Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
7.7
3.3
Journals
Sustainability
Special Issues
Sustainable, Intelligent, Resilient, and Connected Mobility and Transport Services
sustainability-logo
Submit to Special Issue Submit Abstract to Special Issue Review for Sustainability Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Sustainable, Intelligent, Resilient, and Connected Mobility and Transport Services

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

Deadline for manuscript submissions: 30 September 2026 | Viewed by 5093

Special Issue Editors

Dr. Yongxiang Zhang

E-Mail Website
Guest Editor
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Interests: optimization of rail transit operations; intelligent and real-time dispatching of rail transit systems; simulation of rail transit systems; rail transit big data technology and its applications
Special Issues, Collections and Topics in MDPI journals
Dr. Qingwei Zhong

E-Mail Website
Guest Editor
College of Air Traffic Management, Civil Aviation Flight University of China, Chengdu 641400, China
Interests: optimization modeling applied in railroad operation and scheduling; mathematical modeling and optimization; air traffic management
Special Issues, Collections and Topics in MDPI journals
Dr. Zhihong Yao

E-Mail Website
Guest Editor
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Interests: traffic signal control; connected automated vehicles; traffic flow theory; traffic simulation; machine learning; trajectory predictions
Special Issues, Collections and Topics in MDPI journals
Dr. Jingwei Guo

E-Mail Website
Guest Editor
Faculty of Business, City University of Macau, Macau SAR 999078, China
Interests: optimization of railway transport organization; transport economics; option theory and supply chain risk evaluation; artificial intelligence and deep learning; machine learning

Special Issue Information

Dear Colleagues,

We are calling for papers for a Special Issue of the journal of Sustainable, Intelligent, Resilient, and Connected Mobility and Transport Services. The rapid evolution of mobility and transport services is reshaping the way we move, live, and interact with our environment. As urban populations grow and technological advancements accelerate, the need for sustainable, intelligent, and resilient transport systems becomes increasingly urgent. This research area is pivotal in addressing global challenges such as climate change, urban congestion, and resource depletion. By integrating sustainability principles with cutting-edge technologies, we can create transport solutions that are not only efficient but also environmentally friendly and socially inclusive.

This special issue aims to explore innovative approaches and solutions in the realm of mobility and transport services that align with the principles of sustainability, intelligence, resilience, and connectivity. We invite researchers and practitioners to contribute original research articles, case studies, and reviews that delve into how these themes can transform transport systems. This issue is closely aligned with the journal's scope, which focuses on advancing knowledge and practices in sustainable development across various sectors. In this Special Issue, original research articles and reviews are welcome.

We welcome submissions on, but not limited to, the following themes:

  • Sustainable Mobility Solutions: Innovations in reducing the carbon footprint of transport systems, including electric and hybrid vehicles, renewable energy integration, and eco-friendly infrastructure design. 
  • Intelligent Transport Systems: The application of AI, IoT, and big data analytics in optimizing transport operations, enhancing safety, and improving user experience. 
  • Resilience in Transport Networks: Strategies to enhance the robustness and adaptability of transport systems in the face of disruptions such as natural disasters, pandemics, and cyber threats. 
  • Connected Mobility: The role of connectivity and digitalization in facilitating seamless, multimodal transport experiences, and the development of smart cities. 
  • Policy and Governance: Examination of regulatory frameworks and policy measures that support sustainable transport initiatives and innovation.

