Collaborative Intelligence for Internet of Vehicles

Submission Deadline:  01 September 2021

IEEE Access invites manuscript submissions in the area of Collaborative Intelligence for Internet of Vehicles.   

Internet of vehicles (IoV) technology is one of the most important breakthroughs that can significantly support mobility systems toward achieving smart and sustainable societies. For example, cooperative driving features enabled by IoV can significantly decrease the risk of traffic accidents and reduce CO2 emissions, thus facilitating smarter transportation. Aerial vehicles, also known as drones, are useful for many applications, including environment and traffic monitoring, crowd mobility and gathering surveillance in pandemics, disaster recovery, and so on. Internet of underwater vehicles could enable many innovative maritime applications such as autonomous shipping, target detection, navigation, localization, and environmental pollution control. However, the development of IoV systems is dependent on overcoming the following two main challenges.

First, due to the heterogeneity of networking entities, strict application and data processing requirements, and limited resources in IoV environments, more advanced networking and computing technologies are required. Future IoV systems feature a larger number of devices and multi-access environments where different types of wireless spectrums should be efficiently utilized. At the same time, novel services, such as cooperative autonomous driving, IoV-based safety and traffic efficiency applications are emerging, and demand unprecedented high accuracy and reliability, ultra-low latency, and large bandwidth. This poses crucial challenges to the efficient use of the limited networking and computing resources.

Recently, to further explore the value of big data from IoV systems, artificial intelligence (AI)-based approaches have been attracting great interest in empowering computer systems. Some collaborative learning approaches, such as federated learning and multi-agent systems, have been used to reduce network traffic and improve the learning efficiency of some smartphone applications. For IoV systems, collaborative intelligence can be achieved via an efficient collaboration among heterogeneous entities, including vehicles, edge servers, and the cloud.

Second, in order to enable a smarter society, more research should be conducted on developing collaborative IoV frameworks and systems to expedite the applications of emerging IoV technologies. An efficient use of cross-domain big data should be discussed, and academic-industrial collaborations should be promoted to solve the existing problems toward a smarter society.

This Special Section focuses on the technical challenges for enabling collaborative IoV systems, and the applications of IoV technologies for a smarter society.

The topics of interest include, but are not limited to:

  • Collaboration among Space, Air, Ground, and Sea mobile networks
  • Collaborative intelligence based on cross-domain big data for IoV
  • Collaborative networking for IoV
  • Collaborative computing for IoV
  • Collaborative IoV for smart cities
  • Collaborative IoV for intelligent transportation systems
  • Collaborative IoV for energy-efficient sustainable cities
  • Collaborative electric vehicles
  • Collaborative unmanned aerial vehicles
  • Collaborative heterogeneous unmanned ground and aerial vehicles
  • Collaborative underwater vehicle technologies for smart ocean
  • Collaborative IoV for smarter society
  • Collaborative learning for IoV
  • Data driven collaborative intelligence for IoV
  • End-edge-cloud collaboration for IoV
  • New networking and computing architectures for Collaborative IoV
  • Security & privacy for IoV

 

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

 

Associate Editor:  Celimuge Wu, The University of Electro-Communications, Japan

Guest Editors:

    1. Soufiene Djahel, Manchester Metropolitan University, UK
    2. Damla Turgut, University of Central Florida, USA
    3. Sidi-Mohammed Senouci, University of Bourgogne, France
    4. Lei Zhong, Toyota Motor Corporation, Japan

 

Relevant IEEE Access Special Sections:

    1. Artificial Intelligence (AI)-Empowered Intelligent Transportation SystemsBeyond 5G Communications
    2. Edge Intelligence for Internet of ThingsMillimeter-Wave Communications: New Research Trends and Challenges
    3. Information Centric Wireless Networking with Edge Computing for 5G and IoT

 

IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

 For inquiries regarding this Special Section, please contact: celimuge@uec.ac.jp.

Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems

Submission Deadline: 01 June 2020

IEEE Access invites manuscript submissions in the area of Artificial Intelligence (AI)-Empowered Intelligent Transportation Systems.

