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Sustainable Transportation: Strategies for Enhancing Safety and Reliability

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

Deadline for manuscript submissions: 20 June 2025 | Viewed by 6618

Special Issue Editors


E-Mail Website
Guest Editor
Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, 2000 Maribor, Slovenia
Interests: traffic safety; sustainable mobility; microsimulation
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Maribor, Slovenia
Interests: traffic safety; sustainable mobility; microsimulation; vulnerable road users
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are very pleased to invite you to contribute to the Special Issue entitled “Sustainable Transportation: Strategies for Enhancing Safety and Reliability”. This Special Issue addresses two key issues for today’s society: road safety and sustainable mobility. Both aspects are necessary for a road transportation system that is safe and fair for all.

Recently, the Sustainable Safety approach has been introduced, which, similarly to other road safety approaches such as Vision Zero, aims to obtain the safest road traffic system possible. This concept builds on five principles: road functionality, (bio)mechanics, road users’ psychology, governments’ and stakeholders’ responsibility, and research and knowledge. Moreover, this method underlines the need for proper infrastructure that takes into consideration the needs of more vulnerable road users, such as children, teenagers, and elderly people, and less safe traffic participants, such as (powered) two-wheelers. Additionally, it encourages the use of both pro-active and reactive approaches to have a comprehensive vision of the road safety problem, which could lead to concrete actions.

The aim of this Special Issue is to provide a collection of studies focusing on key issues in road safety and sustainable mobility, especially with progress related to road design, driver behavior and human factors, and road safety policies. Of particular interest are original and/or review papers addressing (but not limited to) the following topics:

  • Concepts and approaches for sustainability and safety in road traffic;
  • Pro-active and re-active methods and models to predict road safety;
  • Safe road infrastructure;
  • Safe vehicles and ADAS;
  • Human factors for motorized traffic;
  • Perceived and real road safety;
  • Issues related to fitness to drive (fatigue, distraction, etc.);
  • Innovative road infrastructure to increase vulnerable road users’ safety;
  • Human factors for vulnerable road users;
  • Accessibility and inclusiveness of the road infrastructure;
  • Road safety issues of people with reduced physical capabilities/mobility.

We look forward to receiving your contributions.

Prof. Dr. Matjaž Šraml
Dr. Chiara Gruden
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

  • road safety
  • sustainable mobility
  • safe roads and vehicles
  • human factors in road safety
  • vulnerable road users

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Published Papers (5 papers)

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Research

25 pages, 19849 KiB  
Article
Drivers’ Perspective on Traffic Safety and Impacts from the Surrounding Landscape: A Case Study of Serbia
by Ivana Sentić, Ivana Živojinović, Jasmina Đorđević and Jelena Tomićević-Dubljević
Sustainability 2025, 17(5), 1936; https://doi.org/10.3390/su17051936 - 25 Feb 2025
Viewed by 650
Abstract
Due to the high volume of traffic on European highways and the increased percentage of traffic accidents and fatalities, traffic safety is imperative in the planning and design of highways. While highway safety design construction standards have been extensively researched, insufficient attention has [...] Read more.
Due to the high volume of traffic on European highways and the increased percentage of traffic accidents and fatalities, traffic safety is imperative in the planning and design of highways. While highway safety design construction standards have been extensively researched, insufficient attention has been given to the influence of the surrounding landscape on traffic safety and to drivers’ awareness about the danger of the same. Thus, the aim of the research was to assess drivers’ perceptions of various factors impacting highway traffic safety (climatic impacts from the surrounding landscape, landscape vegetation that follows the roadway, and animals) beyond specific engineering features (roadway surface, traffic signs, highway junction points). A survey of 138 drivers was conducted to assess driver awareness of traffic safety on the research section of a highway in Serbia. This highway is part of the Serbian highway that is a key connection within the European road network, forming an integral part of several major routes. The survey revealed that drivers, regardless of gender or experience, primarily associate traffic safety with well-built roads and good visibility during driving. While the impacts of climatic elements from the surrounding landscape were acknowledged, drivers do not strongly attribute any danger to traffic safety from these factors due to their lack of visibility. This is reflected in the notable number of traffic accidents, impacted by these factors, on the studied highway (e.g., 12% of the total number of accidents during 2022). Vegetation and animals did not play a significant role in the respondents’ answers, which should not be the case; however, their absence in the highway landscape and along the roadway led to a lack of observed quality by drivers. This underscores the need for the scientific community and policymakers to delve deeper into these issues with a broader perspective, and to elevate highway safety standards accordingly. Full article
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19 pages, 5523 KiB  
Article
In-Depth Analysis of Fatal Motorcycle Accidents—Case Study in Slovenia
by Tomaž Tollazzi, Laura Brigita Parežnik, Chiara Gruden and Marko Renčelj
Sustainability 2025, 17(3), 876; https://doi.org/10.3390/su17030876 - 22 Jan 2025
Viewed by 1091
Abstract
Motorcyclists remain a disproportionately large group of vulnerable road users, with fatality rates significantly higher than that in other road groups. Additionally, fatal accidents involving motorcyclists have a more slowly decreasing trend in comparison to that of other road users, while the number [...] Read more.
Motorcyclists remain a disproportionately large group of vulnerable road users, with fatality rates significantly higher than that in other road groups. Additionally, fatal accidents involving motorcyclists have a more slowly decreasing trend in comparison to that of other road users, while the number of this kind of users is growing fast. For all these reasons, there is a need to understand what the key factors leading to fatal accidents are in order to identify the possible measures to minimize the accidents themselves or at least their consequences. This would permit, indeed, to positively impact the road traffic system, leading to the creation of the safest road traffic system possible, as it is the goal of the Sustainable Safety approach. The aim of this study is to dive into the mentioned problem, analyzing fatal motorcycle accidents in Slovenia over a decade, highlighting the key factors contributing to these incidents. By integrating data from four databases, the study evaluated accident trends, infrastructural elements, and rider behavior through a multi-stage analysis. Firstly, data were collected from four national, up-to-date databases that contain information about road accidents themselves, the road infrastructure, additional police data, and media descriptions. After merging this information into one comprehensive database, where each row represents all the data available for one accident, a general analysis of accidents’ trends over the considered 10-year period was developed, considering at first all fatal road accidents, then deepening it to accidents caused by a motorcyclist, and finally to single-vehicle accidents. A statistical analysis followed, aimed at identifying a statistical correlation between the accidents and the factors leading to them. The results of the first accident analysis indicated that excessive speed, incorrect driving direction, and overtaking maneuvers are the primary causes of fatal accidents, especially on non-urban roads preferred by motorcyclists. Single-vehicle accidents frequently involve collisions with roadside objects, including safety barriers and poles, underscoring the need for targeted infrastructural improvements. The following correlation analysis revealed that a total of seven factors were statistically significant: three human factors (age, gender, experience)—which were the ones with the strongest correlations—one infrastructural factor (pavement width), and three factors belonging to external conditions (accident type, cause, and location). Of these, four were positively correlated to the causer, while three, i.e., pavement width, causes, and road location, were negatively correlated. This study provides a foundation for future research on less severe accidents and proactive risk behavior analysis, aiming to improve motorcyclist safety comprehensively. Full article
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16 pages, 2022 KiB  
Article
A Novel Accident Duration Prediction Method Based on a Conditional Table Generative Adversarial Network and Transformer
by Yongdong Wang, Haonan Zhai, Xianghong Cao and Xin Geng
Sustainability 2024, 16(16), 6821; https://doi.org/10.3390/su16166821 - 9 Aug 2024
Cited by 1 | Viewed by 1281
Abstract
