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Technologies
Special Issues
Smart Transportation and Driving
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Smart Transportation and Driving

A special issue of Technologies (ISSN 2227-7080). This special issue belongs to the section "Information and Communication Technologies".

Deadline for manuscript submissions: 28 February 2026 | Viewed by 998

Special Issue Editors

Dr. Behrouz Zolfaghari

E-Mail Website
Guest Editor
Department of Computer Science and Software Engineering, Miami University, Oxford, OH 45056, USA
Interests: cybersecurity; high-performance computing; Internet of Things
Special Issues, Collections and Topics in MDPI journals
Dr. Swapnoneel Roy

E-Mail Website
Guest Editor
School of Computing, University of North Florida, Jacksonville, FL 32224, USA
Interests: computer security; energy-aware computing; algorithms
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hamid Nemati

E-Mail Website
Guest Editor
Department of Information Systems and Supply Chain Management, Bryan School of Business and Economics, The University of North Carolina at Greensboro, 1400 Spring Garden St, Greensboro, NC 27412, USA
Interests: AI and machine learning; data analytics; data science; business intelligence
Dr. Naoto Yanai

E-Mail Website
Guest Editor
Department of Multimedia Engineering, Osaka University, Osaka, Japan
Interests: information security; AI

Special Issue Information

Dear Colleagues,

Smart transportation has received focus from the research community, industries, businesses and governments in recent years. However, there is still room for extensive research on enabling technologies, applications, challenges and aspects of smart transportation. MDPI’s Technologies is proud to announce its new Special Issue titled “Smart Transportation and Driving”. Researchers are invited to submit their research papers to this Special Issue. Its areas of interest include, but are not limited to, the following:

  • Supporting and enabling technology networks;
  • Internet and IoT support for smart transportation sensors;
  • AI cloud;
  • Content delivery networks;
  • Covered areas;
  • Smart parking;
  • Smart traffic management;
  • Smart public transportation;
  • Electronic vehicles;
  • Smart information;
  • Challenges of navigation and entertainment systems;
  • Security traffic scheduling;
  • Energy management applications and systems based on smart transportation;
  • Data mining and knowledge discovery on information provided by smart transportation;
  • Military applications;
  • Aspects and forensics of smart transportation;
  • Economics of smart transportation;
  • Sociology and culture of smart transportation.

Dr. Behrouz Zolfaghari
Dr. Swapnoneel Roy
Prof. Dr. Hamid Nemati
Dr. Naoto Yanai
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. Technologies 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.

Keywords

  • smart parking
  • smart traffic management
  • smart public transportation
  • electronic vehicles
  • smart information
  • navigation and entertainment systems

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  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

20 pages, 2198 KiB  
Article
Ellipsoidal-Set Design of Robust and Secure Control Against Denial-of-Service Cyber Attacks in Electric-Vehicle Induction Motor Drives
by Ehab H. E. Bayoumi, Hisham M. Soliman and Sangkeum Lee
Technologies 2025, 13(7), 289; https://doi.org/10.3390/technologies13070289 - 7 Jul 2025
Viewed by 220
Abstract
Electric vehicles face increasing cybersecurity threats that can compromise the integrity of their electric drive systems, especially under Denial-of-Service (DoS) attacks. To precisely regulate torque and speed in electric vehicles, vector-controlled induction motor drives rely on continuous communication between controllers and sensors. This [...] Read more.
Electric vehicles face increasing cybersecurity threats that can compromise the integrity of their electric drive systems, especially under Denial-of-Service (DoS) attacks. To precisely regulate torque and speed in electric vehicles, vector-controlled induction motor drives rely on continuous communication between controllers and sensors. This flow could be broken by a DoS attack, which could result in unstable motor operation or complete drive system failure. To address this, we propose a novel ellipsoidal-set-based state feedback controller with integral action, formulated via linear matrix inequalities (LMIs). This controller improves disturbance rejection, maintains system stability under DoS-induced input disruptions, and enhances security by constraining the system response within a bounded invariant set. The proposed tracker has a faster dynamic reaction and better disturbance attenuation capabilities than the traditional Hꚙ control method. The effectiveness of the proposed controller is validated through a series of diverse testing scenarios. Full article
(This article belongs to the Special Issue Smart Transportation and Driving)
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17 pages, 1673 KiB  
Article
Model-Driven Clock Synchronization Algorithms for Random Loss of GNSS Time Signals in V2X Communications
by Wei Hu, Jiajie Zhang and Ximing Cheng
Technologies 2025, 13(7), 273; https://doi.org/10.3390/technologies13070273 - 27 Jun 2025
Viewed by 275
Abstract
Onboard Vehicle-to-Everything (V2X) communication technology is being widely implemented in domains such as intelligent driving, vehicle–road cooperation, and smart transportation. Nevertheless, time synchronization in V2X systems suffers from instability due to the random loss of Global Navigation Satellite System (GNSS) Pulse-Per-Second (PPS) signals. [...] Read more.
Onboard Vehicle-to-Everything (V2X) communication technology is being widely implemented in domains such as intelligent driving, vehicle–road cooperation, and smart transportation. Nevertheless, time synchronization in V2X systems suffers from instability due to the random loss of Global Navigation Satellite System (GNSS) Pulse-Per-Second (PPS) signals. To address this challenge, a model-driven local clock correction approach is proposed. Leveraging probability theory and mathematical statistics, models for the randomly lost GNSS PPS signals are developed. High-order polynomials are used to model local clocks. An optimized Kalman-filter-based time compensation algorithm is then devised to compensate for time errors during PPS signal loss. A software-based task-scheduling solution for precision-time synchronization is developed. An experimental testbed was then built to measure both terminal clocks and PPS signals. The proposed algorithm was integrated into the V2X terminals. Results show that the full-value PPS signals follow an exponential distribution. The onboard clock correction algorithm operates stably across three V2X terminals and accurately predicts clock variations. Furthermore, the virtual clocks achieve an average absolute error of 1.1 μs and a standard deviation of 16 μs, meeting the time synchronization requirements for V2X communication in intelligent connected vehicles. Full article
(This article belongs to the Special Issue Smart Transportation and Driving)
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