The topic of Artificial Intelligence (AI)- Empowered Intelligent Transportation Systems (ITS) has drawn more attention recently, with the rapid development of ubiquitous networks and smart vehicles. Researchers around the world have been working on new automotive applications to create a comfortable and safer driving environment. Current challenges include: how to run computing-intensive applications on vehicles; how to enable real-time feedback between vehicles and the traffic management server based on the current Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication modes; and how to provide efficient computing capabilities for resource-consumption applications, and reasonable resource allocation for vehicles and infrastructures. AI-Empowered solutions, such as deep learning and reinforcement learning, should help relieve computational loads for vehicles. Recently, AI has achieved remarkable achievements in many fields, such as image processing, pattern recognition, and natural language processing, etc. It is also involved in computing-intensive applications, such as autopilot and real-time navigation through V2V or V2I. However, AI-Empowered ITS is still in its infancy. How can AI be integrated with ITS and make it work well in dynamic vehicular network scenarios? Furthermore, there are still questions on how to design more efficient AI solutions for resource management in ITS.

The objective of this Special Section in IEEE Access is to introduce the current developments and advancements of the technical elements of the AI-Empowered ITS, from both theoretical and practical perspectives.

The topics of interest include, but are not limited to:

  • Architecture and framework establishment of AI-Empowered ITS
  • Design of efficient AI solutions in ITS
  • AI-Empowered approach of route planning in ITS
  • AI-Empowered approach of traffic scheduling in ITS
  • AI-Empowered resource management in ITS
  • AI-Empowered security and privacy protection in ITS
  • AI-Empowered real-time applications in ITS
  • Testing and evaluation tools for AI-Empowered ITS
  • Novel applications based on AI-Empowered ITS
  • Future AI-Empowered ITS: challenges and open issues

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Edith Ngai, Uppsala University, Sweden

Guest Editors:

    1. Chao Chen, Chongqing University, China
    2. Amr M. Tolba, King Saud University, Saudi Arabia
    3. Mohammad S. Obaidat, Fordham University, USA
    4. Fanzhao Wang, Huawei Technologies Co Ltd, China

 

Relevant IEEE Access Special Sections:

  1. Big Data Technology and Applications in Intelligent Transportation
  2. Trends and Advances for Ambient Intelligence with Internet of Things (IoT) systems
  3. Communication, Control, and Computation Issues in Heterogeneous Vehicular Networks


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact:  edith.ngai@it.uu.se.

Performance Evaluation of Multi-UAV System in Post-Disaster Application….

Can eyes in the air counter chaos on the ground? Researchers in Japan analyzed performance of unmanned aerial vehicles (UAVs) used in the response to the 2011 Tohoku earthquake-tsunami disaster, and report on their findings in this IEEE Access article of the week.

The paper proposes an evaluation of unmanned aerial vehicles (UAVs) performance in the mapping of disaster-struck areas. Sendai city in Japan, which was struck by the Tohoku earthquake/tsunami disaster in 2011, was mapped using multi-heterogeneous UAV.

Normal mapping and searching missions are challenging as human resources are limited, and rescue teams are always needed to participate in disaster response mission. Mapping data and UAV performance evaluation will help rescuers to access and commence rescue operations in disaster-affected areas more effectively.

Herein, flight-plan designs are based on the information recorded after the disaster and on the mapping capabilities of the UAVs. The numerical and statistical results of the mapping missions were validated by executing the missions on real-time flight experiments in a simulator and analyzing the flight logs of the UAVs.

After considering many factors and elements that affect the outcomes of the mapping mission, the authors provide a significant amount of useful data relevant to real UAV modules in the market. All flight plans were verified both manually and in a hardware-in-the-loop simulator developed by the authors. Most of the existing simulators support only a single UAV feature and have limited functionalities such as the ability to run different models on multiple UAVs.

The simulator demonstrated the mapping and fine-tuned flight plans on an imported map of the disaster. As revealed in the experiments, the presented results and performance evaluations can effectively distribute different UAV models in post-disaster mapping missions.

View this article n IEEE Xplore

Communication and Fog/Edge Computing Towards Intelligent Connected Vehicles (ICVs)

Submission Deadline: 30 November 2019

IEEE Access invites manuscript submissions in the area of Communication and Fog/Edge Computing Towards Intelligent Connected Vehicles (ICVs).

