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Controlled, Connected, and Self-Organizing Intelligent Transportation Systems

Call for Papers

The quest for more efficient, sustainable transportation systems finds a natural solution in connected and communicating vehicles that are able to share their knowledge of the surrounding environment. This enables safer, faster, and more efficient road management. Research and development on connected vehicles not only involves wireless communication technologies and systems, but also is a multidisciplinary field involving networked control systems, intelligent systems, simulation and modeling, protocol design, and self-organizing systems. The challenge of developing future transportation systems being able to self-organize and adapt to dynamic context changes requires foundational and applied research work embracing multiple areas and merging them in a transdisciplinary effort. In addition, the role and impact of different communication technologies (including IEEE 802.11p, 5G Cellular V2X, visible light communication, and radar-based communication) and of the protocols built on top of them are still not clearly understood.

However, before intelligent transportation solutions are introduced, they must be rigorously evaluated to enable the community to understand the impact that heterogeneous system interactions have on cooperative and automated driving. A control system for cooperative driving obtains data from multiple sources but primarily from heterogeneous wireless networks. The impact of the quality of such data on the performance of the system, in terms of stability, actual safety, and efficiency effectiveness, needs to be formally assessed. The same holds true for the design of protocols and the high-level optimization required to realize cooperative driving and on-the-road fleet management. Intelligent mobile computing algorithms will be required to gather contextual information, determine the best actions to undertake, and communicate such actions back to the vehicles. It is therefore necessary to assess how proposed vehicular communication technologies can support the demands of such mobile computing algorithms, from both a network performance and security perspective.

This special issue is focused on the multidisciplinary advancement of future transportation systems and thus welcomes original research articles and review articles that discuss related applications in the vehicular context of networked control systems, cooperative safety, and efficiency, distributed, adaptive, and self-organizing systems, as well as modeling and simulation. Multidisciplinary works that explore these topics are welcome; however, the link with wireless communications and mobile computing algorithms should be made clear.

Potential topics include but are not limited to the following:

  • Vehicular networked control systems
  • Comparison and coexistence of IEEE 802.11p and 5G Cellular V2X
  • Cooperative vehicle safety and efficiency applications
  • Heterogeneous communication protocols and technologies for vehicular networks
  • Car-to-cloud communication applications
  • Network slicing and coordination for cooperative driving
  • Mobile algorithms and protocols for self-organizing vehicle fleets
  • Modeling and simulation of networked control systems, wireless networks, and optimization mechanisms
  • Joint network/control design for cooperative driving
  • Distributed and mobile algorithms for the optimization of platooning management systems
  • Impact of cooperative driving technologies on safety and efficiency
  • Autonomous driving models and their interaction with connected vehicles
  • Comparison of autonomous and cooperative driving
  • Self-organizing traffic management
  • Security, privacy, and liability issues related to connected driving

Authors can submit their manuscripts through the Manuscript Tracking System at https://mts.hindawi.com/submit/journals/wcmc/ccsoits/.

Submission DeadlineFriday, 16 August 2019
Publication DateJanuary 2020

Papers are published upon acceptance, regardless of the Special Issue publication date.

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