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A probe into the acid deposition mitigation path in China over the last four decades and beyond

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National Science Review 2024年第4期11卷 84-92页

作者： Qian Yu Xiaodong Ge Haotian Zheng Jia Xing Lei Duan Dongwei Lv Dian Ding Zhaoxin Dong Yisheng Sun Posch Maximilian Danni Xie Yu Zhao Bin Zhao Shuxiao Wang Jan Mulder Thorj?rn Larssen Jiming Hao State Key Laboratory of Environmental Simulation and Pollution Control School of EnvironmentTsinghua University State Key Laboratory of Pollution Control &Resource Reuse and School of the Environment Nanjing University State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex School of EnvironmentTsinghua University International Institute for Applied System Analysis(IIASA) School of Land Engineering Chang'an University Faculty of Environmental Sciences and Natural Resource Management Norwegian University of Life Sciences Norwegian Institute for Water Research

China currently has the highest acid deposition globally, yet research on its status, impacts, causes and controls is lacking. Here, we compiled data and calculated critical loads regarding acid deposition. The results showed that the abatement measures in China have achieved a sharp decline in the emissions of acidifying pollutants and a continuous recovery of precipitation p H, despite the drastic growth in the economy and energy consumption. However, the risk of ecological acidification and eutrophication showed no significant decrease. With similar emission reductions, the decline in areas at risk of acidification in China(7.0%) lags behind those in Europe(20%) or the USA(15%). This was because, unlike Europe and the USA, China's abatement strategies primarily target air quality improvement rather than mitigating ecological impacts. Given that the area with the risk of eutrophication induced by nitrogen deposition remained at 13%of the country even under the scenario of achieving the dual targets of air quality and carbon dioxide mitigation in 2035, we explored an enhanced ammonia abatement pathway. With a further 27% reduction in ammonia by 2035, China could largely eliminate the impacts of acid deposition. This research serves as a valuable reference for China's future acid deposition control and for other nations facing similar challenges.

关键词： acid deposition critical loads acidification eutrophication ammonia abatement

Vehicle 5.0: From Driverless Vehicles for ITS in CPS to MetaDriving for Smart Mobility in CPSS

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第6期8卷 3523-3526页

作者： Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

From January 1 to May 30, 2023, we have received 1214 submissions, averaging 8.09 submissions per day. Based on this SPD, we are on track to surpass our estimated 2500 submissions by November [1], [2]. This implies more work for processing and evaluation; therefore we need to speed up our effort to recruit more able and responsible Associate Editors and Reviewers. I need help from you in this task with great appreciation.

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Parallel Training: An ACP-Based Training Framework for Iterative Learning in Uncertain Driving Spaces

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第4期8卷 2832-2841页

作者： Wang, Jiangong Wang, Xiao Tian, Yonglin Wang, Yutong Niu, Jinglong Kwan, Oliver Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Anhui Univ Sch Artificial Intelligence State Key Lab Management & Control Complex Syst Hefei 230031 Peoples R China Chinese Acad Sci Qingdao Acad Intelligent Ind State Key Lab Management & Control Complex Syst Qingdao 266109 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Acad Intelligent Ind Qingdao 266109 Peoples R China China North Ind North Automatic Control Technol Re Taiyuan 030006 Peoples R China Motion G Inc Singapore 068898 Singapore

The traffic environment and driving behaviors are of great complexity and uncertainty in our physical world. Therefore, training in the digital world with low cost and diverse complexities become popular for autonomous driving in recent years. However, the current training methods tend to be limited to static data sets and deterministic models that do not sufficiently take into account the uncertainty and diversity prevalent in real traffic scenarios. These approaches also limit more possibilities for the comprehensive development and optimization of vision systems. In this paper, we develop a parallel training method based on artificial systems, computational experiments, and parallel execution (ACP) for the intelligent optimization and learning of the aforementioned agents in uncertain driving spaces. Parallel training creates a virtual driving space following the instruction of the ACP approach and conducts large-scale rehearsal experiments for possible scenarios. By enhancing the diversity of virtual scenarios, intelligent vehicles are trained to respond and adapt to the diverse uncertainties in the physical real-world driving space. Specifically, parallel training first proposes a standard operating procedure for intelligent driving systems, namely the projection-emergence-convergence-operation (PECO) loop. Digital quadruplets for parallel training, i.e., physical, descriptive, predictive, and prescriptive coaches, are also proposed. With the guidance of parallel training, virtual and real-world driving spaces are set up in parallel and interact frequently. They are closely linked and unified in opposition to each other, ultimately building a parallel driving system that fulfills safety, security, sustainability, sensitivity, service, and smartness (6S).

