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  Subjects -> ELECTRONICS (Total: 207 journals)
Showing 1 - 200 of 277 Journals sorted by number of followers
IEEE Transactions on Aerospace and Electronic Systems     Hybrid Journal   (Followers: 313)
Control Systems     Hybrid Journal   (Followers: 253)
IEEE Transactions on Geoscience and Remote Sensing     Hybrid Journal   (Followers: 201)
Journal of Guidance, Control, and Dynamics     Hybrid Journal   (Followers: 197)
Electronics     Open Access   (Followers: 138)
Advances in Electronics     Open Access   (Followers: 133)
Electronic Design     Partially Free   (Followers: 129)
Electronics For You     Partially Free   (Followers: 128)
IEEE Antennas and Propagation Magazine     Hybrid Journal   (Followers: 120)
IEEE Power Electronics Magazine     Full-text available via subscription   (Followers: 91)
IEEE Transactions on Power Electronics     Hybrid Journal   (Followers: 89)
IEEE Antennas and Wireless Propagation Letters     Hybrid Journal   (Followers: 88)
IEEE Transactions on Software Engineering     Hybrid Journal   (Followers: 84)
IEEE Transactions on Industrial Electronics     Hybrid Journal   (Followers: 84)
IEEE Transactions on Antennas and Propagation     Full-text available via subscription   (Followers: 81)
IET Power Electronics     Open Access   (Followers: 70)
IEEE Transactions on Automatic Control     Hybrid Journal   (Followers: 67)
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of     Hybrid Journal   (Followers: 63)
IEEE Embedded Systems Letters     Hybrid Journal   (Followers: 62)
IEEE Transactions on Industry Applications     Hybrid Journal   (Followers: 58)
IEEE Journal of Emerging and Selected Topics in Power Electronics     Hybrid Journal   (Followers: 53)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 53)
Advances in Power Electronics     Open Access   (Followers: 49)
IEEE Nanotechnology Magazine     Hybrid Journal   (Followers: 45)
IEEE Transactions on Consumer Electronics     Hybrid Journal   (Followers: 45)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 41)
IEEE Transactions on Biomedical Engineering     Hybrid Journal   (Followers: 35)
IEEE Transactions on Circuits and Systems for Video Technology     Hybrid Journal   (Followers: 34)
IET Microwaves, Antennas & Propagation     Open Access   (Followers: 34)
Journal of Physics B: Atomic, Molecular and Optical Physics     Hybrid Journal   (Followers: 32)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 30)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 28)
Electronics Letters     Open Access   (Followers: 28)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 27)
Microelectronics and Solid State Electronics     Open Access   (Followers: 27)
International Journal of Power Electronics     Hybrid Journal   (Followers: 24)
International Journal of Aerospace Innovations     Full-text available via subscription   (Followers: 24)
Journal of Sensors     Open Access   (Followers: 23)
International Journal of Image, Graphics and Signal Processing     Open Access   (Followers: 22)
IEEE Reviews in Biomedical Engineering     Hybrid Journal   (Followers: 20)
IEEE/OSA Journal of Optical Communications and Networking     Hybrid Journal   (Followers: 19)
IEEE Transactions on Electron Devices     Hybrid Journal   (Followers: 18)
Journal of Artificial Intelligence     Open Access   (Followers: 18)
Journal of Power Electronics & Power Systems     Full-text available via subscription   (Followers: 17)
IET Wireless Sensor Systems     Open Access   (Followers: 17)
Circuits and Systems     Open Access   (Followers: 16)
Archives of Electrical Engineering     Open Access   (Followers: 15)
International Journal of Control     Hybrid Journal   (Followers: 14)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 14)
International Journal of Advanced Research in Computer Science and Electronics Engineering     Open Access   (Followers: 14)
IEEE Women in Engineering Magazine     Hybrid Journal   (Followers: 13)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
IEEE Solid-State Circuits Magazine     Hybrid Journal   (Followers: 13)
Machine Learning with Applications     Full-text available via subscription   (Followers: 12)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 12)
IEEE Transactions on Broadcasting     Hybrid Journal   (Followers: 12)
IEEE Transactions on Learning Technologies     Full-text available via subscription   (Followers: 12)
IEICE - Transactions on Electronics     Full-text available via subscription   (Followers: 11)
International Journal of Sensors, Wireless Communications and Control     Hybrid Journal   (Followers: 11)
International Journal of Microwave and Wireless Technologies     Hybrid Journal   (Followers: 11)
International Journal of Advanced Electronics and Communication Systems     Open Access   (Followers: 11)
Journal of Low Power Electronics     Full-text available via subscription   (Followers: 11)
Open Journal of Antennas and Propagation     Open Access   (Followers: 10)
Solid-State Electronics     Hybrid Journal   (Followers: 10)
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 10)
IETE Journal of Research     Open Access   (Followers: 10)
Batteries     Open Access   (Followers: 9)
Electronics and Communications in Japan     Hybrid Journal   (Followers: 9)
International Journal of Wireless and Microwave Technologies     Open Access   (Followers: 9)
IETE Technical Review     Open Access   (Followers: 9)
Nature Electronics     Hybrid Journal   (Followers: 9)
Journal of Signal and Information Processing     Open Access   (Followers: 9)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
IEEE Journal of the Electron Devices Society     Open Access   (Followers: 8)
International Journal of Electronics and Telecommunications     Open Access   (Followers: 8)
Journal of Electromagnetic Waves and Applications     Hybrid Journal   (Followers: 8)
China Communications     Full-text available via subscription   (Followers: 8)
Superconductivity     Full-text available via subscription   (Followers: 8)
IEEE Transactions on Autonomous Mental Development     Hybrid Journal   (Followers: 8)
Journal of Low Power Electronics and Applications     Open Access   (Followers: 8)
International Journal of Antennas and Propagation     Open Access   (Followers: 8)
Journal of Electronic Design Technology     Full-text available via subscription   (Followers: 8)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 8)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Power Electronic Devices and Components     Open Access   (Followers: 7)
Foundations and Trends® in Signal Processing     Full-text available via subscription   (Followers: 7)
Nanotechnology, Science and Applications     Open Access   (Followers: 7)
IEEE Magnetics Letters     Hybrid Journal   (Followers: 7)
Progress in Quantum Electronics     Full-text available via subscription   (Followers: 7)
Foundations and Trends® in Communications and Information Theory     Full-text available via subscription   (Followers: 6)
Metrology and Measurement Systems     Open Access   (Followers: 6)
Advances in Biosensors and Bioelectronics     Open Access   (Followers: 6)
International Journal of Systems, Control and Communications     Hybrid Journal   (Followers: 6)
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access   (Followers: 6)
International Journal of Electronics     Hybrid Journal   (Followers: 6)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 6)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Journal of Power Electronics     Hybrid Journal   (Followers: 6)
Annals of Telecommunications     Hybrid Journal   (Followers: 6)
Electronic Markets     Hybrid Journal   (Followers: 6)
Energy Storage Materials     Full-text available via subscription   (Followers: 6)
IEEE Transactions on Services Computing     Hybrid Journal   (Followers: 5)
International Journal of Computational Vision and Robotics     Hybrid Journal   (Followers: 5)
Journal of Optoelectronics Engineering     Open Access   (Followers: 5)
Journal of Electromagnetic Analysis and Applications     Open Access   (Followers: 5)
Journal of Field Robotics     Hybrid Journal   (Followers: 5)
Journal of Electronics (China)     Hybrid Journal   (Followers: 5)
Batteries & Supercaps     Hybrid Journal   (Followers: 5)
IEEE Pulse     Hybrid Journal   (Followers: 5)
Journal of Microelectronics and Electronic Packaging     Hybrid Journal   (Followers: 4)
Networks: an International Journal     Hybrid Journal   (Followers: 4)
EPE Journal : European Power Electronics and Drives     Hybrid Journal   (Followers: 4)
Advanced Materials Technologies     Hybrid Journal   (Followers: 4)
Frontiers in Electronics     Open Access   (Followers: 4)
Wireless and Mobile Technologies     Open Access   (Followers: 4)
Synthesis Lectures on Power Electronics     Full-text available via subscription   (Followers: 4)
Journal of Energy Storage     Full-text available via subscription   (Followers: 4)
IEEE Transactions on Haptics     Hybrid Journal   (Followers: 4)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 4)
Journal of Circuits, Systems, and Computers     Hybrid Journal   (Followers: 4)
International Journal of Review in Electronics & Communication Engineering     Open Access   (Followers: 4)
Electronic Materials Letters     Hybrid Journal   (Followers: 4)
Journal of Biosensors & Bioelectronics     Open Access   (Followers: 4)
Biomedical Instrumentation & Technology     Hybrid Journal   (Followers: 4)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
