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Feature Review Papers in ‘Transportation and Future Mobility’ Section
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Feature Review Papers in ‘Transportation and Future Mobility’ Section

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Transportation and Future Mobility".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 9820

Special Issue Editors

Prof. Dr. David Fernández-Llorca

E-Mail Website
Guest Editor
Computer Engineering Department, University of Alcalá, 28805 Madrid, Spain
Interests: automated and autonomous vehicles; predictive perception and planning; human-vehicle interaction; trustworthy artificial intelligence; traffic behaviour; assistive intelligent transportation systems; digital twins for ITS
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Suchao Xie

E-Mail Website
Guest Editor
School of Traffic and Transportation Engineering, Central South University, Changsha 410083, China
Interests: railway vehicle dynamics; vehicle structure analysis; passive safety; Prognostic and Health Management (PHM); acoustic metamaterials
Special Issues, Collections and Topics in MDPI journals
Dr. Nadia Giuffrida

E-Mail Website
Guest Editor
DICATECH, Polytechnic University of Bari, 70125 Bari, Italy
Interests: transportation and land use; spatial analysis; participatory transport planning; transport and social inclusion; geographic information systems; planning for accessibility
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the Editorial Board Members of the section “Transportation and Future Mobility”, we are glad to announce the Special Issue “Feature Review Papers in ‘Transportation and Future Mobility’ Section”. This Special Issue aims to collect high-quality reviews, systematic reviews, and meta-analyses from the field of transportation.

Topics of interest include but are not limited to:

  • Intelligent transportation systems;
  • Traffic monitoring, modelling and control;
  • Urban and public transportation;
  • Air transportation;
  • Water transportation;
  • Rail transportation;
  • Freight and logistics;
  • Advanced driver assistance systems;
  • Automated and autonomous driving;
  • Vehicle safety and engineering systems;
  • Cooperative driving systems;
  • Human factors and human–machine interaction;
  • Sustainable transportation;
  • Transport and environment;
  • Electrified transportation systems;
  • Electric and hybrid vehicles;
  • Energy system for vehicles;
  • Privacy and security of transportation;
  • Artificial intelligence;
  • Decision and control systems;
  • Simulation and digital twins;
  • Internet of Things;
  • Intelligent mobility;
  • Big Data in future mobility;
  • Industry 4.0 in future mobility.

Prof. Dr. David Fernández-Llorca
Prof. Dr. Suchao Xie
Dr. Nadia Giuffrida
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. Applied Sciences 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 2400 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

  • transportation
  • traffic
  • future mobility

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

Published Papers (3 papers)

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Review

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20 pages, 372 KiB  
Review
Large Language Models for Intelligent Transportation: A Review of the State of the Art and Challenges
by Sebastian Wandelt, Changhong Zheng, Shuang Wang, Yucheng Liu and Xiaoqian Sun
Appl. Sci. 2024, 14(17), 7455; https://doi.org/10.3390/app14177455 - 23 Aug 2024
Cited by 5 | Viewed by 5274
Abstract
Large Language Models (LLMs), based on their highly developed ability to comprehend and generate human-like text, promise to revolutionize all aspects of society. These LLMs facilitate complex language understanding, translation, content generation, and problem-solving, enabled by vast historical data processing and fine-tuning. Throughout [...] Read more.
Large Language Models (LLMs), based on their highly developed ability to comprehend and generate human-like text, promise to revolutionize all aspects of society. These LLMs facilitate complex language understanding, translation, content generation, and problem-solving, enabled by vast historical data processing and fine-tuning. Throughout the past year, with the initial release of ChatGPT to the public, many papers have appeared on how to exploit LLMs for the ways we operate and interact with intelligent transportation systems. In this study, we review more than 130 papers on the subject and group them according to their major contributions into the following five categories: autonomous driving, safety, tourism, traffic, and others. Based on the aggregated proposals and findings in the extant literature, this paper concludes with a set of challenges and research recommendations, hopefully contributing to guide research in this young, yet extremely active research domain. Full article
(This article belongs to the Special Issue Feature Review Papers in ‘Transportation and Future Mobility’ Section)
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26 pages, 2026 KiB  
Review
Prediction and Analysis of Airport Surface Taxi Time: Classification, Features, and Methodology
by Jianan Yin, Mingwei Zhang, Yuanyuan Ma, Wei Wu, He Li and Ping Chen
Appl. Sci. 2024, 14(3), 1306; https://doi.org/10.3390/app14031306 - 5 Feb 2024
Cited by 3 | Viewed by 2584
Abstract
Airport arrival and departure movements are characterized by high dynamism, stochasticity, and uncertainty. Therefore, it is of paramount importance to predict and analyze surface taxi time accurately and scientifically. This paper conducts a comprehensive review of existing studies on surface taxi time prediction [...] Read more.
Airport arrival and departure movements are characterized by high dynamism, stochasticity, and uncertainty. Therefore, it is of paramount importance to predict and analyze surface taxi time accurately and scientifically. This paper conducts a comprehensive review of existing studies on surface taxi time prediction and analysis. Firstly, the overall research framework of surface taxi time prediction and analysis is categorized from three perspectives: taxi time type, movement type, and modeling method. Then, focusing on the two means of taxi time analytical modeling and simulation modeling, the existing mainstream models and methods are categorized, and the main ideas and scope of application of the various methods are analyzed. Finally, the paper presents the future development direction of surface taxi time prediction prospects. The research results are aimed at providing basic support and methodological guidance for reducing the uncertainty in airport surface operation and enhancing the level of control and decision-making ability of airport surface operation. Full article
(This article belongs to the Special Issue Feature Review Papers in ‘Transportation and Future Mobility’ Section)
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Other

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26 pages, 397 KiB  
Systematic Review
Dynamic Low-Emission Zones for Urban Mobility: A Systematic Review
by Pablo Manglano-Redondo, Alvaro Paricio-Garcia and Miguel A. Lopez-Carmona
Appl. Sci. 2025, 15(6), 2915; https://doi.org/10.3390/app15062915 - 7 Mar 2025
Cited by 1 | Viewed by 1010
Abstract
Urban air pollution, particularly from vehicular emissions, poses a significant challenge to public health and environmental sustainability. Low-Emission Zones (LEZs) have emerged as a solution, reducing pollution in high-traffic areas by restricting access to high-emission vehicles. However, most LEZ implementations are static, failing [...] Read more.
Urban air pollution, particularly from vehicular emissions, poses a significant challenge to public health and environmental sustainability. Low-Emission Zones (LEZs) have emerged as a solution, reducing pollution in high-traffic areas by restricting access to high-emission vehicles. However, most LEZ implementations are static, failing to account for real-time changes in traffic and emissions. This review focuses on dynamic LEZ systems, which are adjusted based on real-time data to optimize emission reduction without disrupting traffic flow. By categorizing LEZ strategies into static, hybrid, and dynamic systems, this study highlights key case studies and technologies, such as traffic simulation tools and sensor networks, that enable these adaptive systems. The review also discusses the challenges and future opportunities in LEZ implementation, emphasizing the need for data-driven approaches to achieve both environmental and mobility goals. This study aims to provide insights for policymakers and researchers seeking to enhance urban air quality management through more flexible, efficient LEZ strategies. Full article
(This article belongs to the Special Issue Feature Review Papers in ‘Transportation and Future Mobility’ Section)
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