关键词： Training Digital twins Testing Task analysis Intelligent agents complex systems Uncertainty Parallel intelligence parallel driving digital quadruplets parallel learning digital twins metaverses automated driving knowledge transfer

Meta-Services in Industry 5.0: A New Paradigm of Intelligent Services in Metaverses

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IEEE TRANSACTIONS ON systemS MAN CYBERNETICS-systemS 2024年第11期54卷 6826-6836页

作者： Lyu, Yudan Li, Lefei Jing, Zheng Liang, Yuchen Wang, Ridong Wang, Fei-Yue Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In the era of Industry 5.0 and the emerging metaverses, this study proposes Meta-Services, a novel paradigm that evolves a traditional service system into a multistage ecosystem. In the proposed paradigm, we develop a parallel intelligence-based management framework that enables stakeholders to control and manage the complex dynamics of service delivery in the metaverse. The management framework involves the following three stages: 1) service systems in metaverses;2) elementary parallel service systems;and 3) parallel intelligence empowered ecosystems. The third stage evolves from the first two stages by incorporating the approach of "designer in the loop," contributing to more human-centered, adaptive, and resilient service systems. Moreover, a case study in the retail sector is provided to validate the effectiveness of the proposed paradigm and show its practical potential.

关键词： Metaverse Industries Fifth Industrial Revolution complexity theory Digital humans Real-time systems Ecosystems Cyber-physical-social systems designer in the loop Industry 5 0 metaverses parallel services service systems

Imaginative Intelligence for Intelligent Vehicles: Sora Inspired New Directions for New Mobility and Vehicle Intelligence

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第4期9卷 4557-4562页

作者： Wang, Fei-Yue Wuhan Inst Ind Innovat & Dev Wuhan 430000 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

The current issue includes 3 perspectives, 2 letters and 17 regular papers. These perspectives explore critical issues within the field of IVs and propose prospective research directions based on the evolution of foundation models. After Scanning the Issue, I would like to share insights on how Sora-based imaginative intelligence could propel the future development of IVs.

关键词： Intelligent vehicles Task analysis Biological system modeling Adaptation models Reviews Autonomous vehicles Safety

Intelligent Vehicles for Sustainability Industry: Call for Nomination and Participation

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2024年第3期9卷 4233-4239页

作者： Wang, Fei-Yue Wuhan Inst Ind Innovat & Dev Hubei 430000 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

From Jan. 1 to Mar. 23, we have received 1735 submissions. The current average number of submissions per day (SPD) rate is 21.12 [1], [2]. However, such a vibrated SPD also indicates a tremendous workload for our editorial board. Therefore, I would like to expand our team to include at least 240 members. If you have suitable candidates for potential associate editors, please send a Short BioSketch and a Resume to feiyue@*** and danielyenew22@***.

关键词： Industries Intelligent vehicles Sustainable development

Adaptive Dynamic Programming for Robust Event-Driven Tracking control of Nonlinear systems With Asymmetric Input Constraints

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IEEE TRANSACTIONS ON CYBERNETICS 2024年第11期54卷 6333-6344页

作者： Yang, Xiong Wei, Qinglai Tianjin Univ Sch Elect & Informat Engn Tianjin Key Lab Intelligent Unmanned Swarm Techno Tianjin 300072 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

This article considers the robust dynamic event-driven tracking control problem of nonlinear systems having mismatched disturbances and asymmetric input constraints. Initially, to tackle the asymmetric constraints, a novel nonquadratic value function is constructed for the original system. This makes the asymmetrically constrained tracking control problem transformed into an unconstrained optimal regulation problem. Then, a dynamic event-driven mechanism is proposed. Meanwhile, the event-driven Hamilton-Jacobi-Bellman equation (ED-HJBE) is developed for the optimal regulation problem in order to acquire the optimal control with distinctly decreased computational burden. To solve the ED-HJBE, a single critic neural network (CNN) is designed in the adaptive dynamic programming framework. Meanwhile, the gradient descent method is employed to update the CNN's weights. After that, both the weight estimation error and the tracking error are proved to be uniformly ultimately bounded via Lyapunov's direct method. Finally, simulations of the spring-mass-damper system and the pendulum plant are separately utilized to validate the established theoretical claims.

关键词： Nonlinear systems control systems Optimal control Regulation Dynamic programming Perturbation methods Adaptive systems Adaptive dynamic programming (ADP) asymmetric constraint event-driven mechanism (EDM) neural network (NN) reinforcement learning (RL)