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Future Internet
Special Issues
Vehicular Networks and Mobility as Service
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Vehicular Networks and Mobility as Service

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Smart System Infrastructure and Applications".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 8423

Special Issue Editors

Dr. Grzegorz Karoń

E-Mail Website
Guest Editor
Faculty of Transport and Aviation Engineering, Silesian University of Technology, Gliwice, Poland
Interests: modelling of transportation systems and processes
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jerzy Mikulski

E-Mail Website
Guest Editor
1. President of PSTT - the Polish Association of Transport Telematics, Poland Affiliation
2. University of Technology, Katowice, Poland
Interests: transport engineering; modeling of transport systems and processes; transport systems telematics, intelligent transportation systems, mobility management

Special Issue Information

Dear Colleagues,

This Special Issue of Future Internet “Vehicular Networks and Mobility as Service” will consist of manuscripts describing state-of-the-art of intelligent transport systems and mobility as service.

The growing congestion in cities and urban agglomerations causes problems related to the nuisance of residents' lives and the functioning of economic entities in urban areas. One of the expected solutions to these problems will be systems using the Internet of things and artificial intelligence with machine learning functioning as intelligent transport systems forming vehicular networks and mobility as service. Therefore, in order to exchange theoretical and practical knowledge related to these issues, the Special Issue of Future Internet "Vehicular Networks and Mobility as Service" was launched. We invite all theoretician scientists and practitioners to submit their articles in order to share their knowledge in this area on the pages of this Special Issue of Future Internet. Topics of interest include, but are not limited to, models and methods:

  • models and methods for vehicular networks
  • mobility as a service (MaaS) - theory and practice
  • various communication environments
  • mobility planning, development, prediction - innovative new mobility service
  • variable network density
  • dynamic topology of vehicular network
  • ITS intelligent transportation systems and services, C-ITS cooperative intelligent transport systems, IoT Internet of things
  • autonomous vehicles, connected vehicles
  • demand responsive transport and demand responsive service
  • deep learning, machine learning, artificial intelligence in transportation systems and applications

Manuscripts that emphasize either method development or applications are encouraged. Both original papers and review articles are welcome; authors interested in submitting a review article are encouraged to contact the editor in advance to discuss the scope.

Prof. Dr. Grzegorz Karoń
Prof. Dr. Jerzy Miikulski
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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17 pages, 4290 KiB  
Article
Vehicular Communication Management Framework: A Flexible Hybrid Connectivity Platform for CCAM Services
by Dries Naudts, Vasilis Maglogiannis, Seilendria Hadiwardoyo, Daniel van den Akker, Simon Vanneste, Siegfried Mercelis, Peter Hellinckx, Bart Lannoo, Johann Marquez-Barja and Ingrid Moerman
Future Internet 2021, 13(3), 81; https://doi.org/10.3390/fi13030081 - 22 Mar 2021
Cited by 16 | Viewed by 3148
Abstract
In the upcoming decade and beyond, the Cooperative, Connected and Automated Mobility (CCAM) initiative will play a huge role in increasing road safety, traffic efficiency and comfort of driving in Europe. While several individual vehicular wireless communication technologies exist, there is still a [...] Read more.
In the upcoming decade and beyond, the Cooperative, Connected and Automated Mobility (CCAM) initiative will play a huge role in increasing road safety, traffic efficiency and comfort of driving in Europe. While several individual vehicular wireless communication technologies exist, there is still a lack of real flexible and modular platforms that can support the need for hybrid communication. In this paper, we propose a novel vehicular communication management framework (CAMINO), which incorporates flexible support for both short-range direct and long-range cellular technologies and offers built-in Cooperative Intelligent Transport Systems’ (C-ITS) services for experimental validation in real-life settings. Moreover, integration with vehicle and infrastructure sensors/actuators and external services is enabled using a Distributed Uniform Streaming (DUST) framework. The framework is implemented and evaluated in the Smart Highway test site for two targeted use cases, proofing the functional operation in realistic environments. The flexibility and the modular architecture of the hybrid CAMINO framework offers valuable research potential in the field of vehicular communications and CCAM services and can enable cross-technology vehicular connectivity. Full article
(This article belongs to the Special Issue Vehicular Networks and Mobility as Service)
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24 pages, 5611 KiB  
Article
Intrusion Detection for in-Vehicle Communication Networks: An Unsupervised Kohonen SOM Approach
by Vita Santa Barletta, Danilo Caivano, Antonella Nannavecchia and Michele Scalera
Future Internet 2020, 12(7), 119; https://doi.org/10.3390/fi12070119 - 14 Jul 2020
Cited by 51 | Viewed by 4364
Abstract
The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose [...] Read more.
The diffusion of embedded and portable communication devices on modern vehicles entails new security risks since in-vehicle communication protocols are still insecure and vulnerable to attacks. Increasing interest is being given to the implementation of automotive cybersecurity systems. In this work we propose an efficient and high-performing intrusion detection system based on an unsupervised Kohonen Self-Organizing Map (SOM) network, to identify attack messages sent on a Controller Area Network (CAN) bus. The SOM network found a wide range of applications in intrusion detection because of its features of high detection rate, short training time, and high versatility. We propose to extend the SOM network to intrusion detection on in-vehicle CAN buses. Many hybrid approaches were proposed to combine the SOM network with other clustering methods, such as the k-means algorithm, in order to improve the accuracy of the model. We introduced a novel distance-based procedure to integrate the SOM network with the K-means algorithm and compared it with the traditional procedure. The models were tested on a car hacking dataset concerning traffic data messages sent on a CAN bus, characterized by a large volume of traffic with a low number of features and highly imbalanced data distribution. The experimentation showed that the proposed method greatly improved detection accuracy over the traditional approach. Full article
(This article belongs to the Special Issue Vehicular Networks and Mobility as Service)
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