Informatik-Spektrum     Hybrid Journal   (Followers: 3)
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits     Hybrid Journal   (Followers: 3)
International Journal of Numerical Modelling: Electronic Networks, Devices and Fields     Hybrid Journal   (Followers: 3)
Advancing Microelectronics     Hybrid Journal   (Followers: 3)
International Journal of Applied Electronics in Physics & Robotics     Open Access   (Followers: 3)
IETE Journal of Education     Open Access   (Followers: 3)
Superconductor Science and Technology     Hybrid Journal   (Followers: 3)
Sensors International     Open Access   (Followers: 3)
e-Prime : Advances in Electrical Engineering, Electronics and Energy     Open Access   (Followers: 3)
EPJ Quantum Technology     Open Access   (Followers: 3)
Frontiers of Optoelectronics     Hybrid Journal   (Followers: 3)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 2)
ACS Applied Electronic Materials     Open Access   (Followers: 2)
IET Smart Grid     Open Access   (Followers: 2)
Energy Storage     Hybrid Journal   (Followers: 2)
Journal of Microwave Power and Electromagnetic Energy     Hybrid Journal   (Followers: 2)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal   (Followers: 2)
Journal of Information and Telecommunication     Open Access   (Followers: 2)
TELKOMNIKA (Telecommunication, Computing, Electronics and Control)     Open Access   (Followers: 2)
Journal of Semiconductors     Full-text available via subscription   (Followers: 2)
Radiophysics and Quantum Electronics     Hybrid Journal   (Followers: 2)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
Journal of Intelligent Procedures in Electrical Technology     Open Access   (Followers: 2)
Sensing and Imaging : An International Journal     Hybrid Journal   (Followers: 2)
Security and Communication Networks     Hybrid Journal   (Followers: 2)
Journal of Nuclear Cardiology     Hybrid Journal   (Followers: 2)
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 1)
IET Energy Systems Integration     Open Access   (Followers: 1)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 1)
International Journal of Granular Computing, Rough Sets and Intelligent Systems     Hybrid Journal   (Followers: 1)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 1)
Journal of Computational Intelligence and Electronic Systems     Full-text available via subscription   (Followers: 1)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)
Open Electrical & Electronic Engineering Journal     Open Access   (Followers: 1)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 1)
Journal of Advanced Dielectrics     Open Access   (Followers: 1)
Transactions on Cryptographic Hardware and Embedded Systems     Open Access   (Followers: 1)
International Journal of Hybrid Intelligence     Hybrid Journal   (Followers: 1)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
IET Cyber-Physical Systems : Theory & Applications     Open Access   (Followers: 1)
Edu Elektrika Journal     Open Access   (Followers: 1)
Power Electronics and Drives     Open Access   (Followers: 1)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access  
npj Flexible Electronics     Open Access  
Elektronika ir Elektortechnika     Open Access  
Emitor : Jurnal Teknik Elektro     Open Access  
IEEE Solid-State Circuits Letters     Hybrid Journal  
IEEE Open Journal of Industry Applications     Open Access  
IEEE Open Journal of the Industrial Electronics Society     Open Access  
IEEE Open Journal of Circuits and Systems     Open Access  
Journal of Electronic Science and Technology     Open Access  
Solid State Electronics Letters     Open Access  
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
Journal of Engineered Fibers and Fabrics     Open Access  
Jurnal Teknologi Elektro     Open Access  
IET Nanodielectrics     Open Access  
Elkha : Jurnal Teknik Elektro     Open Access  
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Jurnal Teknik Elektro     Open Access  
IACR Transactions on Symmetric Cryptology     Open Access  
Acta Electronica Malaysia     Open Access  
Bioelectronics in Medicine     Hybrid Journal  
Chinese Journal of Electronics     Open Access  
Problemy Peredachi Informatsii     Full-text available via subscription  
Technical Report Electronics and Computer Engineering     Open Access  
Jurnal Rekayasa Elektrika     Open Access  
Facta Universitatis, Series : Electronics and Energetics     Open Access  
Visión Electrónica : algo más que un estado sólido     Open Access  
Telematique     Open Access  
International Journal of Nanoscience     Hybrid Journal  
International Journal of High Speed Electronics and Systems     Hybrid Journal  
Semiconductors and Semimetals     Full-text available via subscription  

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Intelligent Transportation Systems Magazine, IEEE
Journal Prestige (SJR): 0.816
Citation Impact (citeScore): 4
Number of Followers: 12  
 
  Full-text available via subscription Subscription journal
ISSN (Print) 1939-1390
Published by IEEE Homepage  [228 journals]
  • IEEE Collabratec filler

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      Issue No: Vol. 14, No. 6 (2022)
       
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      Abstract: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
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  • On Chinese Parallel Mobility Paradigm [Editor’s Column]

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      Authors: Ljubo Vlacic;
      Pages: 3 - 4
      Abstract: China was quite behind the United States, Germany, and some other countries when it comes to permitting testing of self-driving cars on public roads. However, this is no longer the case as China now leads the way by permitting commercial operations of self-driving vehicles.
      PubDate: Nov.-Dec. 2022
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  • Blockchain-Based Intelligent Transportation Systems: The Human Use of
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      Authors: Cristina Olaverri-Monreal;
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      Abstract: The interconnected objects, infrastructure, and data that form the base of cyberphysical systems use a broad range of electronic technologies to improve the usage of civil infrastructure and make transportation systems safe, efficient, reliable, and environmentally friendly. These existing relationships have established a strong relevance for potential future developments in automation and data exchange in the field of intelligent transportation systems (ITS). Collaborative platforms to acquire data; advanced driver assistance systems; or other tools, such as simulation platforms with connectivity and automation capabilities, are examples of the possibilities for the systemic coverage of many aspects of the automotive, transport, and mobility system, and they make it possible to address interdisciplinary holistic problems that include aspects from social sciences, transport, planning, robotics, and communication technologies.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • DeCAST in TransVerse for Parallel Intelligent Transportation Systems and
           Smart Cities: Three Decades and Beyond

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      Authors: Chen Zhao;Yisheng Lv;Junchen Jin;Yonglin Tian;Jiangong Wang;Fei-Yue Wang;
      Pages: 6 - 17
      Abstract: Parallel transportation management and control was proposed three decades ago as a new paradigm for conducting complex transportation operations and has led to today’s DeCAST in TransVerse platform designed and constructed according to the principle of decentralized/distributed autonomous operations and organizations. This article presents an overview of its architectures, processes, operating procedures, and major applications. The developments and applications have demonstrated clearly that parallel transportation systems are effective for networked traffic control and distributed logistical operations. The existing challenges and emerging opportunities are also addressed. A transportation foundation model based on parallel learning and federated intelligence is proposed as a potential path to the next-generation parallel intelligent transportation systems.
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      Issue No: Vol. 14, No. 6 (2022)
       
  • Parallel Intelligence for Smart Mobility in Cyberphysical Social
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      Authors: Kunhua Liu;Leixin Li;Yisheng Lv;Dongpu Cao;Zhongmin Liu;Long Chen;
      Pages: 18 - 25
      Abstract: On 27 June 2018, the International Parallel Driving Alliance (iPDA) inaugural conference was held in Changshu, China. The iPDA consists of 24 well-known institutions, e.g., the University of Cambridge, Purdue University Indianapolis, and the Royal Institute of Technology of Sweden. The iPDA aims to co-establish a common shared research platform for parallel driving and a timely exchange of the latest research results and data related to parallel driving. During the conference, participants discussed the definition, applications, and future challenges of parallel driving and generally agreed that it is a solution to the current autonomous driving problem. Five keynote speakers presented parallel driving with intelligent vehicle theme talks to share their perspectives, field applications, and outlooks on industry trends and future research.
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      Issue No: Vol. 14, No. 6 (2022)
       
  • An Integrated Traffic and Vehicle Co-Simulation Testing Framework for
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      Authors: Yunyang Shi;Zhongkai Liu;Zihan Wang;Jiajun Ye;Weiping Tong;Zhiyuan Liu;
      Pages: 26 - 40
      Abstract: Simulation testing is critical for the development and optimization of connected and autonomous vehicle (CAV) driving systems. Existing simulation tools for autonomous driving testing generally focus on single-vehicle-based perception, decision, and control. Nevertheless, cooperative maneuvering among CAV and human-driven vehicles is of utmost importance in many high-value scenarios, e.g., intersections, platooning, and bottlenecks. To this end, this article aims to establish a comprehensive and realistic co-simulation framework that combines both vehicle and traffic simulation. For the sake of presentation and without loss of generality, CARLA is employed for vehicle simulation as it features high-fidelity vehicle dynamics models, while Simulation of Urban Mobility is employed for traffic simulation as it provides advanced traffic models. Further, vehicle trajectory extraction technology is applied to extract vehicle trajectories from videos and use them as an input of the co-simulation framework. Moreover, three different scenarios comprising the presence of obstacles on the highway, congested city intersections, and complete CAV testing are described to verify the rationality of the framework. The real data-driven, full-chain co-simulation testing method proposed in this article can provide a realistic virtual environment for testing decision- and motion-planning level vehicular functions of CAVs.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • The Role of Digital Twins in Connected and Automated Vehicles

