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
AI and Technology Disruptions: Impacts on Transportation, Road Safety and...
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

AI and Technology Disruptions: Impacts on Transportation, Road Safety and Urban Form

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

Deadline for manuscript submissions: 29 November 2026 | Viewed by 2047

Special Issue Editors

Prof. Dr. Krsto Lipovac

E-Mail Website
Guest Editor
Road Safety Department, Faculty for Transport and Traffic Safety, Belgrade University, 11 000 Belgrade, Serbia
Interests: road safety; road safety management; road crash investigation and road crash analyses
Dr. Alan Ross

E-Mail Website
Guest Editor
Global-AI Solutions, V92 CR2X Kilflynn, Ireland
Interests: AI and technology impacts; road safety management; transportation; urban design; sustainable development goals

Special Issue Information

Dear Colleagues,

Current technological disruptions and advances in Artificial Intelligence (AI) will impact every aspect of society over the next few years. These disruptions will create unprecedented opportunities to rethink how we provide transportation for society and how we create and plan our urban environments to ensure safe, green, and sustainable environments for all.

The aim of this Special Issue is to explore the major technological disruptions that are already underway and which will result in fundamental changes in energy and transportation. These changes, in turn, will shape the structure, activities, liveability, and sustainability of our cities. With 50% of world population already living in urban areas, rising to 70% by 2050, cities will continue to be the dominant engines of economic growth and the societal structures within which most of the world’s population will live. The purpose of this Special Issue is to explore the radical changes that are likely to occur in transportation over the next decade and show why and how this will offer unprecedented opportunities to reshape our cities, re-purpose urban buildings, and re-allocate urban spaces to create greener and more sustainable transportation, urban areas, and livable cities.

In this Special Issue, original research articles and reviews are welcome. Research areas affecting transportation and its catalyst role in delivering more sustainable and liveable cities may include, but are not limited to, the following:

  • The impacts of the switch to electric vehicles on urban safety and pollution;
  • The impacts of autonomous driving and robotaxis on future urban traffic volumes;
  • The increasing role of AI in urban traffic management and transport planning;
  • The impact of AI and autonomous vehicles on traffic management;
  • The impacts of increased usage of drones for delivery instead of vans/lorries;
  • Regulation/control and management of flying cars;
  • Repurposing excess road space and surplus parking due to autonomous vehicles and robot-taxis reducing the need for parked cars in city centres;
  • Repurposing multi-storey carparks as vertical farms to reduce food miles;
  • The effects of food production in urban areas, e.g., precision fermentation;
  • Innovative business models for free public transport 24 hrs/day;
  • The impact of AI and autonomous driving on driving jobs (buses/lorries taxi drivers);
  • New innovative transportation modes for urban areas, etc.

We look forward to receiving your contributions.

Prof. Dr. Krsto Lipovac
Dr. Alan Ross
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

  • sustainability
  • transportation
  • autonomous vehicles
  • electric vehicles
  • AI
  • urban farming
  • 15-minute cities
  • smart cities
  • green walls
  • liveable cities
  • road safety
  • traffic management

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 (2 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