The accurate duration prediction of road traffic accident is crucial for ensuring the safe and efficiency of transportation within social road networks. Such predictive capabilities provide significant support for informed decision-making by transportation administrators while also offering new technological support for the sustainable [...] Read more.
The accurate duration prediction of road traffic accident is crucial for ensuring the safe and efficiency of transportation within social road networks. Such predictive capabilities provide significant support for informed decision-making by transportation administrators while also offering new technological support for the sustainable development of modern road networks. This study introduced a novel predictive model for road traffic accident duration, integrating a Conditional Table Generative Adversarial Network (CTGAN) with a transformer architecture. We initially utilized CTGAN to augment and refine the historical accident dataset. Subsequently, we implemented a wavelet denoising technique to cleanse the expanded dataset. The core of our model lies in the application of the transformer mechanism, which was trained to forecast the accident duration with high precision. To prove the effectiveness of our proposed model, a series of comparative experiments were designed and executed. The experimental results show that the prediction error of CTGAN-Tr for accident duration in the accident area could reach below 0.8. Compared with other models, the MAE of CTGAN-Tr was reduced by 0.31 compared with GRU, and the correlation coefficient was increased by 0.2 compared with TCN. At the same time, the model can show excellent performance in the other two accident areas. The results of these experiments not only substantiate the performance of our model but also demonstrate its robustness and generalizability when applied to traffic accident data from other regions. Full article
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16 pages, 1249 KiB  
Article
A Sustainable Approach to How Roadway Recognition Affects Drivers’ Speed Choice
by Ruy Santos Ribeiro, Orlando Yesid Esparza Albarracin, Guilherme Rodrigues Linhares, Ana Paula C. Larocca and Liedi Legi B. Bernucci
Sustainability 2024, 16(15), 6546; https://doi.org/10.3390/su16156546 - 31 Jul 2024
Viewed by 1079
Abstract
Previous research has reported that driving on a familiar roadway can influence speed choice. However, the findings have not been extensively discussed in simulated environments, which are frequently used for assessments of driving behavior and traffic safety. This study assesses the effects of [...] Read more.
Previous research has reported that driving on a familiar roadway can influence speed choice. However, the findings have not been extensively discussed in simulated environments, which are frequently used for assessments of driving behavior and traffic safety. This study assesses the effects of familiar roadways on drivers’ speed behavior in a driving simulator environment. During testing, 120 individuals drove through two blocks of four scenarios, each representing a real stretch of a mountainous Brazilian highway, with differences among the scenarios in advisory signs but with the same regulated speed. The participants could drive during the first, second, third, or fourth round, as established by random sorting. Afterwards, a Kruskal–Wallis Analysis of Variance (ANOVA) test was applied to search for significant differences in average speed between the rounds and scenarios. The results showed no significant differences in average speed (p-value < 0.05; α = 0.05); moreover, the drivers’ ability and time licensed were not necessarily correlated with average speed, supporting future research with repeated scenarios towards maximizing the sample’s utility for speed analysis in driving simulators. Full article
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23 pages, 7814 KiB  
Article
Classification of Roadway Context and Target Speed for Multilane Highways in Thailand Using Fuzzy Expert System
by Chomphunut Sutheerakul, Nopadon Kronprasert, Wichuda Satiennam and Moe Sandi Zaw
Sustainability 2024, 16(9), 3865; https://doi.org/10.3390/su16093865 - 5 May 2024
Viewed by 1739
Abstract
The classification of roadway contexts and speeds is a critical step in the planning, design, and operation of highway infrastructure. In developing countries, road users encounter safety and operational issues due to poorly defined roadway contexts and inappropriately determined target speeds for a [...] Read more.
The classification of roadway contexts and speeds is a critical step in the planning, design, and operation of highway infrastructure. In developing countries, road users encounter safety and operational issues due to poorly defined roadway contexts and inappropriately determined target speeds for a highway network. This study developed an expert system for classifying roadway contexts and target speeds of multilane highway segments and applied the classification process to 16,235 km of multilane highways in Thailand’s highway network. The proposed methodology used a fuzzy decision mechanism to deal with subjective and imprecise expert judgment (e.g., low, high), many variables, and a complex evaluation process. This study used the Fuzzy Delphi method to identify the possible important factors influencing contexts and speeds and the Fuzzy Inference System method to reason factors to categorize multilane highway segments in Thailand into different classes of roadway contexts (e.g., rural, low-density suburban, high-density suburban, and urban highways) and target speeds (e.g., ≤50 km/h, 50–60 km/h, 60–70 km/h, 70–80 km/h, 80–90 km/h, 90–100 km/h, and 100 km/h). The study was based on data from questionnaire surveys of experts and field investigations of 120 highway segments. The results showed that roadside environments and activities influence the roadway contexts, while the target speeds are sensitive to the roadway characteristics and contexts. These findings support the need for changes in context-adapted highway design and speed management. The proposed expert system provided high accuracy (90.8%) in classifications of both roadway contexts and target speeds. The fuzzy expert system provides a systematic and structural framework for analyzing imprecise data in highway contextual and speed classifications and improving the clarity and accuracy of the evaluation process. The implementation of the fuzzy expert system has the potential to revolutionize the highway classification decision-making problem under uncertainty. Full article
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