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Information and Perception Technologies Development and Applications in the Transportation...
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Information and Perception Technologies Development and Applications in the Transportation Sector

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Transportation".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 5169

Special Issue Editors

Dr. Gabriele Cecchetti

E-Mail Website
Guest Editor
TeCIP Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
Interests: transportation; information technologies
Dr. Cristian Ulianov

E-Mail Website
Guest Editor
NewRail Newcastle Centre for Railway Research, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
Interests: railway engineering; reliability and maintainability of mechanical systems; manufacturing technologies (machining; welding and joining; non traditional technologies); composites engineering
Dr. Anna Lina Ruscelli

E-Mail Website
Guest Editor
TeCIP Institute, Scuola Superiore Sant’Anna, 56127 Pisa, Italy
Interests: wireless communications; sustainable railway transport; railway signalling and communications systems; railway management systems; intelligent transportation systems; e-health

Special Issue Information

Dear Colleagues,

The Special Issue on “Information and Perception Technologies Development and Applications in the Transportation Sector” provides a multidisciplinary and international forum for researchers, industries, operators, and infrastructure managers for the publication of the latest original research, achievements, and developments supported by the introduction of Information and Perception Technologies in different areas of the transportation sector. The Special Issue also introduces to a broader audience the more recent publicly financed projects aiming to introduce innovative technologies and methods in the transportation domain.

Recently, the transport sector has been the subject of an extensive innovation process driven by progressive digitization and the introduction of innovative technologies, also borrowed from areas other than transport, with positive effects on efficiency, sustainability, and inclusiveness. Furthermore, the environmental emergency due to CO2 emissions produced by the transport sector can contribute to a global rethinking of the different mass modes of transport, which are more attractive for environmentally friendly users. Finally, integrating different modes of transport is the current evolution of the sector, enabling a more efficient transport of people and goods and improving customer experience.

This Special Issue aims to provide a broad overview of the current evolution of the transport sector, focusing on new technologies and applications with a global approach where technological innovation and sustainability cooperate in designing efficient and sustainable modes of transport.

Reviews, regular research papers, communications, and short notes regarding all aspects of the Information and Perception Technologies Development and Applications in the Transportation Sector will be welcome.

Scientists and industrial operators are encouraged to publish their experimental and theoretical research about topics related, but not limited to:

  • Innovative and efficient intelligent transportation systems;
  • Traffic management systems;
  • Introduction of information and perception technologies in the transport domain to improve its efficiency and sustainability;
  • New platforms and demonstrators for innovative transport systems;
  • Transport sustainability;
  • Multimodality.

Dr. Gabriele Cecchetti
Dr. Cristian Ulianov
Dr. Anna Lina Ruscelli
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. Sustainability 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

  • sustainable transportation systems
  • traffic management systems
  • intelligent transportation systems
  • multimodality

Published Papers (4 papers)

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Research

22 pages, 19832 KiB  
Article
Toward the Enhancement of Rail Sustainability: Demonstration of a Holistic Approach to Obstacle Detection in Operational Railway Environments
by Miloš Simonović, Milan Banić, Dušan Stamenković, Marten Franke, Kai Michels, Ingo Schoolmann, Danijela Ristić-Durrant, Cristian Ulianov, Sergiu Dan-Stan, Alin Plesa and Marjan Dimec
Sustainability 2024, 16(7), 2613; https://0-doi-org.brum.beds.ac.uk/10.3390/su16072613 - 22 Mar 2024
Viewed by 526
Abstract
Rail transport plays a crucial role in promoting sustainability and reducing the environmental impact of transport. Ongoing efforts to improve the sustainability of rail transport through technological advancements and operational improvements are further enhancing its reputation as a sustainable mode of transport. Autonomous [...] Read more.
Rail transport plays a crucial role in promoting sustainability and reducing the environmental impact of transport. Ongoing efforts to improve the sustainability of rail transport through technological advancements and operational improvements are further enhancing its reputation as a sustainable mode of transport. Autonomous obstacle detection in railways is a critical aspect of railway safety and operation. While the widespread deployment of autonomous obstacle detection systems is still under consideration, the ongoing advancements in technology and infrastructure are paving the way for their full implementation. The SMART2 project developed a holistic obstacle detection (OD) system consisting of three sub-systems: long-range on-board, trackside (TS), and Unmanned Aerial Vehicle (UAV)-based OD sub-systems. All three sub-systems are integrated into a holistic OD system via interfaces to a central Decision Support System (DSS) that analyzes the inputs of all three sub-systems and makes decision about locations of possible hazardous obstacles with respect to trains. A holistic approach to autonomous obstacle detection for railways increases the detection area, including areas behind a curve, a slope, tunnels, and other elements blocking the train’s view on the rail tracks, in addition to providing long-range straight rail track OD. This paper presents a demonstration of the SMART2 holistic OD performed during the operational cargo haul with in-service trains. This paper defines the demonstration setup and scenario and shows the performance of the developed holistic OD system in a real environment. Full article
(This article belongs to the Special Issue Information and Perception Technologies Development and Applications in the Transportation Sector)
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16 pages, 6847 KiB  
Article
Demographic-Based Public Perception Analysis of Electric Vehicles on Online Social Networks
by Tavishi Priyam, Tao Ruan and Qin Lv
Sustainability 2024, 16(1), 305; https://0-doi-org.brum.beds.ac.uk/10.3390/su16010305 - 28 Dec 2023
Viewed by 1361
Abstract
Electric vehicles have gained significant popularity in the market, with sales increasing yearly. The introduction of new policies and reforms aimed at promoting environmental sustainability, coupled with the release of more advanced electric vehicles with higher driving ranges and technical specifications, has encouraged [...] Read more.
Electric vehicles have gained significant popularity in the market, with sales increasing yearly. The introduction of new policies and reforms aimed at promoting environmental sustainability, coupled with the release of more advanced electric vehicles with higher driving ranges and technical specifications, has encouraged more people to consider switching to electric vehicles. However, there is still a lack of understanding of public perception and the factors influencing the decision to switch to electric vehicles, especially among people from different demographic groups. In this study, we leverage machine learning techniques to analyze public opinion about electric vehicles across different demographic groups on two online social networks (OSNs), namely Reddit and Twitter. Our analyses provide valuable insights into how users on these platforms perceive electric vehicles and the factors that influence their perception. This information can be used to inform market strategies and future policies aimed at promoting the adoption of electric vehicles. Full article
(This article belongs to the Special Issue Information and Perception Technologies Development and Applications in the Transportation Sector)
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21 pages, 3796 KiB  
Article
Multimodal Traveling with Rail and Ride-Sharing: Lessons Learned during Planning and Demonstrating a Pilot Study
by Lambros Mitropoulos, Annie Kortsari, Emy Apostolopoulou, Georgia Ayfantopoulou and Alexandros Deloukas
Sustainability 2023, 15(18), 13755; https://0-doi-org.brum.beds.ac.uk/10.3390/su151813755 - 15 Sep 2023
Cited by 1 | Viewed by 872
Abstract
Multimodal traveling is expected to enhance mobility for users, reduce inequalities of car ownership, and reduce emissions. In the same context, ride-sharing aims to minimize negative impacts related to emissions, reduce travel costs and congestion, increase passenger vehicle occupancy, and increase public transit [...] Read more.
Multimodal traveling is expected to enhance mobility for users, reduce inequalities of car ownership, and reduce emissions. In the same context, ride-sharing aims to minimize negative impacts related to emissions, reduce travel costs and congestion, increase passenger vehicle occupancy, and increase public transit ridership when planned for first/last-mile trips. This study uses the empirical data gained from the pilot study in Athens, Greece, to outline a step-by-step planning guide for setting up a pilot study, and it concludes with challenges that emerged during and after its implementation. The demo aims to enhance the connection of low-density regions to public transport (PT) modes, specifically to the metro, through the provision of demand-responsive ride-sharing services. During the demo period, two different applications were utilized: the “Travel Companion” app and the “Driver Companion” app, which refer to passengers and drivers of the ride-sharing service, respectively. Demo participants were identified through a Stated Preference (SP) experiment. Challenges that were faced during the implementation show that although participants are willing to try new mobility solutions, the readiness and reliability of the new service are essential attributes in maintaining existing users and engaging new ones. Full article
(This article belongs to the Special Issue Information and Perception Technologies Development and Applications in the Transportation Sector)
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18 pages, 25163 KiB  
Article
RedNavi: Building a 3D Scene of the Current Sea from AIS Data
by Hongze Liu and Nobukazu Wakabayashi
Sustainability 2022, 14(19), 12572; https://0-doi-org.brum.beds.ac.uk/10.3390/su141912572 - 02 Oct 2022
Cited by 1 | Viewed by 1275
Abstract
The Automatic Identification System (AIS) is a kind of navigation equipment that exchanges a wealth of essential information among vessels and between ships to shore through Very High Frequency. Currently, identification and other navigational information can be obtained in real time with AIS [...] Read more.
The Automatic Identification System (AIS) is a kind of navigation equipment that exchanges a wealth of essential information among vessels and between ships to shore through Very High Frequency. Currently, identification and other navigational information can be obtained in real time with AIS data integrated into other shipborne systems, such as the Electronic Chart Display and Information System and radar. However, at present, AIS information is represented in a two-dimensional (2D) way, which is not the same as the three-dimensional (3D) world people perceive visually. In this paper, we introduce RedNavi, a sustainable computer 3D scene building system that visualizes the current sea, specifically the environment and traffic conditions around the ownship, using received AIS data. RedNavi has a wide range of application scenarios. Applying to the maritime education and training field, it can serve as a bridge between the 2D and 3D worlds, helping less experienced trainees build up their capabilities. Applying to actual navigation, it can provide the deck officer with another visual aid to their lookout in addition to existing 2D information systems. In addition, given the microservices architecture RedNavi adopts, the development, deployment, and maintenance processes become relatively lighter, faster, and easier, and therefore more sustainable than traditional monolithic systems. Full article
(This article belongs to the Special Issue Information and Perception Technologies Development and Applications in the Transportation Sector)
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