28 pages, 26621 KB  
Article
Dual-Modal Gated Fusion-Driven BEV 3D Object Detection: Enhancing Sustainable Intelligent Transportation in Nighttime Autonomous Driving
by Peifeng Liang, Ye Zhang, Xinyue Wu and Qiongyuan Wu
Sustainability 2026, 18(5), 2438; https://doi.org/10.3390/su18052438 - 3 Mar 2026
Viewed by 496
Abstract
Autonomous driving technology is a core enabler for new energy vehicle industrial upgrading and a critical pillar for achieving sustainable development goals (SDGs), especially sustainable urban mobility, low-carbon transportation, and efficient intelligent transportation systems (ITS). However, unstable nighttime low-light perception severely restricts autonomous [...] Read more.
Autonomous driving technology is a core enabler for new energy vehicle industrial upgrading and a critical pillar for achieving sustainable development goals (SDGs), especially sustainable urban mobility, low-carbon transportation, and efficient intelligent transportation systems (ITS). However, unstable nighttime low-light perception severely restricts autonomous driving deployment, hindering sustainable transportation development—rooted in visual feature degradation and cross-modal imbalance that impair 3D object detection (autonomous driving’s core perception technology). To address this and advance sustainable autonomous driving, this paper proposes a Bird’s-Eye View (BEV)-based multi-modal 3D object detection approach tailored for nighttime scenarios, integrating low-light adaptive components while preserving the original BEV pipeline. Without modifying core inference, it enhances low-light robustness and cross-modal fusion stability, ensuring reliable perception for sustainable autonomous driving operation. Extensive experiments on the nuScenes nighttime subset quantify performance via rigorous metrics (NDS, mAP, mATE). Results show the method outperforms BEVFusion with negligible parameter/inference overhead, achieving 1.13% NDS improvement. This validates its effectiveness and provides a sustainable technical tool for autonomous driving perception, promoting new energy vehicle popularization, optimizing urban ITS efficiency, reducing perception-related accidents and carbon emissions, and directly contributing to transportation and socio-economic sustainability. Full article
(This article belongs to the Special Issue AI and Technology Disruptions: Impacts on Transportation, Road Safety and Urban Form)
►▼ Show Figures

Figure 1

21 pages, 9102 KB  
Article
A Lightweight Edge AI Framework for Adaptive Traffic Signal Control in Mid-Sized Philippine Cities
by Alex L. Maureal, Franch Maverick A. Lorilla and Ginno L. Andres
Sustainability 2026, 18(3), 1147; https://doi.org/10.3390/su18031147 - 23 Jan 2026
Viewed by 1228
Abstract
Mid-sized Philippine cities commonly rely on fixed-time traffic signal plans that cannot respond to short-term, demand-driven surges, resulting in measurable idle time at stop lines, increased delay, and unnecessary emissions, while adaptive signal control has demonstrated performance benefits, many existing solutions depend on [...] Read more.
Mid-sized Philippine cities commonly rely on fixed-time traffic signal plans that cannot respond to short-term, demand-driven surges, resulting in measurable idle time at stop lines, increased delay, and unnecessary emissions, while adaptive signal control has demonstrated performance benefits, many existing solutions depend on centralized infrastructure and high-bandwidth connectivity, limiting their applicability for resource-constrained local government units (LGUs). This study reports a field deployment of TrafficEZ, a lightweight edge AI signal controller that reallocates green splits locally using traffic-density approximations derived from cabinet-mounted cameras. The controller follows a macroscopic, cycle-level control abstraction consistent with Transportation System Models (TSMs) and does not rely on stationary flow–density–speed (fundamental diagram) assumptions. The system estimates queued demand and discharge efficiency on-device and updates green time each cycle without altering cycle length, intergreen intervals, or pedestrian safety timings. A quasi-experimental pre–post evaluation was conducted at three signalized intersections in El Salvador City using an existing 125 s, three-phase fixed-time plan as the baseline. Observed field results show average per-vehicle delay reductions of 18–32%, with reclaimed effective green translating into approximately 50–200 additional vehicles per hour served at the busiest approaches. Box-occupancy durations shortened, indicating reduced spillback risk, while conservative idle-time estimates imply corresponding CO2 savings during peak periods. Because all decisions run locally within the signal cabinet, operation remained robust during backhaul interruptions and supported incremental, intersection-by-intersection deployment; per-cycle actions were logged to support auditability and governance reporting. These findings demonstrate that density-driven edge AI can deliver practical mobility, reliability, and sustainability gains for LGUs while supporting evidence-based governance and performance reporting. Full article
(This article belongs to the Special Issue AI and Technology Disruptions: Impacts on Transportation, Road Safety and Urban Form)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop