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Hyper-Connected Cities: Advancing Intelligent Transport Systems for Sustainable and Resilient Mobility

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

Deadline for manuscript submissions: closed (14 December 2025) | Viewed by 1075

Special Issue Editors


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Guest Editor
Korea Transport Institute, Sejong 30147, Republic of Korea
Interests: connected and automated driving system; AI-based transportation; demand-responsive transit service; cloud system; intelligent transportation system
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Guest Editor
Department of Artificial Intelligence and Data Science, Sejong University, Seoul 05006, Republic of Korea
Interests: AI-based mobility system; route guidance system; cooperative–intelligent transportation system; connected and automated driving system

Special Issue Information

Dear Colleagues,

This Special Issue aims to explore advancements in intelligent transport systems (ITSs) that drive the transformation toward hyper-connected, sustainable, and resilient cities. It seeks to highlight research on data-driven smart mobility, connected and automated transport, infrastructure intelligence, and governance frameworks that shape the future of urban mobility. Special emphasis is placed on the role of AI, big data, mobility-as-a-service (MaaS), electrification, and policy innovations in integrating transport networks, improving urban traffic efficiency, and enhancing accessibility for all users. Additionally, this Special Issue examines the role of ITS in responding to crises, including climate change and urban resilience strategies.

This Special Issue aims to provide a platform for discussing emerging challenges and solutions in smart transportation technologies, urban mobility, and intelligent infrastructure development. Potential topics include (but are not limited to) the following:

  • Smart infrastructure and data ecosystems: big data collection, AI-driven traffic management, and real-time connectivity.
  • Connected and automated vehicles (CAVs): cooperative mobility, self-driving systems, and urban deployment challenges.
  • Mobility-as-a-service (MaaS) and on-demand transport: integration of shared mobility solutions, demand-responsive transit (DRT), and multimodal transport networks.
  • Sustainability and green mobility: electrification, carbon-neutral transport strategies, and ITS applications in smart cities.
  • Safety, security, and resilience: cybersecurity in ITS, pedestrian and vulnerable road user protection, and emergency response mechanisms.
  • Governance and policy innovation: legal frameworks, standardization, citizen engagement, and funding strategies for ITS deployment.

Dr. Sehyun Tak
Dr. Donghoun Lee
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. 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

  • intelligent transport systems (ITSs)
  • hyper-connected mobility
  • smart infrastructure
  • big data and AI in transport
  • connected and automated vehicles (CAVs)
  • mobility-as-a-service (MaaS)
  • demand-responsive transport (DRT)
  • sustainable and carbon-neutral mobility
  • cybersecurity and safety in ITS
  • urban resilience and transport policy

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Published Papers (1 paper)

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Research

25 pages, 3610 KB  
Article
Design of an Extended DCAT-Based Metadata Schema and Data Catalog for Autonomous Vehicle Accident Investigation
by Minwook Kim, Nayeon Kim, Heesoo Kim and Tai-Jin Song
Sustainability 2025, 17(24), 11237; https://doi.org/10.3390/su172411237 - 15 Dec 2025
Viewed by 691
Abstract
Autonomous vehicle (AV) accidents introduce uncertainty in liability attribution, as responsibility is divided between humans and automated systems. The 2018 Arizona crash highlighted growing societal concerns about accountability. To address these issues, prior studies proposed investigation processes considering perception sensors, driving control systems, [...] Read more.
Autonomous vehicle (AV) accidents introduce uncertainty in liability attribution, as responsibility is divided between humans and automated systems. The 2018 Arizona crash highlighted growing societal concerns about accountability. To address these issues, prior studies proposed investigation processes considering perception sensors, driving control systems, communication infrastructure, and cybersecurity. However, conducting such investigations requires integrating large-scale data from multiple sources, including vehicle sensors, onboard recorders, V2X communications, and road infrastructure. Raw data often lack descriptive information, limiting their use in real investigations. This study establishes a structured mapping framework linking investigation procedures, responsible entities, items, and data across accident phases. With this backdrop, an autonomous driving–specific metadata schema extending DCAT was designed, comprising 10 Classes and 76 Properties. To demonstrate its applicability, a prototype data catalog user interface (UI) was conceptualized with data discovery and visualization examples. The proposed schema strengthens accountability and interoperability by explicitly aligning responsibilities and data relationships. It enables precise event localization and effective linkage of heterogeneous data. Future work will refine the schema by incorporating DSSAD, V2X, and security log data, and develop a user-tested UI prototype as a practical support tool for AV accident investigation. Full article
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