Article
Engineering, Civil
Yuan Tang, Ning Zhou, Qiao Yu, Di Wu, Chong Hou, Guangming Tao, Min Chen
Summary: With the commercialization of 5G and the beginning of the exploration of 6G, the global industry is looking to transform the service of mobile communication technology. The proposed 6G Semantic Communication Scheme based on Intelligent Fabrics for transportation in-cabin scenarios (6GSCS-IF) and the Deep Learning-based Semantic Communication Model for Time-series data (DL-SCMT) demonstrate the potential of intelligent fabrics and deep learning in achieving intelligent sensory interaction and providing better communication services compared to traditional methods.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Telecommunications
Lokendra Vishwakarma, Debasis Das
Summary: The proposed SmartCoin mechanism aims to improve the safety and efficiency of the transportation network by providing incentives for vehicles based on blockchain technology, encouraging more vehicles to participate in network improvement, and reducing traffic congestion and road accidents.
VEHICULAR COMMUNICATIONS
(2022)
Article
Engineering, Civil
Dandan Meng, Xin Li, Wei Wang
Summary: This paper introduces an architecture for vehicle position estimation in traffic congestion, which consists of three unmanned aerial vehicles (UAVs) equipped with a uniform linear array (ULA), an ITS center, and a terminal for position estimation. The UAV collects data from the ULA, the ITS center stores data, and the terminal executes the corresponding DOA estimation algorithm to estimate the vehicle position. A robust sparse recovery framework based on optimal weighted subspace fitting is proposed for DOA estimation in the presence of direction-dependent unknown mutual coupling. Experimental results demonstrate the superiority and robustness of the proposed architecture and algorithm.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Jun Liu, Lei Zhang, Chunlin Li, Jingpan Bai, Haibin Lv, Zhihan Lv
Summary: This study aims to improve the communication security of Internet of Vehicles (IoV) nodes in intelligent transportation by studying the safety of IoV in smart transportation based on Blockchain. An IoV DTs model combining big data with Digital Twins (DTs) is built, and a secure communication architecture based on immutable and trackable BC data is proposed to address current IoV communication security issues. Additionally, a WaGAN model based on Wasserstein Distance is utilized to construct an IoV node risk forecast model. Furthermore, a Group Authentication and Privacy-preserving (GAP) scheme is put forward to handle network channel congestion caused by simultaneous connections of in-vehicle devices in IoV. In summary, this research has significant value in improving the security of information sharing in IoV.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Weiyuan Huang, Yanyan Chen, Xun Zhu
Summary: With the development of network technology and multimedia technology, the multimedia communication system has played an important role in the intelligent transportation system, improving communication efficiency and traffic management, and reducing traffic accidents.
JOURNAL OF ADVANCED TRANSPORTATION
(2022)
Article
Engineering, Civil
Yajie He, Menglei Kong, Chunshan Du, Dingyi Yao, Miao Yu
Summary: This paper analyzes the security issues of the Internet of Vehicles (IoV) in the 5G environment and proposes an access control mechanism based on risk prediction and a Combined Generative Adversarial Network (WCGAN) based on Wasserstein Distance. Experimental results show that the WCGAN model has a smaller prediction error and higher prediction accuracy in terms of node packet transmission rate compared to the traditional BP neural network.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Ikram Ud Din, Kamran Ahmad Awan, Ahmad Almogren
Summary: This paper introduces an innovative Context-Aware Cognitive Memory Trust Management System (CACMTM) tailored for Intelligent Cyber-Physical Transportation Systems (ICPTS). The system utilizes game theory to model trust interactions and integrates various trust constituents into a dependable solution, specifically addressing the unique demands of ICPTS. It incorporates a cognitive memory-based trust management method for IoT in the metaverse and employs a multi-dimensional trust evaluation model to minimize the risk of false trust evaluation outcomes. The proposed system also integrates a blockchain-secured logging mechanism for enhanced security, transparency, and accountability.
