Article
Economics
Alex Anas, Huibin Chang
Summary: The Grand Paris Express (GPE) reduces road congestion and induces job densification, benefiting consumers and improving productivity. To analyze the effects empirically, a spatial general equilibrium model is used. The TFP externality reduces costs and benefits consumers, while Pigouvian congestion tolling raises welfare in the long run.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2023)
Article
Automation & Control Systems
K. Senthilkumar, Avinash Kumar Roy, K. Srinivasan
Summary: This paper presents a feedback control design based on an event-triggered estimator for networked control systems (NCS) under stochastic effects and correlated noises. The proposed method incorporates an event-triggered mechanism at the sensor node to regulate data transmission and reduce energy consumption and network traffic. The estimator uses a predicted sensor measurement in case of data packet loss, improving performance and reducing computation burden. The proposed method achieves mean-square stability and is suitable for online estimations with model mismatch and correlated noises.
Article
Computer Science, Information Systems
Jixian Zhang, Ning Xie, Xutao Yang, Xuejie Zhang, Weidong Li
Summary: This paper addresses the problem of time-varying batch virtual machine allocation and pricing in the cloud. The authors propose an integer programming model and truthful auction mechanisms, including dynamic programming and VCG algorithm, to solve the problem. In addition, the approximation ratio of the allocation algorithm in the greedy mechanism is also proved.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Mathematics, Applied
Ali Kazemy, Ramasamy Saravanakumar
Summary: This paper addresses the design problem of networked cascade control systems with two different event-triggered mechanisms for the feedback loops, considering a combination of stochastic denial-of-service attack and deception attack in the communication network. The stability theory and stochastic analysis techniques are employed to derive and formulate H infinity control design conditions in terms of linear matrix inequalities. The proposed method is evaluated using a superheater steam temperature control.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Economics
Elisheba Spiller, Ricardo Esparza, Kristina Mohlin, Karen Tapia-Ahumada, Burgin Unel
Summary: This paper uses a simulation model to analyze the impact of more advanced residential electricity tariffs on the adoption of distributed energy resources (DERs) by households. The study finds that time variant tariffs lead to greater adoption of DERs and further reduction of peak demands. Investments in rooftop photovoltaic (PV) and batteries are not privately optimal under the current tariff design scenarios, but could become more favorable with reduced PV technology costs. The study also highlights the incentives for investing in heat pumps for household space heating under cost-reflective tariffs.
Article
Economics
Allister Loder, Michiel C. J. Bliemer, Kay W. Axhausen
Summary: The paper introduces the three-dimensional macroscopic fundamental diagram network design problem (3D-MFD-NDP) to improve the performance of multimodal transportation systems. By minimizing total travel time and considering variables such as user costs and bus frequency, substantial reductions in travel time can be achieved by limiting car use and increasing its costs.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Computer Science, Software Engineering
Yao Xia, Zhiqiu Huang, Yonglong Zhang, Min Yuan, Shangguang Wang, Yu Zhou
Summary: In cloud computing, service composition faces challenges of dishonest service providers regarding cost and QoS. The proposed strategy-proof auction mechanism (SPASC) aims to address this issue, ensuring both truthfulness and individual rationality in service offerings.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Economics
Dong Mo, Xiqun (Michael) Chen, Junlin Zhang
Summary: This study models a monopoly ride-sourcing market with human-driven vehicles (HVs) and autonomous vehicles (AVs). It takes into account the congestion externality and heterogeneity of riders' perceived utility when analyzing riders' mode choice behavior. The results show that the demand rates for mixed ride service types are not necessarily monotonic to the price or fleet size due to congestion externality and the wild goose chase regime. The study also suggests that a higher AV traffic flow capacity benefits drivers and riders, and the platform should encourage riders to switch to AV service in a high demand scenario.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Mathematics, Applied
Lin Zhu, Wei -Wei Che, Xiao-Zheng Jin
Summary: This study investigates the problem of dynamic event-triggered model-free adaptive tracking control for nonlinear systems considering denial-of-service attacks and round-trip time delays. The study introduces attack compensation and delay compensation mechanisms, and develops the DET method to save communication resources. The designed DET-MFATC algorithm solves the security tracking control problem only using input and output data, and simulation results demonstrate its effectiveness.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Economics
Gregor Schwarz, Martin Bichler
Summary: One of the core reasons for urban traffic congestion is the mispricing of road capacity. This paper proposes a two-stage market for road capacity similar to other major utilities markets. However, there are three problems to be addressed: expressing preferences for numerous products, solving the large optimization problem, and finding competitive equilibrium prices in non-convex allocation problem. The researchers propose a bid language based on origin-destination pairs and solve the problems using a mixed-integer optimization approach. The results demonstrate the feasibility of the proposed wholesale markets for road capacity.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Automation & Control Systems
Hui Gao, Kaibo Shi, Hongbin Zhang
Summary: This paper proposes a novel event-triggered method and discusses finite-time extended dissipative analysis of closed-loop networked switched systems. The controller gains and event-triggered parameters are obtained by solving LMIs. Numerical examples are provided to demonstrate the effectiveness of the proposed method.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Guangpu Huang, Xiang Wu, Fanghong Guo, Li Yu, Wen-An Zhang
Summary: This article presents a novel networked rapid control prototyping system that facilitates theoretical analysis and product design of networked control systems. The system is cost-effective and convenient to deploy, with a simple structure and robust scalability. It includes a PC controller equipped with MATLAB/Simulink software and an embedded target designed with open-source hardware. The article also introduces a networked magnetic levitation control system developed using this system and proposes a discrete-time equivalent-input-disturbance-based model predictive control approach to handle practical issues in networked control systems.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Xuede Zhou, Yan Wang, Shenglin Zhang, Zhicheng Ji
Summary: This paper addresses the problem of reducing network delays and controller co-design in networked control systems (NCSs) through the use of a dual event-triggered mechanism (DETM). By reducing the amount of sampled data transmitted over the network and utilizing Lyapunov function, the network-induced delays in NCSs are effectively reduced while maintaining system stability.
Article
Computer Science, Interdisciplinary Applications
Mahmood Vahdani, Zeinab Sazvar
Summary: During the COVID-19 period, retailers increasingly turn to online selling platforms and social technologies for marketing, affecting potential customers' purchasing decisions and product demand through word-of-mouth communication. Therefore, it is crucial to study the coordinated dynamic pricing and inventory control problem under social learning.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Hardware & Architecture
Dapeng Qu, Jun Wu, Jiankun Zhang, Chengxi Gao, Haiying Shen, Keqin Li
Summary: As a pioneering network architecture, Named Data Networking (NDN) leverages the content-centric model and connectionless transmission mode to enhance network capacity. C3NDN is a congestion control scheme that utilizes caching strategy in NDN, formulating a One-Interest-Multiple-Data model to improve network efficiency and employing a probabilistic caching strategy to optimize NDN's in-network caching characteristic. Additionally, C3NDN incorporates a congestion control algorithm based on the One-Interest-Multiple-Data model, considering the bandwidth and delay information of the transmission path.
JOURNAL OF NETWORK AND COMPUTER APPLICATIONS
(2023)
Article
Management
Shi Pu, Alfredo Garcia
OPERATIONS RESEARCH
(2018)
Article
Automation & Control Systems
Davood Hajinezhad, Mingyi Hong, Alfredo Garcia
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2019)
Article
Automation & Control Systems
Shi Pu, J. Joaquin Escudero-Garzas, Alfredo Garcia, Shahin Shahrampour
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2020)
Article
Automation & Control Systems
Alfredo Garcia, Luochao Wang, Jeff Huang, Lingzhou Hong
Summary: This article explores the issue of learning models using a distributed architecture with interconnected local nodes when streaming data cannot be transferred to a single location in a timely manner. It proposes a distributed scheme where each local node implements stochastic gradient updates based on a local data stream, with a network regularization penalty used to maintain cohesion in the ensemble of models. Results show that the ensemble average approximates a stationary point and characterizes the differences between individual models and the ensemble average, highlighting the robustness of the proposed approach compared to federated learning in handling heterogeneity in data streams.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2021)
Article
Automation & Control Systems
Shixiang Chen, Alfredo Garcia, Shahin Shahrampour
Summary: The stochastic subgradient method is widely used for solving large-scale optimization problems in machine learning, especially when the problems are neither smooth nor convex. This article proposes a distributed implementation of the stochastic subgradient method with theoretical guarantee, demonstrating global convergence using the Moreau envelope stationarity measure. Additionally, it shows that deterministic DPSM linearly converges to sharp minima under a sharpness condition with geometrically diminishing step size.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Lingzhou Hong, Alfredo Garcia, Ceyhun Eksin
Summary: This paper considers a distributed estimation method for heterogeneous streams of correlated data distributed across nodes in a network. In this method, linear models are locally estimated with a network regularization term that penalizes differences between local and neighboring models. The paper analyzes computation dynamics and information exchange and provides a finite-time characterization of convergence for the weighted ensemble average estimate, comparing it to federated learning.
Article
Engineering, Electrical & Electronic
Alfredo Garcia, Roohallah Khatami, Ceyhun Eksin, Furkan Sezer
Summary: This paper proposes a new decentralized market mechanism for efficient coupling of independent electricity markets. By iteratively quoting energy trading terms, the mechanism achieves optimal flows between markets.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Psychology
Zhide Wang, Yanling Chang, Brandon J. Schmeichel, Alfredo A. Garcia
Summary: Mental fatigue has negative effects on task performance and willingness for further exertion. This study proposes a mathematical framework to model human cognitive effort allocations and estimates the effects of mental fatigue on subjective evaluations of effort expenditure. The proposed approach successfully recapitulates task performance and engagement patterns observed under mental fatigue, advancing our understanding of how cognitive operations are affected by mental fatigue.
PSYCHOLOGICAL REVIEW
(2022)
Article
Engineering, Civil
Ran Wei, Anthony D. McDonald, Alfredo Garcia, Hananeh Alambeigi
Summary: Automated vehicle technologies promise to improve traffic safety and reduce driver workload. To support the design and development of these technologies, driver behavior models have been extensively studied. Recent research has shown that driver behavior models based on human cognitive information processing achieve better generalization. In this study, active inference, a framework based on predictive processing theory, was used to model driver emergency braking responses to automation failures. The results demonstrate that the model effectively captures braking reaction times and provides insights into the relationship between driver parameters and behavior.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Yanling Chang, Alfredo Garcia, Zhide Wang, Lu Sun
Summary: This article discusses the (inverse) structural estimation of POMDPs based on observable sequences and implemented actions. The structural properties of an entropy regularized POMDP are analyzed, and conditions for model identifiability without knowledge of state dynamics are specified. A soft policy gradient algorithm is used to compute a maximum likelihood estimator, and an equipment replacement problem is used as an illustration.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Shixiang Chen, Alfredo Garcia, Mingyi Hong, Shahin Shahrampour
Summary: This paper addresses distributed non-convex optimization problem on the Stiefel manifold, proposing two decentralized algorithms, DRSGD and DRGTA, with convergence rates of O(1/root K) and O(1/K) respectively. Multi-step consensus is used to maintain iteration in the local consensus region. The DRGTA is the first decentralized algorithm achieving exact convergence for distributed optimization on the Stiefel manifold.
INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 139
(2021)
Proceedings Paper
Automation & Control Systems
Lingzhou Hong, Alfredo Garcia, Ceyhun Eksin
2020 59TH IEEE CONFERENCE ON DECISION AND CONTROL (CDC)
(2020)
Article
Computer Science, Information Systems
J. J. Escudero-Garzas, Carlos Bousono-Calzon, Alfredo Garcia
Proceedings Paper
Transportation Science & Technology
J. J. Escudero-Garzas, A. Garcia, Stephen G. Wilson
2018 IEEE 88TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL)
(2018)
Correction
Automation & Control Systems
Shi Pu, Alfredo Garcia
SIAM JOURNAL ON CONTROL AND OPTIMIZATION
(2018)