Research areas may include (but not limited to) the following:

  1. Integration of Renewable Energy in Public Transport Systems: Exploring the adoption of solar, wind, and other renewable energy sources in public transportation.
  2. Impact of Smart Infrastructure on Urban Mobility: Analyzing how smart roads, traffic lights, and parking systems contribute to efficient transport services.
  3. Resilience Strategies for Climate Change Adaptation in Transport: Developing approaches for transport systems to withstand and recover from climate-related disruptions.
  4. Cybersecurity in Connected Vehicle Networks: Investigating the security challenges and solutions for connected and autonomous vehicles.
  5. Behavioral Insights into Shared Mobility Adoption: Understanding consumer behavior and preferences in the adoption of shared mobility services.
  6. Blockchain Applications in Transport Logistics: Examining the use of blockchain for enhancing transparency and efficiency in transport logistics.
  7. Equity and Accessibility in Future Transport Systems: Addressing social inclusion and accessibility in the planning of sustainable transport solutions.
  8. Integration of Renewable Energy Sources in Public Transport: Exploring the feasibility and impact of integrating solar, wind, and other renewable energy sources into public transportation systems to enhance energy efficiency and sustainability.
  9. Optimization of Energy Consumption in Public Transit Systems: Investigating methods to reduce energy usage through route optimization, scheduling, and operational efficiency improvements in public transportation networks.
  10. Policy Frameworks for Sustainable Urban Transport: Developing policies that support sustainable urban transport initiatives.

We look forward to receiving your contributions.  

Dr. Yongxiang Zhang
Dr. Qingwei Zhong
Dr. Zhihong Yao
Dr. Jingwei Guo
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

  • connected vehicles
  • Mobility-as-a-Service (MaaS)
  • urban mobility innovation
  • transport electrification
  • smart infrastructure
  • autonomous vehicles
  • sustainable and shared mobility
  • intelligent transport systems
  • resilient transportation
  • transport policy and governance

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 (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

26 pages, 5301 KB  
Article
Resilience-Oriented Recovery Optimization of Metro Systems Under Extreme Rainfall-Induced Urban Flooding Disruptions
by Lu Huang, Zhigang Liu, Chengcheng Yu and Bing Yan
Sustainability 2026, 18(5), 2597; https://doi.org/10.3390/su18052597 - 6 Mar 2026
Cited by 1 | Viewed by 435
Abstract
Climate-induced natural hazards are increasingly disrupting metro operations in megacities, necessitating robust and generalizable frameworks for system-wide resilience. While current studies often treat infrastructure degradation, operational adjustment, and passenger flow redistribution as separate problems, this study proposes a resilience-oriented decision framework that couples [...] Read more.
Climate-induced natural hazards are increasingly disrupting metro operations in megacities, necessitating robust and generalizable frameworks for system-wide resilience. While current studies often treat infrastructure degradation, operational adjustment, and passenger flow redistribution as separate problems, this study proposes a resilience-oriented decision framework that couples these universal processes together to address diverse disruptive events. Taking extreme rainfall as a critical representative scenario, a multi-objective recovery optimization model is developed to jointly optimize repair resource cost and average section saturation. Resilience is quantified through the demand satisfaction ratio over the disruption–recovery process, ensuring the framework’s applicability across different hazard types. A case study of the Shanghai metro system under a real extreme rainfall event demonstrates the model’s efficacy in capturing complex system dynamics. Results show a clear Pareto trade-off between repair resource cost and average section saturation, while increasing service capacity on adjacent lines improves the Pareto frontier. Prioritizing repairs on lines with the fewest damaged sections effectively reduces network saturation by restoring corridor throughput. The resilience curve proves that higher repair resources not only shorten recovery time but also raise the minimum demand satisfaction ratio. These findings provide a scalable methodology for designing resilient metro recovery strategies under various climate-related disruptions globally. Full article
(This article belongs to the Special Issue Sustainable, Intelligent, Resilient, and Connected Mobility and Transport Services)
►▼ Show Figures

Figure 1

39 pages, 1813 KB  
Article
Facilitating Repurchase in the Sharing Economy: The Interaction of Service Quality, Perceived Usefulness, and Sustainability Motivations in Chinese Car-Sharing Services
by Shuang Hu, Jie Sun and Wei Li
Sustainability 2026, 18(5), 2505; https://doi.org/10.3390/su18052505 - 4 Mar 2026
Cited by 1 | Viewed by 1319
Abstract
Chinese users possess unique service experiences and behavioural intentions for utilising car-sharing. Car-sharing services offer a variety of competitive car-sharing options and possess distinctive traits that merit exploration. This mixed methods study examines the factors influencing repurchase intention in China’s car-sharing market by [...] Read more.
Chinese users possess unique service experiences and behavioural intentions for utilising car-sharing. Car-sharing services offer a variety of competitive car-sharing options and possess distinctive traits that merit exploration. This mixed methods study examines the factors influencing repurchase intention in China’s car-sharing market by combining qualitative insights with quantitative validation. Utilising the theory of planned behaviour and the technology acceptance model, we propose a framework wherein perceived ease of use, price consciousness, perceived security, perceived consumer effectiveness, and environmental concern directly affect repurchase intention, with service quality and perceived usefulness acting as essential mediators. Qualitative studies from 12 in-depth interviews indicate that user experiences are influenced by multifaceted convenience, pricing transparency, risk perception, and contextual usage patterns. A later quantitative analysis of 416 car-sharing service users was conducted utilising PLS-SEM. The findings indicate that perceived usefulness (β = 0.272, p < 0.001) is the most significant direct predictor of repurchase intention, followed by perceived security (β = 0.209) and environmental concern (β = 0.195). Service quality exerts a significant full mediating effect on the influence of perceived ease of use, and perceived security has a mediating effect on perceived usefulness (the direct effects of perceived ease of use and perceived security on perceived usefulness are not significant after including service quality as a mediator). The qualitative phase involved participants from eight major Chinese cities (Beijing, Shanghai, Guangzhou, Shenzhen, Dongguan, Wuhan, Changsha, and Zhengzhou), while the quantitative survey covered over 20 cities (including first-tier, new first-tier, and prefecture-level cities) via the Credamo platform, ensuring broad geographic representation. Significantly, price-quality beliefs do not substantially influence repurchase intention. This study contributes to the literature on the sharing economy by integrating technology, trust, and sustainability factors, providing practical recommendations for platform operators seeking to improve client retention in China’s competitive mobility sector. Full article
(This article belongs to the Special Issue Sustainable, Intelligent, Resilient, and Connected Mobility and Transport Services)
►▼ Show Figures

Figure 1

22 pages, 680 KB  
Article
Using the Large Language Model ChatGPT to Support Decisions in Sustainable Transport
by Paweł Ziemba and Filip Majewski
Sustainability 2025, 17(16), 7520; https://doi.org/10.3390/su17167520 - 20 Aug 2025
Cited by 1 | Viewed by 2209
Abstract
Recently, the popularity of large language models (LLMs) used as artificial intelligence tools supporting humans has been growing. LLMs are applied in many fields, including increasingly for various sustainability-related issues. One of the most popular tools of this type is ChatGPT, which, after [...] Read more.
Recently, the popularity of large language models (LLMs) used as artificial intelligence tools supporting humans has been growing. LLMs are applied in many fields, including increasingly for various sustainability-related issues. One of the most popular tools of this type is ChatGPT, which, after being supplied with appropriate knowledge, can act as a domain expert, including in the area of sustainable transport. The article uses this functionality of ChatGPT, feeding it with knowledge about electric vehicles (EVs) available on the Polish market. The aim of the research was to develop a solution based on an LLM, which will act as an advisor when buying an EV. After appropriate modelling of knowledge and feeding it into ChatGPT, an expert system was obtained, which, based on the defined needs of the user, recommends the most suitable EV for them. When answering the system’s questions, the user provides only a description of the decision-making situation at the LLM input (e.g., the locations to which they are travelling, information on the number of family members, etc.). In turn, the appropriately fine-tuned ChatGPT provides a recommendation of vehicles that meet the user’s defined needs. This is a very user-friendly solution because it does not require the user to precisely define the vehicle evaluation criteria or a set of alternatives. This approach also does not require the user to have detailed domain knowledge. Full article
(This article belongs to the Special Issue Sustainable, Intelligent, Resilient, and Connected Mobility and Transport Services)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop