Submit to Special Issue Submit Abstract to Special Issue Review for Sustainability Propose a Special Issue

Journal Menu

Journal Browser

Research on Sustainable Public Transportation System: Behavior, Safety and Planning—2nd Edition

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

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

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1829

Share This Special Issue

Special Issue Editor

Prof. Dr. Sangho Choo

E-Mail Website
Guest Editor

Department of Urban Design & Planning, Hongik University, Seoul 04066, Republic of Korea
Interests: travel behavior; transportation planning; urban public transport; mobility as a service; big data analysis; discrete choice modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Increasing concern over environmental degradation and the need to reduce greenhouse gas emissions have led to a growing interest in sustainable public transportation systems. With more and more people living in cities, public transportation systems have come to play a crucial role in providing an efficient, reliable, and environmentally friendly means of transportation. A sustainable public transportation system can not only reduce carbon emissions but also provide economic and social benefits, such as reduced traffic congestion, improved air quality, and enhanced accessibility to employment and education opportunities. In recent years, there have been significant advancements in the field of public transportation, and we aim to explore these developments further through this publication.

This Special Issue invites papers related to sustainable public transportation systems with respect to behavior, safety, and planning. We encourage new methodologies and various applications of data analysis for sustainable public transportation systems as well as multimodal transport systems in urban areas.

In this Special Issue, original research articles and review articles considering public transportation systems are welcome, and research areas may include, but are not limited to, the following topics:

Travel behavior of public transportation systems;
Public transportation demand forecasting;
Sustainable public transportation systems;
User satisfaction and perceptions;
Safety and security measures;
Integrated and multimodal transport systems;
Mobility as a service;
First/last miles for public transportation networks;
Emerging technologies and trends;
The application of large language models (LLMs) to public transit.

We look forward to receiving your contributions.

Prof. Dr. Sangho Choo
Guest Editor

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

public transportation systems
public transportation planning
travel behavior
multimodal transport systems
safety
mobility as a service
large language models (LLMs)

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 Show export options

Select all

Export citation of selected articles as:

Research

24 pages, 1073 KB

Open AccessArticle

Designing Accessible and Comfortable Bus Interiors for Sustainable and Smart Urban Mobility: A Pilot Experimental Ordinal Regression Study

by Mitsuyoshi Fukushi, Sebastián Seriani, Vicente Aprigliano, Alvaro Peña and Emilio Bustos

Sustainability 2026, 18(2), 1019; https://doi.org/10.3390/su18021019 - 19 Jan 2026

Viewed by 161

Abstract

Accessible and comfortable public transportation is a cornerstone of sustainable and inclusive urban mobility. However, there is a knowledge gap in how interior layout influences riders’ comfort perception under constant occupancy conditions. We conducted a pilot laboratory experiment in Valparaíso, Chile using a full-scale urban bus mock-up. Twenty-five participants each experienced four seating scenarios (yielding 100 total observations per outcome) that varied seat pitch (20, 30, 45 cm) and seat orientation (forward-facing vs. side-facing). Cumulative link mixed models were used to estimate seat pitch and orientation effects on the comfort outcomes, with participant-specific random intercepts. Increased seat pitch dramatically improved comfort ratings (e.g., virtually no participants felt comfortable at 20 cm, whereas nearly all did at 45 cm). Side-facing bench seating (longitudinal orientation) yielded significantly higher comfort, legroom, and ease-of-movement ratings than the forward-facing configuration at ~30 cm pitch (p < 0.001). Within the tested mock-up conditions, the results suggest that seat pitch is a major driver of perceived comfort and in-vehicle usability, and that a side-facing bench layout (tested at ~30 cm spacing) can improve perceived spaciousness relative to forward-facing seating. Because this is a small, non-probability pilot sample and a partial factorial design, these findings should be considered preliminary design sensitivities that warrant validation in larger, in-service studies before informing fleet-wide standards. Full article

(This article belongs to the Special Issue Research on Sustainable Public Transportation System: Behavior, Safety and Planning—2nd Edition)

► Show Figures

Figure 1

21 pages, 28904 KB

Open AccessArticle

Predicting Public Transit Demand Using Urban Imagery with a Dual-Latent Deep Learning Framework

by Eunseo Ko, Gitae Park and Sangho Choo

Sustainability 2026, 18(1), 67; https://doi.org/10.3390/su18010067 - 20 Dec 2025

Viewed by 294

Abstract

Public transit demand forecasting is a foundational component of sustainable urban mobility, enabling efficient operation, equitable service provision, and planning of public transit systems. Urban imagery, such as aerial images, contains rich information about urban sociodemographic characteristics and the built environment, offering particular value for data-scarce regions where conventional datasets are limited or outdated. However, there is limited research on using these images for public transit demand forecasting. This study introduces a deep learning approach for predicting transit ridership using aerial images. The method employs an encoder–decoder architecture to functionally separate image-derived latent representations into sociodemographic and physical environment vectors, which are subsequently used as inputs to a neural network for ridership prediction. Using data from Seoul, South Korea, the effectiveness of the proposed method is evaluated against three baseline configurations. The results show that the sociodemographic latent vector captures spatially organized residential characteristics, while the physical environment vector encodes distinct urban landscape patterns such as dense housing, traditional street grids, open spaces, and natural environments. The proposed model, which uses only imagery-derived latent features, substantially outperforms the pure image baseline and narrows the performance gap with census-informed models, reducing sMAPE by 25–60% depending on the mode. Combining imagery with census variables yields the highest accuracy, confirming their complementary nature. These findings highlight the potential of imagery-based approaches as a scalable, cost-efficient, and sustainable tool for data-driven transit planning. Full article

(This article belongs to the Special Issue Research on Sustainable Public Transportation System: Behavior, Safety and Planning—2nd Edition)

► Show Figures

Figure 1

34 pages, 4193 KB

Open AccessArticle

Impact of Traffic Calming Zones (TCZs) in Cities on Public Transport Operations

by Mirosław Czerliński, Tomasz Krukowicz, Michał Wolański and Patryk Pawłowski

Sustainability 2025, 17(22), 10012; https://doi.org/10.3390/su172210012 - 9 Nov 2025

Viewed by 991

Abstract

Traffic calming zones (TCZs) are increasingly being implemented in urban areas to enhance road safety, reduce vehicle speeds, and support sustainable mobility. However, their impact on public transport (PT) operations, particularly bus services, remains underexplored. This study examines the impact of classifying streets into TCZs on bus transport performance in Poland’s ten largest cities. Geospatial analysis and a custom R algorithm delineated areas suitable for TCZs based on road class and administrative category. GTFS data were analysed for almost 1000 bus lines to evaluate the overlap of their routes with TCZs. The findings reveal that in several cities, a significant portion of bus operations would run through TCZs, with the average route segment affected notably by city and zone classification methods. Differences in TCZ size and shape across cities were also statistically significant. This study concludes that although TCZs contribute to safer and more liveable urban environments, their influence on bus speeds, which can lead to changes in fuel or energy consumption, and route design must be carefully managed. Strategic planning is essential to find a balance between the benefits of traffic calming and the operational efficiency of PT. These insights offer valuable guidance for integrating TCZs into sustainable urban transport policy without compromising PT performance. Full article

(This article belongs to the Special Issue Research on Sustainable Public Transportation System: Behavior, Safety and Planning—2nd Edition)

► Show Figures

Journal Menu

Journal Browser

Research on Sustainable Public Transportation System: Behavior, Safety and Planning—2nd Edition

Share This Special Issue

Special Issue Editor

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (3 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI