sustainability-logo

Journal Browser

Journal Browser

Sustainable Urban Mobility: Road Safety and Traffic Engineering

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

Deadline for manuscript submissions: 16 January 2026 | Viewed by 3326

Special Issue Editors


E-Mail Website
Guest Editor
Transport and Mobility Laboratory, School of Architecture, Civil and Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
Interests: discrete choice modelling; road safety; sustainable mobility; micromobility; human factors
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Laboratory of Transportation Planning, Transportation Engineering & Highway Engineering, Department of Transportation & Hydraulic Engineering, School of Rural & Surveying Engineering, Faculty of Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
Interests: transport planning; active mobility; walkability; accessibility; micromobility; cycling; pedestrians
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As urban areas continue to develop, ensuring sustainable, safe, and efficient transportation systems is crucial for supporting economic vitality, reducing environmental impacts, improving road safety, and enhancing quality of life. This Special Issue on "Sustainable Urban Mobility: Road Safety and Traffic Engineering" invites research on the latest innovations, challenges, best practices, and findings in the areas of road safety and traffic engineering in relation to sustainable urban mobility.

Some key themes of this issue include sustainable transport planning, smart mobility and autonomous solutions, micromobility, and innovative traffic management strategies. In particular, we welcome submissions that address topics such as sustainable infrastructure design, the integration of non-motorized modes, electric and public transport modes, smart infrastructure, autonomous vehicles, and novel approaches in traffic safety and monitoring.

This Special Issue aims to bring together multidisciplinary insights to support the development of urban transport systems that prioritize safety, sustainability, and resilience. By contributing to this issue, researchers can help shape a safer, greener, and more accessible future for urban mobility.

Dr. Evangelos Paschalidis
Prof. Dr. Socrates Basbas
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 urban transport
  • road safety
  • traffic engineering
  • smart mobility
  • pedestrian safety
  • cyclist safety
  • micromobility
  • autonomous vehicles
  • traffic management
  • infrastructure design

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 (4 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

23 pages, 9667 KiB  
Article
Analysis of Traffic Conflicts on Slow-Moving Shared Paths in Shenzhen, China
by Lingyi Miao, Feifei Liu and Yuanchang Deng
Sustainability 2025, 17(9), 4095; https://doi.org/10.3390/su17094095 - 1 May 2025
Viewed by 376
Abstract
The rapid growth of e-bikes has intensified traffic conflicts on slow-moving shared paths in China. This study analyzed traffic safety of pedestrians and non-motorized vehicles and examined the factors influencing conflict severity utilizing traffic conflict techniques. Video-based surveys were conducted on six shared [...] Read more.
The rapid growth of e-bikes has intensified traffic conflicts on slow-moving shared paths in China. This study analyzed traffic safety of pedestrians and non-motorized vehicles and examined the factors influencing conflict severity utilizing traffic conflict techniques. Video-based surveys were conducted on six shared paths in Shenzhen, and conflict trajectory was extracted by Petrack software (Version 0.8). The minimum Time to Collision and Yaw Rate Ratio were selected as conflict indicators. Fuzzy c-means clustering was employed to classify conflicts into three severity levels: 579 potential conflicts, 435 minor conflicts, and 150 serious conflicts. Nineteen feature variables related to road environment, traffic operation, conflict sample information, and conflict behavior were considered. A SMOTE random forest model was constructed to explore critical influencing factors systematically. The results identified ten key factors affecting conflict severity. The increase in conflict severity is associated with the rise in pedestrian proportion and flow, and the decrease in e-bike proportion and flow. Male participants and pedestrians are more likely to engage in serious conflicts, while illegal lane occupation and wrong-way travel further elevate the severity level. These findings can provide references for traffic engineers and planners to enhance the safety management of shared paths and contribute to sustainable non-motorized transport. Full article
(This article belongs to the Special Issue Sustainable Urban Mobility: Road Safety and Traffic Engineering)
Show Figures

Figure 1

21 pages, 1836 KiB  
Article
Assessing the Impact of a Low-Emission Zone on Air Quality Using Machine Learning Algorithms in a Business-As-Usual Scenario
by Marta Doval-Miñarro, María C. Bueso and Pedro Antonio Guillén-Alcaraz
Sustainability 2025, 17(8), 3582; https://doi.org/10.3390/su17083582 - 16 Apr 2025
Viewed by 765
Abstract
The proliferation of low-emission zones (LEZs) across Europe is anticipated to accelerate in the coming years as a measure to enhance air quality in urban areas. Nevertheless, there is a lack of a standardized methodology to evaluate their effectiveness, and some of the [...] Read more.
The proliferation of low-emission zones (LEZs) across Europe is anticipated to accelerate in the coming years as a measure to enhance air quality in urban areas. Nevertheless, there is a lack of a standardized methodology to evaluate their effectiveness, and some of the proposed strategies may not adequately address air quality issues or overlook meteorological considerations. In this study, we employ three machine learning (ML) algorithms to forecast NO2, PM10 and PM2.5 concentrations in the air in Madrid in 2022 (post-LEZ) based on data from the period 2015–2018 (pre-LEZ) under a business-as-usual scenario, accounting for seasonal and meteorological factors. According to the models, the reductions in NO2 concentrations in 2022 varied from 29 to 35% in contrast to a scenario without the LEZ, which is coherent with the observed decrease in 2022 in traffic volume inside the area limited by the LEZ. However, no clear improvement was observed for PM10 and PM2.5 concentrations. Full article
(This article belongs to the Special Issue Sustainable Urban Mobility: Road Safety and Traffic Engineering)
Show Figures

Graphical abstract

20 pages, 2680 KiB  
Article
Evaluating the Environmental and Safety Impacts of Eco-Driving in Urban and Highway Environments
by Marios Sekadakis, Maria Ioanna Sousouni, Thodoris Garefalakis, Maria G. Oikonomou, Apostolos Ziakopoulos and George Yannis
Sustainability 2025, 17(6), 2762; https://doi.org/10.3390/su17062762 - 20 Mar 2025
Viewed by 826
Abstract
The present study aims to investigate the benefits of eco-driving in urban areas and on highways through an experiment conducted in a driving simulator. Within a group of 39 participants aged 18–30, multiple driving scenarios were conducted, both without and with eco-driving guides, [...] Read more.
The present study aims to investigate the benefits of eco-driving in urban areas and on highways through an experiment conducted in a driving simulator. Within a group of 39 participants aged 18–30, multiple driving scenarios were conducted, both without and with eco-driving guides, to assess the impact of eco-driving behavior on environmental sustainability and safety outcomes. Data on pollutant emissions, including carbon dioxide (CO2), carbon monoxide (CO), and nitrogen oxides (NOx), as well as crash probability, were collected during the experiment. The relationships between driving behavior and pollutant emissions were estimated using linear regression models, while binary logistic regression models were employed to assess crash probability. The analysis revealed that eco-driving led to a significant reduction in pollutant emissions, with CO2 emissions decreasing by 1.42%, CO by 98.2%, and NOx by 20.7% across both urban and highway environments, with a more substantial impact in urban settings due to lower average speeds and smoother driving patterns. Furthermore, eco-driving reduced crash probability by 90.0%, with urban areas exhibiting an 86.8% higher crash likelihood compared to highways due to higher traffic density and more complex driving conditions. These findings highlight the dual benefit of eco-driving in reducing environmental impact and improving road safety. This study supports the integration of eco-driving techniques into transportation policies and driver education programs to foster sustainable and safer driving practices. Full article
(This article belongs to the Special Issue Sustainable Urban Mobility: Road Safety and Traffic Engineering)
Show Figures

Figure 1

22 pages, 2874 KiB  
Article
Priority-Driven Resource Allocation with Reuse for Platooning in 5G Vehicular Network
by Tae-Woo Kim, Sanghoon Lee, Dong-Hyung Lee and Kyung-Joon Park
Sustainability 2025, 17(4), 1747; https://doi.org/10.3390/su17041747 - 19 Feb 2025
Viewed by 721
Abstract
Recently, Vehicle-to-Everything (V2X) communication has emerged as a critical technology for enhancing the safety and traffic management of autonomous vehicles. Developing a resource allocation algorithm that enables autonomous vehicles to perceive and react to their surroundings in real time through fast and reliable [...] Read more.
Recently, Vehicle-to-Everything (V2X) communication has emerged as a critical technology for enhancing the safety and traffic management of autonomous vehicles. Developing a resource allocation algorithm that enables autonomous vehicles to perceive and react to their surroundings in real time through fast and reliable communication is of paramount importance. This paper proposes a novel resource allocation algorithm that minimizes the degradation of communication performance for non-platoon vehicles while ensuring low-latency, high-reliability communication within vehicle platoons. The proposed algorithm prioritizes platoon vehicles and enhances resource efficiency by simultaneously applying interference-based and distance-based resource reuse techniques. Performance evaluations conducted using the Simu5G simulator demonstrate that the proposed algorithm consistently maintains the average resource allocation rate and delay for both platoon and non-platoon vehicles, even as the number of platoons increases. Specifically, in a congested environment with 60 general vehicles and five platoons, the proposed algorithm achieves an average resource allocation rate of over 90%, significantly outperforming existing algorithms such as Max-C/I, which achieves only 58%, and the priority-based algorithm with 54%, ensuring reliable communication for all vehicles. Full article
(This article belongs to the Special Issue Sustainable Urban Mobility: Road Safety and Traffic Engineering)
Show Figures

Figure 1

Back to TopTop