Article
Chemistry, Analytical
Prafull Kasture, Hidekazu Nishimura
Summary: The study reveals that in ant transportation system, ants utilize cooperative perception and communication mechanisms to avoid traffic congestion and maintain a constant speed through clever self-organization.
Article
Engineering, Civil
Zinuo Cai, Zebin Chen, Zihan Liu, Quanmin Xie, Ruhui Ma, Haibing Guan
Summary: Modern transportation big data presents challenges in developing an intelligent transportation system due to its high Volume, Velocity, and Variety. Current transportation systems rely on cloud computing but face issues of real-time processing and under-utilization of smart roadside devices. In this study, we propose RIDIC, an intelligent transportation system utilizing dispersed computing, which provides real-time response and fully utilizes smart devices. The experiments conducted in road vehicle detection and traffic signal recognition scenarios demonstrate that RIDIC can process transportation big data faster while reducing the demand for device computing resources.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Moayad Aloqaily, Haya Elayan, Mohsen Guizani
Summary: The advancement of wireless connectivity in smart cities enhances connections between key elements, and the federated intelligent health monitoring systems in autonomous vehicles contribute to improving quality of life. This study proposes C-HealthIER, a cooperative health intelligent emergency response system that monitors passengers' health and conducts cooperative behavior to reduce emergency treatment time and distance by sharing information between vehicles and infrastructure.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Juan Casavilca Silva, Muhammad Saadi, Lunchakorn Wuttisittikulkij, Davi Ribeiro Militani, Renata Lopes Rosa, Demostenes Zegarra Rodriguez, Sattam Al Otaibi
Summary: A learning-based framework for directly simulating the LF distribution is proposed to address the surface errors of MLA and limited pixel count issues in LF cameras. Experimental results demonstrate that the method outperforms existing approaches in LF image reconstruction, showing effective learning of LF distribution and generation of high-quality LF images.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Miao Yu
Summary: The purpose of this research is to explore the construction status and prediction performance of intelligent transportation systems in the road network of smart cities based on 5G network. The study proposes a resource real-time load balancing scheduling approach and improves the deep learning algorithm used. The results show that the proposed algorithm outperforms other models in terms of prediction accuracy and network performance, providing an experimental basis for the intelligent development of transportation in smart cities.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Hardware & Architecture
Asma Belhadi, Youcef Djenouri, Gautam Srivastava, Jerry Chun-Wei Lin
Summary: This paper presents a secure and scalable intelligent transportation and human behavior system that utilizes blockchain technology and efficient GPU processing, with a reinforced deep learning algorithm to merge local knowledge into global knowledge. Experimental results demonstrate its superiority over baseline solutions in outlier detection.
JOURNAL OF SUPERCOMPUTING
(2021)
Article
Optics
Song Song, Yejun Liu, Tianming Xu, Shasha Liao, Lei Guo
Summary: This paper investigates channel fading prediction in FSO communication, by establishing an experimental platform and achieving high-precision prediction using neural networks.
Article
Engineering, Civil
Cheng Dai, Ying Zhang, Zhigao Zheng
Summary: Predicting traffic flow is essential in intelligent transportation systems, but missing information in traffic data affects performance. Nuclear Norm-based Tensor Completion algorithm tackles this issue through truncated nuclear norm minimization. However, the existing threshold may excessively penalize large singular values, resulting in accurate data missing. To solve this problem, a new method is proposed, considering prior rank information and retaining large singular values. Extensive experiments confirm better recovery accuracy with this method.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Chemical
Yu-Lin Lee, Chang-Hua Lin, Hwa-Dong Liu
Summary: This study proposes an induction heating system with MPPT control strategy, which has advantages of high efficiency, high stability, and high heating speed.
Article
Engineering, Electrical & Electronic
Yu-Lin Lee, Chang-Hua Lin, Shoeb Azam Farooqui, Hwa-Dong Liu, Javed Ahmad
Summary: The battery management system (BMS) is crucial in monitoring and controlling the charging/discharging process, ensuring safety and protection of the battery, and estimating its state of health and charge. Battery balancing, an important technology in BMS, affects the usable capacity range and lifetime of the battery module. This study developed a balancing model and proposed a Master-Slave BMS (MS-BMS) to validate the model, considering factors such as balancing skill, power, speed, control simplicity, modularity, and cost. The performance of the proposed BMS was compared with existing modular BMS architecture, demonstrating advantages in terms of equalization speed, control simplicity, modularity, and cost.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Engineering, Electrical & Electronic
Chang-Hua Lin, Javed Ahmad, Ren-Hao Li, Hwa-Dong Liu
Summary: This article presents a modular adjustable high-voltage pulse (MAHVP) generation system that utilizes full-bridge LLC resonant converters to increase the output voltage. The system uses a unique burst mode and variable frequency voltage sharing (BMVFVS) control mechanism to improve performance under heavy load conditions, while operating in burst mode for light load conditions. A hardware prototype with a maximum output voltage of 6 kV and an efficiency of 97% is developed to validate the feasibility and effectiveness of the proposed system.
IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS
(2023)
Article
Engineering, Chemical
Shoeb Azam Farooqui, Chang-Hua Lin, Shiue-Der Lu, Hwa-Dong Liu, Adil Sarwar, Liang-Yin Huang
Summary: An exponential curve-based (ECB) control strategy has been proposed to drive an isolated three-phase inverter (ITPI) and generate a stable and high-quality three-phase output. By detecting the Fourier expansion series of the auxiliary equipment power supply system's (AEPSS) three-phase output voltage level, the ECB control strategy quickly adjusts the duty cycle to optimize the performance.
Article
Engineering, Chemical
Bushra Sabir, Shiue-Der Lu, Hwa-Dong Liu, Chang-Hua Lin, Adil Sarwar, Liang-Yin Huang
Summary: This study proposes a new isolated intelligent adjustable buck-boost (IIABB) converter with an intelligent control strategy for regenerative energy systems. It utilizes the hill climbing maximum power point tracking (MPPT) algorithm to enhance system performance. The IIABB converter is simulated and compared with the conventional SEPIC converter, showing better efficiency and stable output voltage.
Article
Engineering, Chemical
Rashid Ahmed Khan, Hwa-Dong Liu, Chang-Hua Lin, Shiue-Der Lu, Shih-Jen Yang, Adil Sarwar
Summary: This study proposes a novel high-voltage gain step-up (HVGSU) DC-DC converter for solar photovoltaic system operation with a maximum power point (MPP) tracker. The converter combines primary boost conversion cell, switched capacitors, and voltage multiplier cells. A clamp circuit is used to minimize switch voltage stress and power loss, while the inductor reduces diode's reverse recovery losses. The prototype circuit shows a weighted efficiency of 90-96% and supports the theoretical analysis and claimed benefits.
Article
Green & Sustainable Science & Technology
Ifham H. H. Malick, Mohammad Zaid, Javed Ahmad, Kazem Varesi, Chang-Hua Lin
Summary: In this paper, a new buck-boost converter with reliability analysis is proposed, which utilizes a new voltage multiplier cell to boost the output voltage. The converter has continuous input current and can operate in a wide range of duty cycles. A detailed reliability analysis is conducted using improved Markov modeling, considering open circuit and short circuit faults. The article also discusses the variation of reliability and mean time to failure with different converter parameters.
IET RENEWABLE POWER GENERATION
(2023)
Article
Engineering, Chemical
Khalil Ur Rehman, Injila Sajid, Shiue-Der Lu, Shafiq Ahmad, Hwa-Dong Liu, Farhad Ilahi Bakhsh, Mohd Tariq, Adil Sarwar, Chang-Hua Lin
Summary: This paper proposes a new technique for tracking the global maximum power point (GMPP) in partially shaded photovoltaic systems, based on the Ali Baba and the Forty Thieves (AFT) algorithm. Experimental and simulation results show that this method performs better than particle swarm optimization (PSO) under complex partial irradiance conditions.
Article
Engineering, Chemical
Md Adil Azad, Injila Sajid, Shiue-Der Lu, Adil Sarwar, Mohd Tariq, Shafiq Ahmad, Hwa-Dong Liu, Chang-Hua Lin, Haitham A. Mahmoud
Summary: This research presents the energy-valley-optimizer-based optimization (EVO) technique, which efficiently tackles the issue of partial shading in photovoltaic systems. The technique enhances the speed of tracking and minimizes power output fluctuations.
Article
Engineering, Chemical
Hwa-Dong Liu, Ping-Jui Lin, Shan-Xun Lai, Chang-Hua Lin, Shoeb-Azam Farooqui
Summary: This study aims to develop an image recognition curve-fitting control strategy integrated with a cloud monitoring technique for electric self-driving vehicles to improve their operation efficiency. The proposed strategy combines cameras and a cloud platform to adjust control parameters and remove road obstacles promptly. Comparing with the traditional method, the results show that this control strategy performs better in terms of speed, efficiency, and flexibility.
Article
Engineering, Chemical
Hwa-Dong Liu, Jhen-Ting Lin, Xin-Wen Lin, Chang-Hua Lin, Shoeb-Azam Farooqui
Summary: This study presents a standalone solar power system that utilizes a novel maximum power point tracking algorithm and adjustable frequency and duty cycle control strategy to optimize system efficiency and power quality. Experimental results demonstrate high efficiency under different irradiance conditions. Additionally, the system improves AC voltage and current through an improved inverter, ensuring stable output voltage and better power quality.
Article
Engineering, Chemical
Injila Sajid, Ayushi Gautam, Adil Sarwar, Mohd Tariq, Hwa-Dong Liu, Shafiq Ahmad, Chang-Hua Lin, Abdelaty Edrees Sayed
Summary: This research proposes the dandelion optimizer (DO) as a solution for achieving maximum power point tracking (MPPT) in photovoltaic (PV) arrays under partial shading (PS) conditions. The effectiveness of the DO algorithm in enhancing the performance of MPPT in PV arrays, particularly in challenging partial shading conditions, is demonstrated through simulation and real-time hardware-in-the-loop (HIL) results.
Article
Mathematics
Mohammad Suhail Khan, Chang-Hua Lin, Javed Ahmad, Mohammad Fahad, Hwa-Dong Liu
Summary: This paper presents a novel isolated single-ended-primary-inductance converter (SEPIC) with a model predictive control (MPC) approach for DC electronic loads. The proposed converter uses a transformer for isolation, allowing for higher switching frequency and smaller passive components. Experimental results show satisfactory performance under steady state and sudden input voltage transients. The elimination of the coupled inductor in the circuit eliminates high voltage spikes caused by leakage inductances, making it suitable for medium power applications.
Article
Mathematics
Chang-Hua Lin, Shoeb Azam Farooqui, Hwa-Dong Liu, Jian-Jang Huang, Mohd Fahad
Summary: This article investigates a single-phase five-level T-type topology and applies the finite control set model predictive control (FCS-MPC) strategy to improve the performance and reliability of the system. The topology shows reliability, fault-tolerance, and high-quality output characteristics, making it suitable for renewable energy systems.
Article
Engineering, Electrical & Electronic
Ibrahim Harbi, Jose Rodriguez, Amirreza Poorfakhraei, Hani Vahedi, Miguel Guse, Mohamed Trabelsi, Mohamed Abdelrahem, Mostafa Ahmed, Mohammad Fahad, Chang-Hua Lin, Thiwanka Wijekoon, Wei Tian, Marcelo Lobo Heldwein, Ralph Kennel
Summary: Multilevel converters are widely used for medium- and high-power/voltage applications and have also been extended to low-power applications. Common dc-link MLCs, which eliminate the need for bulky and inefficient transformers and rectifiers, have received particular attention in industry. However, there is currently no comprehensive review article dedicated to common dc-link topologies. This article fills this gap by providing a comprehensive review of common dc-link MLCs and discussing their features, topologies, modulation techniques, control strategies, and industrial applications.
IEEE OPEN JOURNAL OF POWER ELECTRONICS
(2023)