With rapid economic development, the number of vehicles on the road has grown dramatically, which introduces an array of traffic-related issues, such as traffic congestion and driving safety. Intelligent connected vehicles (ICVs) can provide a safer and greener transportation system, which has been envisioned as an effective measure to resolve traffic problems. ICVs are expected to run many emerging smart applications (e.g., autonomous driving, safety early warning, natural language processing, etc.) to assist both the drivers and passengers in vehicular environments. These kinds of applications typically require significant computing power to perform computation-intensive and latency-sensitive tasks generated by the vehicle sensors for low-latency response. However, the limited computation capacity of the on-board computer makes it difficult to satisfy the computation requirements of quality-of-experience (QoE)-demanding applications. To tackle this challenge, fog/edge computing are proposed as innovative computing paradigms to extend computing capacity to the network edge in order to meet the requirements. Fog/edge computing is expected to not only maximize the computation capability and alleviate the greenhouse effect, but also achieve sustainable operation by pushing rich computing and storage resources to the edge of the network.

The limited computation capacity of the on-board computer brings about an unprecedented challenge for the future development of ICVs. Fog/edge computing provides cloud computing capacity in close proximity to vehicles. Vehicles can migrate the computing to the edge of the network via vehicle to everything (V2X) communication. Processing can be completed at road-side unit (RSU) at the side of the network. The advancement of communication technologies and edge computing, such as Fifth-generation (5G), Software Defined Networking (SDN), Network Function Virtualization (NFV), mobile edge/fog computing and so on, makes it possible to enhance computational capabilities, ensure near-real-time responses and realize communication requirements with ultra-low latency and ultra-high reliability. The Special Section in IEEE Access aims to provide the latest research findings and solutions, in terms of communication and edge computing for ICVs.

The topics of interest include, but are not limited to:

  • New architecture and framework establishment based on fog/edge computing for ICVs
  • Advanced vehicular networks technologies, such as 5G vehicular networks, LTE-V and so on
  • Ultra-reliable and low-latency communications for ICVs
  • Resource allocation and management based on fog/edge computing for ICVs
  • Machine learning, deep learning for intelligent management and control
  • Joint analysis of communication and computing to improve performance in vehicular networks
  • Cross-layer optimization for fog/edge computing
  • Mobility modeling and management for ICVs
  • SDN and NFV technologies for vehicular networks
  • Security and privacy challenges

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor:  Lei Shu, Nanjing Agricultural University, China / University of Lincoln, UK

Guest Editors:

  1. Junhui Zhao, East China Jiaotong University, China / Beijing Jiaotong University, China
  2. Yi Gong, Southern University of Science and Technology, China
  3. Changqing Luo, Virginia Commonwealth University, USA
  4. Tim Gordon, University of Lincoln, UK

 

Relevant IEEE Access Special Sections:

  1. Mobile Edge Computing and Mobile Cloud Computing: Addressing Heterogeneity and Energy Issues of Compute and Network Resources
  2. D2D communications: Security Issues and Resource Allocation
  3. Smart caching, communications, computing and cybersecurity for Information-Centric Internet of Things


IEEE Access Editor-in-Chief:  Prof. Derek Abbott, University of Adelaide

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: lei-shu@outlook.com.

D2D Communications: Security Issues and Resource Allocation

Submission Deadline: 28 February 2019

IEEE Access invites manuscript submissions in the area of D2D Communications: Security Issues and Resource Allocation.

Device-to-device (D2D) communications will enable direct communications between devices in cellular networks, thus potentially improving the spectrum utilization, enhancing the overall throughput, and increasing energy efficiency. D2D communication has the potential to enable new peer-to-peer and location-based applications and services, as well as to help offload traffic from the congested traditional cellular networks.

The primary issue with respect to D2D communications, is its sharing of spectrum resources with traditional cellular and other communication networks. D2D systems should be able to use the same spectral resources occupied by traditional communication devices in an opportunistic manner, in order to facilitate the needed point-to-point connectivity. To solve the spectrum scarcity issues involving D2D and traditional communication systems, the research community has resorted to the Cognitive Radio (CR) and Dynamic Spectrum Access (DSA) paradigms that devise new approaches for enabling spectrally efficient D2D communication networks. These new approaches have resulted in innovative network architectures and applications that have the potential to redefine the current state-of-the-art of wireless connectivity and to shape the next generation cellular communications (e.g., 5G and Vehicle-to-Vehicle (V2V) / Vehicle-to-Infrastructure (V2I) communications). The proliferation of D2D communications implies also special security measures, as the involved devices are susceptible to eavesdropping, interference, jamming, and other types of attacks.

The topics of interest include, but are not limited to:

  • D2D communications for 5G networks
  • Cognitive Radio and Dynamic Spectrum Sharing for D2D deployment in TVWS
  • Spectrum regulation and management aspects for D2D networks
  • Energy and spectral efficiency
  • Software Defined Networks (SDN) and Software Defined Radio (SDR) for D2D communications
  • D2D standardization
  • Interference and power control
  • Radio resource allocation and scheduling
  • Biologically-inspired techniques for D2D spectrum management
  • Deep and reinforcement learning for D2D
  • D2D non-orthogonal multiple access (NOMA) frameworks
  • D2D for vehicular communications
  • Vehicle-to-anything (V2X) communications
  • IoT architectures for D2D
  • Social networking for D2D
  • D2D test-beds, prototypes, and implementations
  • Security and privacy for D2D communications

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Li Wang, Beijing University of Post and Telecommunications (BUPT), China

Guest Editors:

  1. Antonino Orsino, Ericsson Research, Finland
  2. Adrian Kliks, Poznan University of Technology, Poland
  3. Alexander M. Wyglinski, Worcester Polytechnic Institute, USA
  4. Vlad Popescu, Transilvania University of Brasov, Romania
  5. Mauro Fadda, University of Cagliari, Italy

 

Relevant IEEE Access Special Sections:

  1. Emerging Technologies for Device to Device Communications
  2. Emerging Technologies for Vehicle to Everything (V2X)
  3. Radio Frequency Identification and Security Techniques


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: liwang@bupt.edu.cn

Emerging Technologies for Vehicle to Everything (V2X)

Submission Deadline: 15 December 2018

IEEE Access invites manuscript submissions in the area of Emerging Technologies for Vehicle to Everything (V2X).

Recently, the vehicle to everything (V2X) paradigm is attracting more attention from both academia and industry. In V2X, while connecting all the devices (motor-vehicle, non-motor-vehicle, bicycle, pedestrian, etc.) on the road, we can collect and share the real-time information (speed, accelerate, route, etc.) among V2X devices for automatic piloting and intelligent traffic control. On the other hand, to accelerate the automatic piloting technologies, big data and deep learning-based image recognition and environment reconstruction is an inevitable technology. In addition to intelligent traffic and automatic driving technologies, 5G will also play a significant role in V2X by providing fast speed transmissions for in-car entertainment (4K/8K high-definition video, etc.), as well as for vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), and vehicle-to-network (V2N) communications. Meanwhile, with V2X’s massive number of connected devices, information centric networking (ICN)/content caching technologies can be exploited for optimal vehicle network routing and wireless information delivery, which will leverage the network and wireless transmission performance. Together with the adoption of optimal routing, ICN-based network architecture will further alleviate the backhaul load. In V2X, to meet the different quality of service (QoS) requirements of a massive number of connected devices, the software defined network (SDN) based network slicing technology can be invoked to create different dedicated network slices.  Based on all those discussions, it is known that to accomplish the goal of V2X, comprehensive solutions are needed to reshape existing networks. Moreover, because of the massive number of connected devices on the road, the future of driving and traffic will be reshaped, and policies on this forthcoming V2X era from the government should be set forth as well.

However, until now, only the V2X’s initial ambitions regarding intelligent traffic control, automatic driving and fast speed transmission experiences are sketched. So, comprehensive technologies and policies able to accomplish all the goals of V2X from academia, industry and government are still needed. This Special Section in IEEE Access aims to bring together researchers to report their recent research advances in V2X and exchange new ideas with innovative technologies and solutions. This Special Section will include a collection of outstanding research-oriented review and survey articles, high level position papers and new research results, covering a wide range of topics within V2X systems and networks.

The topics of interest include, but are not limited to:

  • DSRC technologies for V2X
  • C-V2X technologies for V2X
  • Signal processing technologies for V2X
  • Channel estimation and measurement technologies for V2X
  • Front-hauling and back-hauling technologies for V2X
  • Resource allocation and optimization for V2X
  • Energy efficiency analysis for V2X
  • Heterogeneous network technologies for V2X
  • Cyber security and application scenarios for V2X
  • Software defined network architectures for V2X
  • Network slicing technologies for V2X
  • ICN and SDN technologies-based network architectures for V2X
  • Unmanned aerial vehicle (UAV) assisted communications for V2X
  • Centralized and decentralized network architectures for V2X
  • Integrated vehicle edge, fog computing technologies for V2X
  • Data mining technologies for V2X
  • Vehicle and pedestrian behavior prediction technologies for V2X
  • Machine learning iteration algorithms for V2X
  • Deep learning-based image detection for V2X
  • Deep learning based 2-D, 3-D environment reconstructions for V2X
  • Big data and machine learning based technologies for V2X
  • Legislation, standardization and enforcement for V2X

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Yan Zhang, University of Oslo, Norway


Guest Editors:

  1. Di Zhang, Zhengzhou University, China
  2. Zhi Liu, Waseda University, Japan
  3. Carlos Tavares Calafate, Technical University of Valencia (UPV), Spain
  4. Yi Liu, Guangdong University of Technology (GDUT), China
  5. Anwer Al-Dulaimi, EXFO Inc., Canada

 

Relevant IEEE Access Special Sections:

  1. High Mobility 5G LTE-V: Challenges and Solutions
  2. Security and Privacy for Vehicular Networks
  3. Recent Advances on Modelling, Optimization and Signal Processing Methods in Vehicle Dynamics and Crash-worthiness


IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: di_zhang@zzu.edu.cn (GE), yanzhang@ifi.uio.no (AE).

 

Advanced Energy Storage Technologies and Their Applications

Submission Deadline: 31 May 2019

IEEE Access invites manuscript submissions in the area of Advanced energy storage technologies and their applications.

The depletion of fossil fuels, the increase of energy demands, and the concerns over climate change are the major driving forces for the development of renewable energy such as solar energy and wind power. However, the intermittency of renewable energy has hindered the deployment of large scale intermittent renewable energy, which, therefore, has necessitated the development of advanced large-scale energy storage technologies. The use of large scale energy storage can effectively improve the efficiency of energy resource utilization, and increase the use of variable renewable resources, the energy access and the end-use sector electrification (e.g. electrification of transport sector).

The main objective of this Special Section in IEEE Access is to provide a platform for presenting the latest research results on the technology development of large scale energy storage. We welcome research articles about theoretical, methodological and empirical studies, as well as review articles that provide a critical overview on the state-of-the-art of these technologies. This Special Section is open to all types of energy, such as thermal energy, mechanical energy, electrical energy and chemical energy, using different types of systems, such as phase change materials, batteries, supercapacitors, fuel cells, compressed air, etc., which are applicable to various types of applications, such as heat and power generation, electrical/hybrid transportation etc. Original, high quality technical articles as well as original review and survey articles are encouraged.

The topics of interest include, but are not limited to:

  • Novel energy storage materials and topologies
  • Application in electrical/hybrid driven system and electrical/hybrid vehicles
  • Next generation energy storage and conversion devices, systems or techniques
  • Large scale energy storage system modeling, simulation and optimization, including testing and modeling ageing processes
  • Advanced energy storage management systems, including advanced control algorithms and fault diagnosis/online condition monitoring for energy storage systems
  • Artificial Intelligence in Energy and Renewable Energy Systems
  • Wireless power transfer, charging systems and infrastructures
  • Big Data Analytics in Energy
  • Business model for the application and deployment of energy storage
  • Lifecycle analysis, repurposing, and recycling

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Rui Xiong, Beijing Institute of Technology, China

Guest Editors:

  1. Suleiman Sharkh, University of Southampton, UK
  2. Hailong Li, Mälardalen University, Sweden
  3. Kevin Bai, University of Michigan, USA
  4. Weixiang Shen, Swinburne University of Technology, Australia
  5. Peng Bai, Washington University in St. Louis, USA
  6. Joe Zhou, Kettering University, USA

 

Relevant IEEE Access Special Sections:

  1. Energy Management in Buildings
  2. Battery Energy Storage and Management Systems
  3. Advanced Modeling and Control of Complex Mechatronic Systems with Nonlinearity and Uncertainty

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: rxiong@bit.edu.cn

Advanced Big Data Analysis for Vehicular Social Networks

Submission Deadline: 31 August 2018

IEEE Access invites manuscript submissions in the area of Advanced Big Data Analysis for Vehicular Social Networks.

Vehicular Social Network (VSN) is a mobile communication network formed by the combination of relevant concepts and features from two different fields, i.e., Social Networks (SN) and Vehicular Ad-hoc Networks (VANET). Based on Social Network Analysis (SNA), these interdependencies of network entities can be exploited to enhance Quality of Service (QoS) for perspective applications. This notion of SNA and its applications have recently attracted much attention from the research community. With the pervasive applications of intelligent equipment such as GPS devices, traffic cameras, smart cards, smartphones and road deceleration devices, multisource big data in VSN are more easily collected than before. Analyzing the regularities hidden in VSN big data has been a hot research field associated with transportation management, urban planning, epidemic control, mobile platform application, and so on. Significant improvements could be achieved by exploiting social behaviors of commuters based on VSN big data analysis.

VSN is an emerging field which crosses multiple research disciplines and industry domains, including transportation, information technology, communications, and social sciences. The goal of this Special Section in IEEE Access is to collect articles focusing on big data analysis for a diverse range of VSN applications and services. We also welcome survey articles on this topic.

The topics of interest include, but are not limited to:

  • Architecture, strategies, and algorithms for VSNs
  • Network science for VSN big data
  • Big data-driven recommendation in VSNs
  • IoT and VSNs
  • Cross-layer design and optimization in VSNs
  • Human behavior based on big data in VSNs
  • Human mobility prediction and visualization leveraging big data
  • VSN big data analysis for urban computing and decision-making
  • Wireless communication and vehicular social networking in VSNs
  • Socially-aware intelligent transportation system
  • Security and privacy issues in VSNs
  • Mobility modeling and big data mining in VSNs
  • Cooperative communication in VSNs
  • Entertainment on roads/video and gaming in VSNs
  • Data delivery reliability and network efficiency in VSNs
  • Data privacy and security for VSNs
  • Transportation optimization using VSN big data
  • Traffic control and management based on VSN big data
  • Transportation visualization based on VSN big data
  • Community activity prediction based on VSN big data analysis

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Xiangjie Kong, Dalian University of Technology, China

Guest Editors:

  1. Michael Sheng, Macquarie University, Australia
  2. Alexey Vinel, Halmstad University, Sweden
  3. Saeid Abolfazli, YTL Communications, and Xchanging, Malaysia
  4. Xia Hu, Texas A & M University, USA
  5. Feng Xia, Dalian University of Technology, China

 

Relevant IEEE Access Special Sections:

  1. Advanced Data Analytics for Large-scale Complex Data Environments
  2. The New Era of Smart Cities: Sensors, Communication Technologies and Applications
  3. Security and Privacy for Vehicular Networks

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: xjkong@ieee.org

GNSS, Localization, and Navigation Technologies

Submission Deadline: 28 February 2018

IEEE Access invites manuscript submissions in the area of GNSS, Localization, and Navigation Technologies.

Position and time have become two of the most vital information for the convenience, security, and safety of our daily lives and have been the core enabler of innovative advancements in many science and engineering fields. Since the Global Positioning System (GPS) became available to the public, GPS has been applied not only to terrestrial, maritime and air navigation systems but also to diverse areas in our everyday life such as geodesy, agriculture, mining, construction, remote sensing, cellular communications, finance, power transmission, and in the recent years, location-based services (LBS) in smartphones and Internet of Things (IoT) applications. However, the legacy GPS has been only successful in the outdoor and open-sky applications, and the new demand for positioning and navigation in indoor and urban street environments has been growing strong and rapidly.

A number of countries are carrying out their own plan to build advanced satellite-based navigation systems, which together with GPS and its future evolutions, they are generally referred to as Global Navigation Satellite Systems (GNSS). GNSS will provide a number of new wideband signals with encoded and encrypted data at multiple frequencies for the enhancement of accuracy, robustness, and signal availability in the GPS-denied environments such as dense urban streets and indoor and in the presence of cyber-attacks.

On the other hand, there have been research activities around the world to develop indoor positioning and navigation technologies in diverse directions. One conventional approach is to use radio signals from wireless infrastructure such as WiFi, UWB, and LTE (i.e., cellular signals), and the other is to utilize non-radio signal measurements such as camera-vision, in-building magnetic anomaly, and inertial measurements.

This Special Section in IEEE Access aims to share new ideas, latest findings, and results with researchers, academics, and experts working on the research and development of positioning and navigation technologies. The related topics of interest to GNSS, localization, and navigation technologies include, but are not limited to:

  • Algorithms, signal processing techniques, and performance analysis
  • New design of signals, devices, and systems
  • Sensor fusion and hybridization techniques
  • Cooperative and robust techniques
  • Privacy, authentication, and security improving techniques
  • Experiments and performance evaluation
  • Applications to autonomous vehicles, intelligent transportation systems
  • Innovative techniques and approaches for IoT, cloud processing, and big data

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Seung-Hyun Kong, KAIST, South Korea

Guest Editors:

  1. José A. López-Salcedo, Universitat Autònoma de Barcelona, Spain
  2. Yuanxin Wu, Shanghai Jiao Tong University, China
  3. Euiho Kim, Hong-Ik University, South Korea

 

Relevant IEEE Access Special Sections:

  1. Intelligent Systems for the Internet of Things
  2. Convergence of Sensor Networks, Cloud Computing, and Big Data in Industrial Internet of Things
  3. The New Era of Smart Cities: Sensors, Communication Technologies and Applications

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: skong@kaist.ac.kr

High Mobility 5G LTE-V: Challenges and Solutions

Submission Deadline: 1 December 2017

IEEE Access invites manuscript submissions in the area of High Mobility 5G LTE-V: Challenges and Solutions.

The Internet of Vehicles, previously referred to as Vehicular Ad Hoc Networks (VANETs), will be collections of mobile ad hoc networks for vehicular communications to improve driving safety and traffic efficiency. Major categories include vehicle-to-vehicle (V2V) communications and vehicle-to-infrastructure (V2I) communications, and collectively these (and future categories) can be termed V2X communications. These two categories entail a variety of communication channels, network topologies, vehicle densities and communication scenarios, and in response to this, IEEE has released the IEEE 802.11p and IEEE 1609 protocols for VANETs. With the global commercial application of Long Term Evolution (LTE) mobile communication systems, LTE based vehicular (LTE-V) networks have been shown to offer advantages in V2I communications, coverage, high mobility and complicated communication scenarios. Therefore, in the 5th generation’s (5G) mobile communication networks, the 3GPP is discussing V2V communications as a device-to-device (D2D) communication application. As is well known, in high mobility scenarios, the wireless channel is rapidly time varying, Doppler shifts and spreads can be much larger than in cellular, network topology can change quickly, and switching among base stations and vehicles is more frequent. All this presents formidable challenges to realizing reliable communications with low latency in 5G LTE-V systems. This Special Section in IEEE Access will focus on the challenges and solutions for the 5G LTE-V, with topics including but not limited to:

  • High mobility V2X channel measurement and modeling
  • High mobility V2X channel estimation
  • High mobility V2X channel equalization
  • High mobility channel frequency offset compensation
  • Joint time-frequency correction for high mobility V2X channel
  • LTE-V physical (PHY) and medium access control (MAC) layer enhancements to cope with high mobility V2X channels
  • Interference management for 5G LTE-V and VANETs
  • Resource allocation based on channel state information
  • Cross layer design based on dynamic congestion control
  • Mobility management for V2X applications
  • Heterogeneous networks of 5G LTE-V and other VANETs
  • Nonorthogonal multiple access for LTE-V

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

 

Associate Editor: Wen Chen, Shanghai Jiao Tong University, China

Guest Editors:

  1. Ruisi He, Beijing Jiao Tong University, China
  2. David W. Matolak, University of South Carolina, USA
  3. Chintha Tellambura, University of Alberta, Canada
  4. Zhengguo Sheng, University of Sussex, UK

 

Relevant IEEE Access Special Sections:

  1. Communication, Control and Computation Issues in Heterogeneous Vehicular Networks
  2. Resource Management in Vehicular Ad-Hoc Networks: Energy Management, Communication Protocol and Future Applications
  3. Recent Advances on Modelling, Optimization and Signal Processing Methods in Vehicle Dynamics and Crash-worthiness

 

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to:
http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: wenchen@sjtu.edu.cn