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      Authors: Chris Schwarz;Ziran Wang;
      Pages: 41 - 51
      Abstract: Digital twins found their genesis in the halls of NASA and the methods of product lifecycle management. Rapidly evolving trends around the proliferation of sensors, the Internet of Things, Industry 4.0, and cyber-physical systems have spurred the growth of digital twins. This paper reviews digital twins and their use in connected and automated vehicles (CAVs). Strictly speaking, digital twins must have communication between a physical system and its model, as opposed to similar methodologies that achieve indirect communication through iteration, or that substitute different parts of a system simulation with bits of hardware or software for testing. In practice, new methodologies for testing CAVs are sufficiently complex and difficult to apply simple labels. This is seen in our review of vehicular digital twins. Several gaps and challenges are apparent for the continued advancement of digital twin applications. We note some developing areas as traffic management centers, digital maps, onboard diagnostics, and logistics. Digital twins foster model reuse and encourage the use of multiple models at different scales of resolution. The role of digital twins will continue to grow as models become more tightly integrated to the physical systems they represent. This will drive such models towards uniqueness (matching a particular vehicle or road), adaptability (evolving with changing conditions and subject to wear and tear), and interpretability (conveying useful information to a human user). A maturing connected infrastructure and the development of smart cities will cause the number of new digital twin services to explode in a myriad of unforeseen ways.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Evaluating Cybersecurity Risks of Cooperative Ramp Merging in Mixed
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      Authors: Xuanpeng Zhao;Ahmed Abdo;Xishun Liao;Matthew J. Barth;Guoyuan Wu;
      Pages: 52 - 65
      Abstract: Connected and automated vehicle (CAV) technology has the potential to greatly improve transportation mobility, safety, and energy efficiency. However, ubiquitous vehicular connectivity also opens up the door to cyberattacks. In this study, we investigate cybersecurity risks of a representative cooperative traffic management application, i.e., highway on-ramp merging, in a mixed traffic environment. We develop threat models with two trajectory spoofing strategies on CAVs to create traffic congestion and devise an attack-resilient strategy for system defense. Furthermore, we leverage VEhicular NeTwork Open Simulator, a Veins extension simulator made for CAV applications, to evaluate cybersecurity risks of the attacks and performance of the proposed defense strategy. A comprehensive case study is conducted across different traffic congestion levels, penetration rates of CAVs, and attack ratios. As expected, the results show that mobility performance decreases up to 55.19% in the worst case when the attack ratio increases, as do safety and energy. With our proposed mitigation defense algorithm, the system’s cyberattack resiliency is greatly improved.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • The Internet of Things for Smart Roads: A Road Map From Present to Future
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      Authors: Guoqiang Mao;Yilong Hui;Xiaojiang Ren;Changle Li;Yongjun Shao;
      Pages: 66 - 76
      Abstract: Smart roads can potentially improve the safety and efficiency of present transportation systems and promote the future mass deployment of connected and autonomous vehicles (CAVs). In this article, based on the experience and lessons we learned from our research, field implementation, and industry engagement, we present our view about the phased and spiral development of smart roads and CAVs. A particular focus is on the development of an Internet of Things (IoT)-based system for smart roads to enable construction of a digital twin of the traffic and road system and various applications that can be built on that basis to improve the traffic safety and efficiency of current transportation systems, and the evolution of the IoT system to support the future mass deployment of CAVs.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Testing Predictive Automated Driving Systems: Lessons Learned and Future
           Recommendations

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      Authors: Rubén Izquierdo Gonzalo;Carlota Salinas Maldonado;Javier Alonso Ruiz;Ignacio Parra Alonso;David Fernández Llorca;Miguel Ángel Sotelo;
      Pages: 77 - 93
      Abstract: Conventional vehicles are certified through classical approaches, where different physical certification tests are set up on test tracks to assess the required safety levels. These approaches are well suited for vehicles with limited complexity and limited interactions with other entities as last-second resources. However, these approaches do not allow the evaluation of safety with real behaviors for critical and edge cases nor the evaluation of the ability to anticipate them in the mid or long term. This is particularly relevant for automated and autonomous driving functions that make use of advanced predictive systems to anticipate future actions and motions to be considered in the path planning layer. In this article, we present and analyze the results of physical tests on the proving grounds of several predictive systems in automated driving functions developed within the framework of the BRidging Gaps for the Adoption of Automated VEhicles (BRAVE) project. Based on our experience in testing predictive automated driving functions, we identify the main limitations of current physical testing approaches when dealing with predictive systems, analyze the main challenges ahead, and provide a set of practical actions and recommendations to consider in future physical testing procedures for automated and autonomous driving functions.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Urban Road Safety Prediction: A Satellite Navigation Perspective

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      Authors: Halim Lee;Jiwon Seo;Zaher Zak M. Kassas;
      Pages: 94 - 106
      Abstract: Predicting the safety of urban roads for navigation via global navigation satellite systems (GNSS) signals is considered. To ensure the safe driving of automated vehicles, a vehicle must plan its trajectory to avoid navigating on unsafe roads (e.g., icy conditions, construction zones, narrow streets, and so on). Such information can be derived from roads’ physical properties, the vehicle’s capabilities, and weather conditions. From a GNSS-based navigation perspective, the reliability of GNSS signals in different locales, which is heavily dependent on the road layout within the surrounding environment, is crucial to ensure safe automated driving. An urban road environment surrounded by tall objects can significantly degrade the accuracy and availability of GNSS signals. This article proposes an approach to predict the reliability of GNSS-based navigation to ensure safe urban navigation. Satellite navigation reliability at a given location and time on a road is determined based on the probabilistic position error bound of the vehicle-mounted GNSS receiver. A metric for GNSS reliability for ground vehicles is suggested, and a method to predict the conservative probabilistic error bound of the GNSS navigation solution is proposed. A satellite navigation reliability map is generated for various navigation applications. As a case study, the reliability map is used in a proposed optimization problem formulation for automated ground vehicle safety-constrained path planning.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Edge–Artificial Intelligence-Powered Parking Surveillance With
           Quantized Neural Networks

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      Authors: Yifan Zhuang;Ziyuan Pu;Hao Yang;Yinhai Wang;
      Pages: 107 - 121
      Abstract: The rapid development of urbanization has raised challenges for existing parking facilities to serve increasing parking demand. Being constrained by the limited urban land resources for newly constructed parking facilities, improving the efficiency of existing parking infrastructures relies more on an advanced parking management strategy. Video-based parking surveillance technology, with abundant information, easy installation, and powerful algorithms, is the most popular method to provide real-time parking information as the required data feed for a parking management system. Meanwhile, deep learning-based algorithms gradually replace traditional computer vision methods for video processing since the detection accuracy has been increased considerably by learning fine-grained features. However, the excessive computational complexity of deep learning-based algorithms occupies considerable computational resources, which certainly hurts the entire system’s efficiency. Due to the limited computing power of edge devices, most parking surveillance systems deploy video processing algorithms on a server or cloud platform, which raises concerns about data transmission latency and central computation pressure. Deploying efficient algorithms on an edge-side device is a potential solution to solve these problems. This article proposes an edge computing parking occupancy detection system with a quantized deep learning model. Model quantization is employed to boost the inference speed while maintaining accuracy. In addition, knowledge distillation is applied to improve the quantized model’s training performance. Experiments are conducted to demonstrate the model’s superiority compared to state-of-the-art algorithms and the feasibility of edge computing. The proposed method can improve the accuracy and efficiency of parking surveillance systems. It is a systematic solution for obtaining parking information with limited comp-tational resources.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • A Dynamic Pricing System for Electric Vehicle Charging Management Using
           Reinforcement Learning

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      Authors: Ajay Narayan;Aakash Krishna;Prasant Misra;Arunchandar Vasan;Venkatesh Sarangan;
      Pages: 122 - 134
      Abstract: Multiunit residential building (MURB) residents are an upcoming segment of electric vehicle (EV) owners and potential buyers (around 42% in Europe). Garage-orphaned MURB residents have to mostly rely on public chargers, which currently handle only 5% of the EV charging needs. With EVs becoming more mainstream, public chargers will not be able to match the operations scale without additional deployments. This will not only lead to a demand–supply mismatch in the short term but also impact the growth of EV adoption in the long term. For managing the demand–supply mismatch, dynamic pricing is a widely used control tool, but it is often difficult to make informed pricing decisions when 1) there is variability (both) in demand and supply, 2) users’ spatiotemporal behavior and price elasticity are unknown, and 3) charging preconditions (such as the state of charge) are not freely available. In this article, we present SurCharge, which uses reinforcement learning (RL) to overcome these challenges in dynamic pricing for EV charging. Our approach is evaluated on real-world traffic patterns for Luxembourg by augmenting the Luxembourg Simulation of Urban Mobility traffic scenario simulator with EV charging demand models. The results show that the proposed RL-based SurCharge system delivers a 10%–24% higher revenue margin than other competitive dynamic pricing baselines, without making unrealistic assumptions of prior models and data.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • A Survey of 3D Point Cloud and Deep Learning-Based Approaches for Scene
           Understanding in Autonomous Driving

