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Sustainable Traffic and Mobility—2nd Edition

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

Deadline for manuscript submissions: 5 June 2026 | Viewed by 496

Special Issue Editors

MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: human mobility; urban science; energy and environment; smart transportation
Special Issues, Collections and Topics in MDPI journals
Department of Transportation Information and Control Engineering, College of Transportation Engineering, Tongji University, Shanghai, China
Interests: shared mobility; public transit; data mining; machine learning
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Data and Business Intelligence, Shanghai Jiao Tong University, Shanghai 200030, China
Interests: fintech; mobility; AI ethics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues, 

The world is witnessing an ever-increasing demand for transportation and mobility solutions that are not only efficient and convenient but also environmentally sustainable. As we move towards a more sustainable future, it becomes imperative to address the challenges posed by transportation-related emissions, congestion, and resource depletion. To explore innovative approaches and advancements in sustainable transportation and mobility, we are pleased to announce a Special Issue focused on this critical topic. 

The Special Issue on “Sustainable Traffic and Mobility” aims to bring together cutting-edge research and diverse perspectives from scholars, researchers, and practitioners across the globe. We invite original contributions covering, but not limited to, the following topics:·   

  • Green and electric vehicles: Advances in electric and alternative fuel vehicles, charging infrastructure, battery technologies, and energy efficiency measures.
  • Public transportation: Innovations in public transport systems, including bus rapid transit, light rail, and shared mobility solutions, to reduce congestion and emissions.
  • Active transportation: Studies on walking, cycling, and other non-motorized modes of transport, promoting healthier and eco-friendly options.
  • Smart and intelligent transportation systems: Integration of digital technologies, IoT, and data analytics to optimize transportation networks and improve user experience.
  • Urban planning and design for sustainable mobility: Research on urban planning, infrastructure development, and policies that prioritize sustainable transportation options.
  • Policy and governance: Assessments of governmental policies, regulations, and incentives to accelerate the adoption of sustainable transportation practices.
  • Environmental impact and life cycle analysis: Studies examining the life cycle environmental impacts of various transportation modes and technologies.
  • Future mobility trends: Exploration of emerging trends, such as autonomous vehicles, hyperloop, and other transformative mobility concepts.

You may choose our Joint Special Issue in Vehicles.

Dr. Yanyan Xu
Dr. Yu Shen
Dr. Chunxiao Li
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

  • smart transportation 
  • public transportation 
  • travel behavior 
  • shared mobility 
  • environmentally friendly mobility

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Published Papers (1 paper)

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Research

30 pages, 6286 KB  
Article
Co-Optimization and Interpretability of Intelligent–Traditional Signal Control Based on Spatiotemporal Pressure Perception in Hybrid Control Scenarios
by Yingchang Xiong, Guoyang Qin, Jinglei Zeng, Keshuang Tang, Hong Zhu and Edward Chung
Sustainability 2025, 17(16), 7521; https://doi.org/10.3390/su17167521 - 20 Aug 2025
Viewed by 367
Abstract
As cities transition toward intelligent traffic systems, hybrid networks combining AI and traditional intersections raise challenges for efficiency and sustainability. Existing studies primarily focus on global intelligence assumptions, overlooking the practical complexities of hybrid control environments. Moreover, the decision-making processes of AI-based controllers [...] Read more.
As cities transition toward intelligent traffic systems, hybrid networks combining AI and traditional intersections raise challenges for efficiency and sustainability. Existing studies primarily focus on global intelligence assumptions, overlooking the practical complexities of hybrid control environments. Moreover, the decision-making processes of AI-based controllers remain opaque, limiting their reliability in dynamic traffic conditions. To address these challenges, this study investigates the following realistic scenario: a Deep Reinforcement Learning (DRL) intersection surrounded by max–pressure-controlled neighbors. A spatiotemporal pressure perception agent is proposed, which (a) uses a novel Holistic Traffic Dynamo State (HTDS) representation that integrates real-time queue, predicted vehicle merging patterns, and approaching traffic flows and (b) innovatively proposes Neighbor–Pressure–Adaptive Reward Weighting (NP-ARW) mechanism to dynamically adjust queue penalties at incoming lanes based on relative pressure differences. Additionally, spatial–temporal pressure features are modeled using 1D convolutional layers (Conv1D) and attention mechanisms. Finally, our Strategy Imitation–Mechanism Attribution framework leverages XGBoost and Decision Trees to systematically analyze traffic condition impacts on phase selection, fundamentally enabling explainable control logic. Experimental results demonstrate the following significant improvements: compared to fixed-time control, our method reduces average travel time by 65.45% and loss time by 85.04%, while simultaneously decreasing average queue lengths and pressure at neighboring intersections by 91.20% and 95.21%, respectively. Full article
(This article belongs to the Special Issue Sustainable Traffic and Mobility—2nd Edition)
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