient services. This paper introduces a computation offloading and energy consumption optimization framework that leverages Reconfigurable Intelligent Surfaces (RIS), Unmanned Aerial Vehicles (UAVs), and MEC. The scheme aims to maximize energy efficiency through the optimization of task allocation, RIS phase shifts, and UAV trajectories. By employing the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) reinforcement learning algorithm, the paper further refines UAV trajectories and RIS configurations. The simulation results indicate that the proposed method surpasses the traditional Concave-Convex Procedure (CCCP) algorithm in both UAV trajectory control and RIS configuration, demonstrating quicker convergence and enhanced stability. The method proves to be adaptable to diverse environments and tasks, showcasing notable benefits in RIS-assisted interference suppression, particularly with large RIS, thereby enhancing UAV data reception rates. Additionally, MATD3 exhibits faster and smoother convergence for extended task durations and smaller RIS scenarios. Simulation results reveal that UAVs tend to move closer to RIS, with energy efficiency falling as IoT tasks increase, affirming the proposed algorithm's high energy efficiency and effectiveness. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Low-Cost Approach for Improving Video Transmission Efficiency in WVSN

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Journal of Shanghai Jiaotong university(Science) 2020年第5期25卷 600-605页

作者： LIU Min DENG Bin TANG Ying WU Minghu WANG Juan Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System.Hubei University of Technology Wuhan 430068.China Department of Electrical and Computer Engineering.Rowan University GlassboroNJ 08028USA State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Smart Education Qingdao Academy of Intelligent IndustriesQingdao 266041ShandongChina

The wireless visual sensor network(WVSN)as a new emerged intelligent visual system,has been applied in many video monitoring ***,there is still great challenge because of the limited wireless network *** resolve the problem,we propose a real-time dynamic texture approach which can detect and reduce the temporal redundancy during many successive image ***,an adaptively learning background model is improved to discover successive similar image frames from the inputting video ***,the dynamic texture model based on the singular value decomposition is adopted to distinguish foreground and background element ***,a background discarding strategy based on visual motion coherence is proposed to determine whether each image frame is streamed or *** evaluate the trade-off performance of the proposed method,it is tested on the CDW-2014 dataset,which can accurately detect the first foreground frame when the moving objects of interest appear in the field of view in the most tested dynamic scenes,and the misdetection rate of the undetected foreground frames is near to *** to the original stream,it can reduce the occupied bandwidth a lot and its computational cost is relatively lower than the state-of-the-art methods.

关键词： wireless visual sensor network(WVSN) temporal redundancy foreground background dynamic texture

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Research on occlusion perception facial feature correlation based on less-class learning

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Signal, Image and Video Processing 2025年第8期19卷

作者： Li, Yaqian Zhan, Xin Gao, Ya Li, Haibin Zhang, Wenming Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei Qinhuangdao066004 China Engineering Research Center of the Ministry of Education for Intelligent Control System and Intelligent Equipment Yanshan University Hebei Qinhuangdao066004 China

Occlusion is a significant challenge in face recognition accuracy. An innovative occlusion-aware approach is presented in this paper to mitigate the impact of occlusions on recognition performance. Unlike traditional methods that require extensive occlusion data, our approach utilizes a general occlusion perception network with facial semantic parsing. This network classifies "non-face"regions as occlusions, which makes our approach robust against various occlusion types. For the precise localization of occluded areas, facial contour detection is employed, and missing contour segments are predicted, with this contour information being utilized in subsequent recognition processes. In the recognition phase, the face is segmented into sub-regions based on spatial and semantic cues. A network, similar to Pairwise Difference Siamese Network, is developed to construct a region-feature dictionary, which enables the selective suppression of features affected by occlusion. The efficacy of the proposed method is demonstrated through extensive experiments conducted on the AR, Megaface, LFW, and synthetic occlusion datasets. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Feature extraction

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Motion Projection Consistency Based 3D Human Pose Estimation with Virtual Bones from Monocular Videos

arXiv

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arXiv 2021年

作者： Wang, Guangming Zeng, Honghao Wang, Ziliang Liu, Zhe Wang, Hesheng Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment and System Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge CambridgeCB3 0FD United Kingdom

Real-time 3D human pose estimation is crucial for human-computer interaction. It is cheap and practical to estimate 3D human pose only from monocular video. However, recent bone splicing based 3D human pose estimation method brings about the problem of cumulative error. In this paper, the concept of virtual bones is proposed to solve such a challenge. The virtual bones are imaginary bones between non-adjacent joints. They do not exist in reality, but they bring new loop constraints for the estimation of 3D human joints. The proposed network in this paper predicts real bones and virtual bones, simultaneously. The final length of real bones is constrained and learned by the loop constructed by the predicted real bones and virtual bones. Besides, the motion constraints of joints in consecutive frames are considered. The consistency between the 2D projected position displacement predicted by the network and the captured real 2D displacement by the camera is proposed as a new projection consistency loss for the learning of 3D human pose. The experiments on the Human3.6M dataset demonstrate the good performance of the proposed method. Ablation studies demonstrate the effectiveness of the proposed inter-frame projection consistency constraints and intra-frame loop constraints. Copyright © 2021, The Authors. All rights reserved.

关键词： E-learning

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