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      Authors: Lele Wang;Yingping Huang;
      Pages: 135 - 154
      Abstract: Supported by the advancement of deep learning (DL) techniques and a massive procession of sensor technology, feature learning from 3D lidar data has led to rapid development in the field of autonomous driving. Progress in sensor technologies has led to the increased availability of 3D scanners, such as lidar, which are wildly used for a more accurate representation of a vehicle’s surroundings. This article aims to provide a comprehensive survey of 3D point cloud and DL-based methods for scene understanding in autonomous driving, which is mainly divided into two subtasks: object detection and semantic segmentation. For each of these, we review existing research works according to point cloud representation methods, including pure point cloud, projective 2D views, voxel grids, and multimodal data fusion. Finally, we summarize the review work and provide a discussion of future challenges of the research domain.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Point Wise or Feature Wise' A Benchmark Comparison of Publicly
           Available Lidar Odometry Algorithms in Urban Canyons

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      Authors: Feng Huang;Weisong Wen;Jiachen Zhang;Li-Ta Hsu;
      Pages: 155 - 173
      Abstract: Robust and precise localization is essential for an autonomous system with navigation requirements. Lidar odometry (LO) has been extensively studied in the past decades to realize this goal. Satisfactory accuracy can be achieved in scenarios with abundant environmental features using existing LO algorithms. Unfortunately, the performance of the LO is significantly degraded in urban canyons with numerous dynamic objects and complex environmental structures. Meanwhile, it is still not clear from the existing literature which LO algorithms perform well in such challenging environments. To fill this gap, this article evaluates an array of popular and extensively studied LO pipelines using the data sets collected in urban canyons of Hong Kong. We present the results in terms of their positioning accuracy and computational efficiency. The three major factors dominating the performance of LO in urban canyons are concluded, including the ego-vehicle dynamic, moving objects, and the degree of urbanization. According to our experiment results, point wise accomplishes better accuracy in urban canyons while feature-wise achieves cost-efficiency and satisfactory positioning accuracy.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Media Influence, Trust, and the Public Adoption of Automated Vehicles

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      Authors: Jaeyoung Lee;Farrukh Baig;Xing Li;
      Pages: 174 - 187
      Abstract: Automated vehicles (AVs) have received attention from academia and industry due to their numerous advantages, including safety, efficient mobility, and convenience. One of the biggest challenges to the mass implementation of AVs is public acceptance. This study aimed to explore the factors affecting the public’s intention to adopt AVs. Based on social cognitive theory, a theoretical model was developed with the constructs of social media (e.g., WeChat, Weibo, and TikTok) influence, traditional media (e.g., television, radio, and newspapers) influence, subjective norms, self-efficacy, perceived safety and privacy risks, trust, and behavioral intentions. The data were collected from Changsha, China, through web- and paper-based surveys. A total of 964 responses was collected to test the hypothesized model through the partial least squares path modeling approach. The results revealed that the public’s trust and intention to adopt AVs are more likely to increase through positive information on social and traditional media, strengthening subjective norms and self-efficacy, and reducing perceived safety risks. The study’s findings can be useful for establishing intervention strategies and managerial applications to enhance the public’s trust and intentions to adopt AVs.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Human-Like Decision Making of Artificial Drivers in Intelligent
           Transportation Systems: An End-to-End Driving Behavior Prediction Approach
           

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      Authors: Guofa Li;Liang Yang;Shen Li;Xiao Luo;Xingda Qu;Paul Green;
      Pages: 188 - 205
      Abstract: Drivers can be either human beings or artificial drivers in future intelligent transportation systems (ITSs). It is important to learn how people drive so that artificial drivers can be programmed to drive consistently with them. This will lead to future ITSs that are safe and efficient. In this article, we propose a new, fully end-to-end decision-making method, namely the pyramid pooling convolutional neural network with long short-time memory (PPC-LSTM), for multitask (longitudinal and lateral) decision inference in future ITSs. In this method, the features were extracted from multiscale red, green, blue images, depth images, and historical driving sequences. Our multitask loss for learning was designed by comprehensively considering the homoscedastic uncertainty of each task. Finally, experimental evaluations were conducted on a data set collected from CAR Learning to Act and the BDD100K naturalistic driving data set to examine the effectiveness of our proposed method. The results show that the prediction accuracies of driving speed and steering angle by our proposed PPC-LSTM are 89.97% and 84.67%, respectively. This is an improvement over state-of-the-art-methods by at least 2.52% and 2.67%, respectively, which demonstrates the method’s promising applications in future ITSs.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • A Stochastic Dynamic Traffic Assignment Model for Emergency Evacuations
           That Considers Background Traffic

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      Authors: Tao Zhang;Gang Ren;Gang Cheng;Yang Yang;Minjie Jin;
      Pages: 206 - 220
      Abstract: In this work, we present a stochastic dynamic traffic assignment model for emergency evacuations that considers background traffic. First, the equilibrium functions of the entry time and path choice are formulated based on the logit model. The constraints of this formulation include the state equation, propagation function, and conservation. The proposed equilibrium functions are formulated as a variational inequality problem, which is solved by the dynamic traffic network demand loading iterative method. Based on a case study in Wenling, China, we verify the proposed model on the basis of iterative evolution, path assignment, and model comparison. In addition, we perform sensitivity analysis of four relevant parameters, namely, the length of the time interval, total number of evacuation vehicles, perception error parameters of the total travel cost, and path travel cost. The results make it evident that the proposed model assists evacuation planners to effectively understand real-time dynamic changes of evacuation vehicles and the influence of background vehicles and to generate optimal emergency plans.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Dynamic Traffic Flow Prediction Based on Long-Short Term Memory Framework
           With Feature Organization

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      Authors: Jing Liu;Fangfang Zheng;Xiaobo Liu;Ge Guo;
      Pages: 221 - 236
      Abstract: Traffic flow is an important piece of information for traffic management and control. In particular, the dynamic prediction of traffic flow provides the basis for efficient control measures. The existing studies focus on improving the prediction accuracy by integrating the long short-term memory (LSTM) into various complex frameworks without paying attention to the feature engineering, which has a significant impact on the performance of machine learning methods. In this article, we propose a dynamic traffic flow prediction approach based on the LSTM framework with different feature organizations: feature division modes and feature selection. The feature division modes consider the periodicity of traffic flow by intervals (e.g., 5 min) and periods (e.g., daily). The feature selection determines different types of features as inputs to the prediction model. The impact of different feature organization strategies on the prediction accuracy is investigated using field data collected by the Caltrans Performance Measurement System. Two types of LSTM frameworks, the fully connected LSTM and the sequence-to-sequence LSTM (seq2seq-LSTM), are used to evaluate the performance of the proposed prediction approach. The results show that the seq2seq-LSTM model with optimized feature organization can significantly improve the prediction performance.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Minnesota Intelligent Transportation Systems Laboratory [ITS Research Lab]

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      Authors: Yisheng Lv;
      Pages: 237 - 242
      Abstract: The Minnesota Intelligent Transportation Systems Laboratory (MnITSLab) was established in 1994 as part of the Center for Distributed Robotics (CDR) and the Department of Computer Science and Engineering in the College of Science and Engineering (Figure 1). The MnITSLab research, through collaboration with local state agencies, outside companies, and engineering faculty, focuses on applying sensing, computing, and automation that will improve driver, pedestrian, and worker safety as well as human well-being. The Center and its members conduct a broad array of research activities, spanning intelligent transportation systems, distributed robotics, machine learning, and computer vision. Currently, the CDR supports three full-time staff engineers, one research faculty member, two staff support personnel, eight graduate students, and five undergraduates, and it has more than US$2 million in annual funding.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • IEEE App filler

    • Free pre-print version: Loading...

      Pages: 242 - 242
      Abstract: Advertisement.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • ITS Society Conferences [Conference Reports]

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      Authors: Brendan Morris;
      Pages: 243 - 243
      Abstract: Reports on ITS conference reports and events.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • Calendar

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      Authors: Martin Lauer;
      Pages: 244 - 244
      Abstract: Presents the ITSM calendar of upcoming events and meetings.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
  • IEEE Moving

    • Free pre-print version: Loading...

      Pages: 244 - 244
      Abstract: Advertisement.
      PubDate: Nov.-Dec. 2022
      Issue No: Vol. 14, No. 6 (2022)
       
 
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