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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 1-12页

作者： Liu, Chunhong Zhao, Mengdi Wang, Huaichen Cheng, Bo Liu, Jialei Yuan, Peiyan Engineering Lab of Intelligence Business & Internet of Things and School of Computer and Information Engineering Henan Normal University Xinxiang China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle and School of Computer Engineering Hubei University of Arts and Science Xiangyang China

Vehicle edge computing (VEC) offers users low-latency and high-reliability services by using computational resources at the network's edge. Nevertheless, because of inadequate infrastructure and limited resources, computation-intensive and delay-sensitive vehicle applications cannot be performed efficiently at the edge. Therefore, several studies have used the idle resources of parked vehicles to assist in computation offloading. In this paper, we propose a parked vehicle-assisted vehicle edge computing architecture considering multi-agent collaboration, including intelligent vehicles and edge servers. Additionally, we propose a framework for a parallel Internet of Vehicles (IoV) utilizing computational experiment. The service provider is assigned the role of owning VEC resources and recruiting parking vehicle resources. The model was constructed by using the resource consumption-service relationship of both offloading parties to ensure service quality. First, a Stackelberg game model was constructed based on the interaction between requesting vehicles and a service provider. The latter was the leader, and the requesting vehicles were the followers. The Nash equilibrium for optimal pricing and offloading allocations was attained and verified, and a distributed gradient-based equilibrium algorithm was designed to solve the Stackelberg game model and obtain the final decision through mutual communication. The method also protects the privacy of participants and respects the willingness of requesting vehicles to offload. Finally, the simulation experiments confirmed that the proposed algorithm can achieve game equilibrium. Furthermore, it outperformed state-of-the-art algorithms in improving the service provider's utility. IEEE

关键词： Vehicles

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Introduction to the Special Issue on Formal Methods and Models for System Design

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ACM Transactions on Embedded Computing Systems 2025年第3期24卷 1-3页

作者： Brandt, Jens Saha, Indranil Zhang, Lijun Hochschule Niederrhein Krefeld Germany Department of Computer Science and Engineering Indian Institute of Technology Kanpur Kanpur India State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

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Emotional Synchronization for Audio-Driven Talking-Head Generation 24

Emotional Synchronization for Audio-Driven Talking-Head Gene...

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24th IEEE International Conference on Data Mining, ICDM 2024

作者： Zhang, Zhao Luo, Yan Zuo, Zhichao Hong, Richang Yang, Yi Wang, Meng School of Computer Science and Information Engineering University of Technology Hefei China Yunnan Key Laboratory of Software Engineering Yunan China School of Computer Science and Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798331506681

Audio-driven talking-head synthesis has become a significant focus in the field of virtual human applications. However, existing methodologies face challenges in effectively synchronizing audio and video, especially in maintaining emotional consistency. Additionally, there is a notable inefficiency in leveraging emotional prompts to guide expression generation. To address these limitations, this paper introduces an Emotion Synchronized audio-driven Talking-head synthesis (EST) approach. The EST approach aims to enhance the emotion-agnostic talking-head models by enabling emotion control, and it incorporates a diffusion module to learn diverse latent rep-resentations. Furthermore, EST utilizes null-text embedding to align the latent code with emotional prompts. Additionally, a novel Sync Attention Block (SAB) is developed to broaden the spatial perceptual field, thus preventing the loss of critical information. Extensive experiments demonstrate the effectiveness of the EST method, showcasing state-of-the-art performance across widely-adopted datasets. Moreover, the EST approach exhibits exceptional generalization capabilities, even in scenarios where emotional training videos are unavailable. © 2024 IEEE.

关键词： Synchronization

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Deep Learning Based Take-Over Performance Prediction and Its Application on Intelligent Vehicles

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Liu, Weimin Li, Qingkun Wang, Wenjun Wang, Zhenyuan Zeng, Chao Cheng, Bo State Key Laboratory of Automotive Safety and Energy Center for Intelligent Connected Vehicles and Transportation School of Vehicle and Mobility Tsinghua University Beijing China Beijing Key Laboratory of Human-Computer Interaction Institute of Software Chinese Academy of Sciences Beijing China College of Information Science and Engineering Henan University of Technology Zhengzhou China

Take-over performance plays a significant role in evaluating drivers' state, and serves as a crucial reference for enhancing control transitions in the context of conditionally automated driving. In this study, we aim to predict minimum anticipated collision time (min ACT), an indicator of drivers' take-over performance, in expectation of promoting safer take-overs via deep learning, so that drivers' state detriment of take-over safety could be adjusted accordingly with intelligent human-machine interaction algorithms predictably. By incorporating multi-source information including drivers' state, drivers' demographics, surrounding traffic features as well as driver-vehicle interaction characteristics, network model “ACTNet” was proposed to facilitate continuous estimation. Depthwise separable convolution and non-local self-attention were utilized to prevent overfitting and establish spatial dependency over fixation heatmap, respectively. To overcome data distribution imbalance, class balanced loss was used in conjunction with regression loss to realize more accurate predictions. Driving simulator experiment was conducted with dataset collected for the subsequent verification of the proposed algorithm. Potentialities of deep learning methods were highlighted for take-over studies, contributing to the design of intelligent human-machine interaction systems in conditional automation. Our findings present a valid method of deep learning in predicting drivers' take-over performance and meanwhile have implications for the development of intelligent adaptive take-over time budget regulation and dynamic drivers' state adjustment algorithms. IEEE

关键词： Automation

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V-AUTOSAR: Graphical Modeling Language for AUTOSAR Architecture and Resource Modeling 22

V-AUTOSAR: Graphical Modeling Language for AUTOSAR Architect...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Yang, Yilong Zhang, Yang Niu, Hongliang Yuan, Cangzhou Li, Qiangwei School of Software State Key Laboratory of Complex & Critical Software Environment Beihang University Beijing China School of Transportaton Science and Engineering Beihang University Beijing China

ISBN: (纸本)9798331527471

AUTOSAR enhances the management of complex automotive electrical and electronic architectures by improving the reusability and interchangeability of software modules between OEMs and suppliers. However, existing AUTOSAR modeling tools need help with non-intuitive representation and complicated architectural relationship modeling processes. In this paper, we propose a visual architecture modeling language to represent based on model-driven development of the system architecture design of vehicles. Our approach addresses these issues by implementing multi-dimensional visualization capabilities, incorporating two-dimensional graphical representations and detailed one-dimensional tabular displays. Furthermore, we introduce a practical’AUTOSAR meeting in the middle modeling method, which allows for separate modeling at different levels. This approach effectively harnesses the expertise of detailed bottom-level designers and high-level architects, improving efficiency in automotive system design. A detailed case study and evaluation substantiate the effectiveness of our modeling language in describing the system architecture. © 2024 IEEE.

关键词： Reusability

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A Reliability Prediction Method for AUTOSAR Architecture Considering Unreliable Platforms 22

A Reliability Prediction Method for AUTOSAR Architecture Con...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Yuan, Cangzhou Niu, Hongliang Zhang, Yang Yang, Yilong Li, Qiangwei School of Software State Key Laboratory of Complex & Critical Software Environment Beihang University Beijing China School of Transportaton Science and Engineering Beihang University Beijing China

ISBN: (纸本)9798331527471

With the trend of intelligence, automobile architecture has become more complex. It is necessary to predict and discover reliability-related issues to reduce the cost of correction in the later period. In AUTOSAR-based automotive architecture design, software and hardware interaction, middleware platform behavior, physical environment, and system usage profile affect the system’s reliability. It is necessary to comprehensively consider these factors to predict the system’s reliability reasonably. However, existing methods often overlook the influence of some factors, especially oversimplifying the control flow of the middleware platform in the system. Resulting in difficulty in effectively modeling the behavior of the AUTOSAR middleware platform in error propagation and its impact on system failure behavior. To analyze the impact of middleware platforms on failure behavior, this paper analyzes the impact of the AutoSAR middleware platform on application software faults based on error propagation methods. Then, expand the AUTOSAR meta-model to model reliability parameters and automatically convert the architecture model into a formal model for reliability prediction. Finally, the effectiveness of considering unreliable platform behavior modeling was verified through a car headlight design case study. © 2024 IEEE.

关键词： Middleware

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Adaptive Cost Aggregation in Iterative Depth Estimation for Efficient Multi-view Stereo 12th

Adaptive Cost Aggregation in Iterative Depth Estimation for...

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12th International Conference on Image and Graphics, ICIG 2023

作者： Wang, Xiang Bai, Xiao Wang, Chen School of Computer Science and Engineering State Key Laboratory of Software Development Environment Jiangxi Research Institute Beihang University Beijing China

ISBN: (纸本)9783031463075

The deep multi-view stereo (MVS) approaches generally construct 3D cost volumes to regularize and regress the depth map. These methods are limited with high-resolution outputs since the memory and time costs grow cubically as the volume resolution increases. In this paper, we presented an multi-stage iterative depth map estimation method for MVS. In our network, the cost volume is iteratively processed by lightweight 2D convolution based GRU modules, and the multi-stage coarse-to-fine structure is adopted to speed up the depth estimation process. To further improve the 3D reconstruction quality, we make improvements from two different perspectives of adaptive cost aggregation: a view-adaptive weighting module is proposed to account for the occlusion problem in cost volume fusion, and a spatial-adaptive deformable geometric feature encoding module is introduced to the cost volume feature encoding before feeding into GRUs for stronger modeling capability. Experiments on the DTU dataset demonstrated the effectiveness of the proposed network in accuracy with remarkable efficiency performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Iterative methods

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Micromechanical modeling of longitudinal tensile behavior and failure mechanism of unidirectional carbon fiber/aluminum composites involving fiber strength dispersion

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Chinese Journal of Aeronautics 2024年第9期37卷 312-327页

作者： Qipeng LIU Wengang JIANG Yuehua GAO Zhenjun WANG Shanshan SHI Zhi SUN Jiangxi Key Laboratory of Forming and Joining Technology for Aerospace Components Nanchang Hangkong UniversityNanchang 330063China School of Locomotive and Rolling Stock Engineering Dalian Jiaotong UniversityDalian 116028China State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of TechnologyDalian 116024China

This paper examines the longitudinal tensile behavior and failure mechanism of a new unidirectional carbon fiber reinforced aluminum composite through experiments and simulations.A Weibull distribution model was established to describe the fiber strength dispersion based on single-fiber tensile tests for carbon fibers extracted from the *** constitutive models for the matrix and interface were established based on the uniaxial tensile and single-fiber push-out tests,***,a 3D micromechanical numerical model,innovatively considering the fiber strength dispersion by use of the weakest link and Weibull distribution theories,was estab-lished to simulate the progressive failure behavior of the composite under longitudinal *** to the dispersion of fiber strength,the weakest link of the fiber first fractures,and stress concentra-tion occurs in the surrounding fibers,interfaces,and *** maximum stress concentration fac-tor for neighboring fibers varies nonlinearly with the distance from the fractured *** isolated and clustered fractured fibers are present during the progressive failure process of the *** expansion of fractured fiber clusters intensifies stress concentration and material degradation which in turn enlarges the fractured fiber clusters,and their mutual action leads to the final collapse of the composite.

关键词： Fiber reinforced metals Finite element method 3D micromechanical model Fiber strength dispersion Longitudinal tension Progressive failure

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Research on key technologies of edge cache in virtual data space across WAN

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Frontiers of computer Science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and computer Network Information Center in Chinese Academy of Sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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SCaR: Refining Skill Chaining for Long-Horizon Robotic Manipulation via Dual Regularization 38

SCaR: Refining Skill Chaining for Long-Horizon Robotic Manip...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Zixuan Ji, Ze Huo, Jing Gao, Yang State Key Laboratory for Novel Software Technology Nanjing University China School of Engineering Cardiff University United Kingdom

Long-horizon robotic manipulation tasks typically involve a series of interrelated sub-tasks spanning multiple execution stages. Skill chaining offers a feasible solution for these tasks by pre-training the skills for each sub-task and linking them sequentially. However, imperfections in skill learning or disturbances during execution can lead to the accumulation of errors in skill chaining process, resulting in execution failures. In this paper, we investigate how to achieve stable and smooth skill chaining for long-horizon robotic manipulation tasks. Specifically, we propose a novel skill chaining framework called Skill Chaining via Dual Regularization (SCaR). This framework applies dual regularization to sub-task skill pre-training and fine-tuning, which not only enhances the intra-skill dependencies within each sub-task skill but also reinforces the inter-skill dependencies between sequential sub-task skills, thus ensuring smooth skill chaining and stable long-horizon execution. We evaluate the SCaR framework on two representative long-horizon robotic manipulation simulation benchmarks: IKEA furniture assembly and kitchen organization. Additionally, we conduct a simple real-world validation in tabletop robot pick-and-place tasks. The experimental results show that, with the support of SCaR, the robot achieves a higher success rate in long-horizon tasks compared to relevant baselines and demonstrates greater robustness to perturbations. © 2024 Neural information processing systems foundation. All rights reserved.

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