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Future Transportation
Special Issues
Future of Vehicles (FoV2025)
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Future of Vehicles (FoV2025)

A special issue of Future Transportation (ISSN 2673-7590).

Deadline for manuscript submissions: 31 May 2026 | Viewed by 6245

Special Issue Editors

Prof. Dr. István Lakatos

E-Mail Website
Guest Editor
Department of Road and Rail Vehicles, Széchenyi István University, Győr, Hungary
Interests: vehicle engine diagnostics; chassis dynamometer performance testing; combustion engine cold-start and idling behavior; alternative fuels for diesel engines; electric and hybrid vehicle diagnostics; vehicle online diagnostics and predictive maintenance; vehicle dynamics modeling and simulations; Vehicle safety and acoustic diagnostics; seat safety in non-conventional seating positions; sensor calibration and ADAS sensing systems
Special Issues, Collections and Topics in MDPI journals
Dr. Zoltán Weltsch

E-Mail Website
Guest Editor
Zalaegerszeg Innovation Park, Széchenyi István University, Győr, Hungary
Interests: mechanical engineering; vehicle engineering; vehicle dynamics; autonomous vehicles; advanced driver-assistance system (ADAS); vehicle testing and validation; transportation safety; electric and hybrid vehicles; sustainable transportation systems; powertrain development; vehicle-to-everything (V2X) communication; simulation and modelling in vehicle engineering; hydrogen–gasoline dual-fuel internal combustion engines; hydrogen combustion modeling and optimization; dual-fuel engine efficiency and emissions; combustion stability and knock analysis in hydrogen blends
Dr. Leticia Pekk

E-Mail Website
Guest Editor
Zalaegerszeg Innovation Park, Széchenyi István University, Győr, Hungary
Interests: technology forecasting; technology management; technological competence management; corporate R&D strategies; innovation management; sustainable transportation systems; automotive testing and validation; advanced driver-assistance system (ADAS); vehicle communication networks (CAN, V2X); electric vehicle technologies; battery diagnostics and energy management; smart city mobility solutions; agrivoltaics and renewable integration in transportation; industrial sustainability models

Special Issue Information

Dear Colleagues,

The automotive and mobility sectors are undergoing a rapid and transformative evolution, driven by the urgent need for sustainability, technological innovation, and economic efficiency. Electrification, autonomous driving, smart infrastructure, and digital connectivity are no longer distant concepts but key elements shaping the future of transportation systems. These developments bring remarkable opportunities—improved energy efficiency, safety, and user experience—yet they also present significant challenges, such as infrastructure readiness, integration of renewable energy, and regulatory adaptation.

The Future of Vehicles Conference 2025 (FoV2025), held in Zalaegerszeg, Hungary, served as a dynamic platform to address these challenges. The event gathered over 120 participants, including 78 speakers from 11 countries and leading institutions such as Imperial College London (UK), Nanyang Technological University (Singapore), and the University of Modena and Reggio Emilia (Italy). It brought together academia, industry, and policymakers to exchange ideas, present cutting-edge research, and build strategic collaborations for the mobility of tomorrow.

This Special Issue will feature selected, high-quality contributions from FoV2025 and open submissions from the broader research community, with the aim of advancing sustainable, intelligent, and economically viable vehicle and mobility solutions. The topics align closely with the journal’s scope, encouraging both theoretical and applied research that bridges engineering innovation with environmental and societal impact.

By collecting these works in one Special Issue, we seek to create a scientific reference point for researchers and practitioners, strengthening the link between academic findings and real-world applications. The Special Issue will also promote interdisciplinary approaches, recognizing that future transportation challenges can only be solved through the integration of engineering, economics, and policy perspectives.

Topics of interest include, but are not limited to, the following:

  • Electric, hybrid, and hydrogen-powered vehicle development;
  • Autonomous driving technologies and advanced driver-assistance systems (ADASs);
  • Smart and connected mobility infrastructure (V2X communication);
  • Simulation, testing, and validation of innovative vehicle concepts;
  • Sustainable manufacturing and lightweight material applications;
  • Energy efficiency, emissions reduction, and life-cycle assessment;
  • Integration of renewable energy into transportation systems;
  • Traffic flow management and intelligent transport planning;
  • Technology forecasting, management, and strategic decision-making in mobility;
  • Economic and policy frameworks for vehicle innovation.

We welcome your submissions and look forward to building on the momentum generated at FoV2025 to shape the next generation of transportation systems.

Prof. Dr. István Lakatos
Dr. Zoltán Weltsch
Dr. Leticia Pekk
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 250 words) can be sent to the Editorial Office for assessment.

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 Transportation is an international peer-reviewed open access semimonthly 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 1200 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

  • future mobility
  • sustainable transportation
  • smart vehicles
  • electric and hybrid vehicles
  • autonomous driving
  • vehicle-to-everything (V2X) communication
  • intelligent transport systems (ITS)
  • renewable energy integration
  • technology forecasting and management
  • transportation policy and economics

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • 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 (7 papers)

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Research

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20 pages, 274 KB  
Article
Autonomous Vehicles and the Infrastructure of the World Trade Law
by Balázs Horváthy
Future Transp. 2026, 6(2), 60; https://doi.org/10.3390/futuretransp6020060 - 10 Mar 2026
Viewed by 445
Abstract
The development of new technologies, particularly autonomous vehicles, poses significant challenges and opportunities for international trade law. Legal frameworks must adapt to technological shifts while facilitating cross-border commerce. This paper examines the relationship between emerging technologies and the existing infrastructure of world trade [...] Read more.
The development of new technologies, particularly autonomous vehicles, poses significant challenges and opportunities for international trade law. Legal frameworks must adapt to technological shifts while facilitating cross-border commerce. This paper examines the relationship between emerging technologies and the existing infrastructure of world trade law, focusing specifically on how current WTO agreements address technological developments. The analysis employs a legal doctrinal approach, examining the applicability of key WTO agreements to new technologies through the lens of technology-neutral interpretation. Departing from ‘dialectical relationship theory’ (Cottier), the research investigates the influence of new technologies on the legal infrastructure of international trade and how the latter can respond to their use and development. Current WTO frameworks demonstrate technology-neutral applicability to emerging technologies, including autonomous vehicles and related services. However, the paper identifies significant practical limitations arising from the ‘mosaic’ nature of member state commitments and varying levels of liberalization across relevant technology-related sectors. The findings suggest that, while the existing WTO infrastructure theoretically has the capacity to accommodate technological advances, realizing the full benefits of global trade in new technologies may require either the harmonized extension of WTO member-state commitments or the adoption of specific legislation to address current regulatory fragmentation. Full article
(This article belongs to the Special Issue Future of Vehicles (FoV2025))
12 pages, 1979 KB  
Article
Determination of the Centre of Gravity of Electric Vehicles Using a Static Axle-Load Method
by Balázs Baráth and Dávid Józsa
Future Transp. 2026, 6(1), 22; https://doi.org/10.3390/futuretransp6010022 - 18 Jan 2026
Viewed by 618
Abstract
Accurate determination of a vehicle’s centre of gravity (CoG) is fundamental to driving dynamics, safety, and engineering design. However, existing static CoG estimation methods often neglect tyre deflection and detailed wheel geometry, which can introduce significant errors, particularly in electric vehicles, where the [...] Read more.
Accurate determination of a vehicle’s centre of gravity (CoG) is fundamental to driving dynamics, safety, and engineering design. However, existing static CoG estimation methods often neglect tyre deflection and detailed wheel geometry, which can introduce significant errors, particularly in electric vehicles, where the low and concentrated mass of the battery pack increases the sensitivity of vertical CoG calculations. This study presents a refined static axle-load-based method for electric vehicles, in which the influence of tyre deformation and lifting height on the accuracy of the vertical centre of gravity coordinate is explicitly considered and quantitatively justified. To minimise human error and accelerate the evaluation process, a custom-developed Python (Python 3.13.2.) software tool automates all calculations, provides an intuitive graphical interface, and generates visual representations of the resulting CoG position. The methodology was validated on a Volkswagen e-Golf, demonstrating that the proposed approach provides reliable and repeatable results. Due to its accuracy, reduced measurement complexity, and minimal equipment requirements, the method is suitable for design, educational, and diagnostic applications. Moreover, it enables faster and more precise preparation of vehicle dynamics tests, such as rollover assessments, by ensuring that sensor placement does not interfere with vehicle behaviour. Full article
(This article belongs to the Special Issue Future of Vehicles (FoV2025))
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12 pages, 1438 KB  
Article
Analyzing On-Board Vehicle Data to Support Sustainable Transport
by Márton Jagicza, Gergő Sütheö and Gábor Saly
Future Transp. 2026, 6(1), 17; https://doi.org/10.3390/futuretransp6010017 - 14 Jan 2026
Viewed by 411
Abstract
Energy-efficient driving is essential for reducing the environmental impacts of road transport, especially for electric passenger vehicles. This research aims to build a data-driven behavioral analysis and energy-consumption evaluation model. The model relies on sensor data from the vehicle’s on-board communication network, primarily [...] Read more.
Energy-efficient driving is essential for reducing the environmental impacts of road transport, especially for electric passenger vehicles. This research aims to build a data-driven behavioral analysis and energy-consumption evaluation model. The model relies on sensor data from the vehicle’s on-board communication network, primarily the CAN (Controller Area Network) bus. We analyze patterns of key powertrain and battery parameters—such as current, voltage, state of charge (SoC), and power—in relation to driver inputs, such as the accelerator pedal position. In the first stage, we review the literature with a focus on machine learning and clustering methods used in behavioral and energy analysis. We also examine the role of on-board telemetry systems. Next, we develop a controlled measurement architecture. It defines reference consumption maps from dynamometer data across operating points and environmental variables, including SoC, temperature, and load. The longer-term goal is a multidimensional behavioral map and profiling framework that can predict energy efficiency from real-time driver inputs. This work lays the foundation for a future system with adaptive, feedback-based driver support. Such a system can promote intelligent, sustainable, and behavior-oriented mobility solutions. Full article
(This article belongs to the Special Issue Future of Vehicles (FoV2025))
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17 pages, 989 KB  
Article
Sustainable Hatred: Tesla as a Political Product and the Environmental Impact of Hate Crimes Committed on E-Vehicles
by Judit Glavanits, Gergely G. Karácsony and Gábor Kecskés
Future Transp. 2025, 5(4), 200; https://doi.org/10.3390/futuretransp5040200 - 15 Dec 2025
Viewed by 1188
Abstract
The production and sales figures for electric vehicles are showing a steady upward trend, clearly indicating the growing importance of sustainability goals. A unique historical situation has developed in the US: the owner of the leading electric car manufacturer (Tesla), Elon Musk, has [...] Read more.
The production and sales figures for electric vehicles are showing a steady upward trend, clearly indicating the growing importance of sustainability goals. A unique historical situation has developed in the US: the owner of the leading electric car manufacturer (Tesla), Elon Musk, has taken an active role in political life. Amid a rising trend in electric vehicle (EV) adoption aligned with global sustainability goals, the political activism of Musk has provoked public backlash, including acts of vandalism and aggression toward Tesla vehicles. Using a multidisciplinary approach, the study explores (1) the psychological underpinnings of object-directed violence, (2) the legal classification of politically motivated vandalism, and (3) the broader market implications of corporate politicization. Our findings confirm that object-directed aggression stems from displaced frustration, especially when individuals feel politically powerless or morally outraged. Our analysis revealed that most Tesla-related vandalism will likely be prosecuted as property crimes. Although U.S. officials have labeled some acts as domestic terrorism or hate crimes, legal thresholds are generally not met. Our interdisciplinary model suggests that the politicization of Tesla has broader implications. Tesla’s symbolic status in the electric vehicle market means that attacks on it risk triggering a decline in public trust toward electric mobility. Full article
(This article belongs to the Special Issue Future of Vehicles (FoV2025))
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12 pages, 1677 KB  
Article
Quantization of Faster R-CNN
by Tamás Menyhárt and Róbert Lakatos
Future Transp. 2025, 5(4), 175; https://doi.org/10.3390/futuretransp5040175 - 17 Nov 2025
Viewed by 957
Abstract
The Faster Region-based Convolutional Network (Faster R-CNN) is an efficient object detection model. However, its large size and significant computational requirements limit its applicability in embedded systems and real-time environments. Quantization is a proven method for reducing models’ size and computational requirements, but [...] Read more.
The Faster Region-based Convolutional Network (Faster R-CNN) is an efficient object detection model. However, its large size and significant computational requirements limit its applicability in embedded systems and real-time environments. Quantization is a proven method for reducing models’ size and computational requirements, but there is currently no open-source general implementation for quantizing Faster R-CNN. The main reason is that individual architecture components need to be quantized separately due to their structural characteristics. We present a general Faster R-CNN quantization algorithm, for which our implementation is open-source and compatible with the PyTorch (2.7.0+cu126, pt12) ecosystem. Our solution reduces the model size by 67.2% and the detection time by 50.4% while maintaining the accuracy measured on the test data within an error margin of 8.2% and a standard deviation of ±3.4%. It also allows for the visualization of model errors by extracting the model’s internal activation maps, supporting a more efficient understanding of its behavior. We demonstrate that the proposed method can effectively quantize Faster R-CNN, enabling the model to run on low-power hardware. This is particularly important in applications such as autonomous vehicles, embedded sensor systems, and real-time security surveillance, where fast and energy-efficient object detection is crucial. Full article
(This article belongs to the Special Issue Future of Vehicles (FoV2025))
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18 pages, 4051 KB  
Article
Phase Response Error Analysis in Dynamic Testing of Electric Drivetrains: Effects of Measurement Parameters
by Zoltán Gábor Gazdagh and Balázs Vehovszky
Future Transp. 2025, 5(4), 166; https://doi.org/10.3390/futuretransp5040166 - 6 Nov 2025
Viewed by 600
Abstract
The development of NVH (Noise, Vibration, and Harshness) characteristics in vehicles is facing new challenges with the widespread utilization of electric drivetrains. This shift introduces new requirements in several areas, such as reduced noise and vibration levels, the need for advanced nonlinear characterization [...] Read more.
The development of NVH (Noise, Vibration, and Harshness) characteristics in vehicles is facing new challenges with the widespread utilization of electric drivetrains. This shift introduces new requirements in several areas, such as reduced noise and vibration levels, the need for advanced nonlinear characterization methods, and tuning/masking the typically more prominent tonal noise components. More accurate simulation and measurement techniques are essential to meet these demands. This study focuses on the experimental frequency response function (FRF) testing of electric drivetrain components, specifically on potential phase errors caused by inappropriate measurement settings. The influencing parameters and their quantitative effects are analyzed theoretically and demonstrated using real measurement data. A novel numerical approach, termed Maximum Phase Error Analysis (MPEA), is introduced to systematically quantify the largest potential phase errors due to arbitrary alignment between resonance frequencies and discrete spectral lines. MPEA enhances the robustness of phase accuracy assessment, especially critical for lightly damped systems and closely spaced resonance peaks. Based on the findings, optimal testing parameters are proposed to ensure phase errors remain within a predefined limit. The results can be applied in various dynamic testing scenarios, including durability testing and rattling analysis. Full article
(This article belongs to the Special Issue Future of Vehicles (FoV2025))
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Review

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15 pages, 2006 KB  
Review
Fast Rail in the Era of Modal Shift: Global High-Speed Networks and Their Environmental and Socio-Economic Impacts
by Dániel Szabó and Viktória Panker
Future Transp. 2025, 5(4), 199; https://doi.org/10.3390/futuretransp5040199 - 14 Dec 2025
Cited by 1 | Viewed by 1098
Abstract
This paper reviews the role of high-speed rail (HSR) and other fast rail technologies in decarbonising inter-urban transport. It first outlines the global deployment of HSR, with particular emphasis on Europe and China, and situates these networks within the wider geography of fast [...] Read more.
This paper reviews the role of high-speed rail (HSR) and other fast rail technologies in decarbonising inter-urban transport. It first outlines the global deployment of HSR, with particular emphasis on Europe and China, and situates these networks within the wider geography of fast rail systems. The paper then compares HSR with competing modes such as air transport and passenger cars along key dimensions including door-to-door travel time, energy use and emissions. Building on a qualitative synthesis of the international literature, it discusses the environmental, economic and social impacts of HSR, highlighting conditions under which HSR can deliver substantial modal shift and life-cycle greenhouse gas savings, as well as situations where benefits are more limited or unevenly distributed. Finally, the review briefly considers emerging fast rail concepts such as Maglev and Hyperloop and argues that they should currently be treated as complementary, long-term options rather than immediate substitutes for conventional HSR. Full article
(This article belongs to the Special Issue Future of Vehicles (FoV2025))
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