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Milestones in Autonomous Driving and Intelligent Vehicles: Survey of Surveys

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arXiv 2023年

作者： Chen, Long Li, Yuchen Huang, Chao Li, Bai Xing, Yang Tian, Daxin Li, Li Hu, Zhongxu Na, Xiaoxiang Li, Zixuan Teng, Siyu Lv, Chen Wang, Jinjun Cao, Dongpu Zheng, Nanning Wang, Fei-Yue The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Waytous Ltd United Kingdom BNU-HKBU United International College Zhuhai519087 China Hong Kong Baptist University Kowloon999077 Hong Kong The Department of Industrial and System Engineering Hong Kong Polytechnical University Hong Kong The College of Mechanical and Vehicle Engineering Hunan University China The School of Aerospace Transport and Manufacturing Cranfield University United Kingdom The School of Transportation Science and Engineering Beihang University China The Department of Automation Tsinghua University China The Department of Mechanical and Aerospace Engineering Nanyang Technological University Singapore The Centre for Sustainable Road Freight University of Cambridge United Kingdom The School of Mechanical Engineering Tsinghua University China The College of Artificial Intelligence Xi’an Jiaotong University China

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks, lack of systematic summary and research directions in the future. Here we propose a Survey of Surveys (SoS) for total technologies of AD and IVs that reviews the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. To our knowledge, this article is the first SoS with milestones in AD and IVs, which constitutes our complete research work together with two other technical surveys. We anticipate that this article will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

Giant-cavity-based quantum sensors with enhanced performance

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arXiv 2022年

作者： Zhu, Y.T. Wu, R.B. Peng, Z.H. Xue, Shibei Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Center for intelligent and networked systems Department of Automation Tsinghua University Beijing100084 China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan Province Department of Physics Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha410081 China

Recent progresses have revealed that quantum systems with multiple position-dependent couplings, e.g., giant atoms, can exhibit some unconventional phenomena, such as non-exponential decay etc. However, their potential applications are still open questions. In this paper, we propose a giant-cavity-based quantum sensor for the first time, whose performance can be greatly enhanced compared to traditional cavity-based sensors. In our proposal, two cavities couple to a dissipative reservoir at multiple points while they couple to a gain reservoir in a single-point way. To detecting a unknown parameter using this sensor, a waveguide is coupled to one of the cavities where detecting fields can pass through for homodyne detection. We find that multiple position-dependent couplings can induce an inherent non-reciprocal coupling between the cavities, which can enhance the performance of sensors. Output noise in our scheme can be reduced to the shot noise level, which is about one order magnitude lower than the results in Ref. [Lau and Clerk (2018)]. Besides, the signal-to-noise ratio per photon is also enhanced by about one order of magnitude. These results show that the multiple-point-coupling structure is beneficial to nowadays quantum devices. Copyright © 2022, The Authors. All rights reserved.

关键词： Couplings

Ultralow Frequency Interlayer Mode from Suppressed Van Der Waals Coupling in Polar Janus SMoSe/SWSe Heterostructure

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SSRN

SSRN 2025年

作者： Ren, Kai Wang, Ke Luo, Yi Sun, Minglei Altalhi, Tariq Yakobson, Boris I. Zhang, Gang School of Mechanical and Electronic Engineering Nanjing Forestry University Jiangsu Nanjing210037 China School of Automation Xi’an University of Posts & Telecommunications Xi’an710121 China School of Mechanical Engineering Jiangsu Key Laboratory of Function Control Technology for Advanced Materials Jiangsu Ocean University Lianyungang222005 China Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Chemistry Department Taif University Taif21944 Saudi Arabia Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314019 China Jiangsu Ocean University China Southeast University China

The broken mirror symmetry in Janus SMoSe and SWSe monolayers induces novel properties for photocatalytic, thermoelectric and photocatalytic devices. Interlayer coupling is critical in van der Waals (vdW) heterostructure for quantum transport and polaritonics. We investigate Janus SMoSe/SWSe vdW heterostructures with three stacking interfaces: S-S, S-Se, and Se-Se. The S-Se SMoSe/SWSe vdW heterostructure with lowest symmetry exhibits ultralow frequencies of in-plane shear (1.94 cm−1) and out-of-plane breathing (4.47 cm−1) modes due to weaker interlayer vdW restoring forces and a significant intrinsic vertical dipole moment. The reduced restoring forces are caused by the critical charge transfer across the vdW interface. Thus, the larger interlayer spacing in the S-Se SMoSe/SWSe heterostructure results in the suppressed vdW interlayer coupling for ultralow phonon frequencies. These findings advance understanding of tuning vdW coupling in polar Janus SMoSe/SWSe heterostructures by stacking engineering, providing theoretical insights for designing tunable nanoelectronic devices. © 2025, The Authors. All rights reserved.

关键词： Van der Waals forces

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

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NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

Distributed Online Convex Optimization with Adversarial Constraints: Reduced Cumulative Constraint Violation Bounds under Slater’s Condition

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arXiv 2023年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. Lab for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online convex optimization with adversarial constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collaborate to minimize network regret and cumulative constraint violation. A novel distributed online algorithm is proposed and it achieves an O(T max{c,1−c}) network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the number of rounds and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints), the network cumulative constraint violation bound is reduced to O(T 1−c). Moreover, if the loss functions are strongly convex, then the network regret bound is reduced to O(log(T)), and the network cumulative constraint violation bound is reduced to O(√log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is the first to achieve reduced (network) cumulative constraint violation bounds for (distributed) online convex optimization with adversarial constraints under Slater’s condition. Finally, the theoretical results are verified through numerical simulations. Copyright © 2023, The Authors. All rights reserved.

关键词： Economic and social effects

An enhanced MES strategy for economic recovery and low-carbon operations: Incorporating time-lag superposition and hydrogen-electricity interdependency in chain accidents

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Energy 2025年 330卷

作者： Chen, Jie Zhang, Hongwei Tang, Zao Cao, Yijia Hunan Engineering Research Center of Multi-Energy Cooperative Control Technology College of Automation and Electronic Information Xiangtan University Xiangtan411105 China Department of Automation Hangzhou Dianzi University Hangzhou310018 China College of Electrical and Information Engineering Hunan University Hunan 410000 China

Chain accidents pose a threat to the economic operation of Multi-Energy system (MES). By leveraging the coupling characteristics and time-lag effects of energy sources, losses during chain accidents can be mitigated through coordination among multiple energy systems, thereby offering an economically viable solution. Therefore, in this paper, an enhanced optimization method for MES following chain accidents is proposed. Firstly, a refined thermal-grid inertia model and a gas-grid inertia model are introduced, both of which can help mitigate time-lag effects during accidents in the MES. Secondly, a Z-score statistical measure enhancement strategy is proposed to address unregulated external energy procurement during chain accidents. By considering historical energy prices and their changing trends, this strategy ensures more efficient energy utilization during periods of low prices, thereby facilitating economic recovery under interconnected circumstances. Thirdly, to address the challenging problem of nonlinearity and non-convexity, auxiliary flow variables and piecewise linearization methods are introduced to simplify the solution and improve solving efficiency. Finally, the effectiveness of the proposed multi-level optimization method is confirmed through extensive case studies. Compared to the baseline method, the proposed method achieves a 45.9 % improvement in economic performance. © 2025 Elsevier Ltd

关键词： Energy utilization

An Adaptive Data Rate-Based Task Offloading Scheme in Vehicular Networks

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An Adaptive Data Rate-Based Task Offloading Scheme in Vehicu...

International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Chaofan Chen Wendi Nie Yaoxin Duan Victor C.S. Lee Kai Liu Huamin Li School of Automation Chongqing University Chongqing China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing China Department of Automation Chongqing University of Posts and Telecommunications Chongqing China Institute of Industrial Internet Chongqing University of Posts and Telecommunications Chongqing China Department of Electrical and Electronic Engineering the University of Hong Kong Hong Kong China College of Computer Science Chongqing University Chongqing China

As an important application of Internet of Things (IoT), Internet of Vehicles (IoVs) can provide various valuable services which may require computation-intensive tasks under strict time constraints. Most traditional vehicles may not be able to process all these computation-intensive tasks locally because of the limitation of computing resources. Therefore, task offloading has been proposed, which allows vehicles to offload computation-intensive tasks to Mobile Edge Computing (MEC) servers. With the arising and development of intelligent vehicles, the concept of Vehicle as a Resource (VaaR) has been proposed as an important supplement to MEC, which enables intelligent vehicles to share computation resources with nearby vehicles. Most studies in VaaR generally assume that the transmission data rate of offloading tasks from one vehicle to another is fixed. However, in VaaR, due to the high mobility of vehicles, the communication distance between vehicles may change over time, resulting in changing data rate. Therefore, it is challenging to make offloading decisions (i.e., selecting proper vehicles as computation resource providers) while considering adaptive data rate. In this paper, we study task offloading in vehicular networks while considering adaptive data rate. We propose an Adaptive Data Rate-based Offloading algorithm named ADRO, which can not only achieve minimum energy consumption while satisfying time constraints, but also take adaptive data rate into consideration. Comprehensive experiments have been conducted to demonstrate the efficiency of the ADRO algorithm.

关键词： Energy consumption Adaptive systems Multi-access edge computing Intelligent vehicles Sensors Time factors Servers

SUNet: Scale-aware Unified Network for Panoptic Segmentation

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arXiv 2022年

作者： Yan, Weihao Qian, Yeqiang Wang, Chunxiang Yang, Ming The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China

Panoptic segmentation combines the advantages of semantic and instance segmentation, which can provide both pixel-level and instance-level environmental perception information for intelligent vehicles. However, it is challenged with segmenting objects of various scales, especially on extremely large and small ones. In this work, we propose two lightweight modules to mitigate this problem. First, Pixel-relation Block is designed to model global context information for large-scale things, which is based on a query-independent formulation and brings small parameter increments. Then, Convectional Network is constructed to collect extra high-resolution information for small-scale stuff, supplying more appropriate semantic features for the downstream segmentation branches. Based on these two modules, we present an end-to-end Scale-aware Unified Network (SUNet), which is more adaptable to multi-scale objects. Extensive experiments on Cityscapes and COCO demonstrate the effectiveness of the proposed methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

Leader-tracking in a shape-preserving formation with bearing-only measurements 21st

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Leader-tracking in a shape-preserving formation with bearing...

21st IFAC World Congress 2020

作者： Yang, Ziwen Zhu, Shanying Chen, Cailian Feng, Gang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Department of Biomedical Engineering City University of Hong Kong Kowloon Hong Kong

This paper studies the problem of shape-preserving formation control for multi-agent systems where only bearing measurements are available. Most existing methods to solve the problems assume that accurate global or local position measurements of agents are available, or use estimators to get these information without analysis of estimators' effects on the closed loop system stability. In this work, we propose a framework integrating an estimator to get relative positions using bearing-only measurements and an estimator-based controller to achieve tracking a pair of leaders in a formation with a preserved shape. The estimator is designed by exploiting orthogonality to cope with the high non-linearity of bearing measurements, based on which the controller is designed with the estimated relative positions. With rigorous theoretical analysis of the closed-loop system, we characterize the leaders which can be tracked by followers in a shape-preserving formation using bearing-only measurements, and the asymptotic stability of the closed-loop system can be guaranteed. Simulations testify the effectiveness of the proposed framework. Copyright © 2020 The Authors. This is an open access article under the CC BY-NC-ND license

关键词： Closed loop systems