sustainability-logo

Journal Browser

Journal Browser

Traffic Safety, Traffic Management, and Sustainable Mobility

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

Deadline for manuscript submissions: 31 July 2025 | Viewed by 777

Special Issue Editor


E-Mail Website
Guest Editor
Civil, Construction, and Environmental Engineering, University of Alabama at Birmingham, Birmingham, AL 35294, USA
Interests: traffic operations and safety; congestion mitigation; simulation and modeling; sustainable transportation

Special Issue Information

Dear Colleagues,

In 2023, over 1.19 million people died in traffic crashes worldwide, and another 50 million were seriously injured. Road traffic crashes have enormous consequences, including human suffering, disruption of traffic operations, and economic losses for individuals and communities. The World Health Organization (WHO) estimates that road traffic crashes cost most countries 3% of their gross domestic product. Even minor crashes can result in property losses and contribute to traffic disruption, delays, and non-recurring congestion. Concerns also exist about the implications of the promotion of sustainable transportation modes (such as non-motorized transportation options) for traffic safety and traffic operations. At present, over half of all traffic deaths reported are among vulnerable road users, including pedestrians, cyclists, and motorcyclists.

A holistic approach is needed to address traffic safety and its impacts on transportation operations in the context of sustainability. Re-examining transportation infrastructure and vehicle design, improving transportation planning, traffic management, and incident response, revisiting the role of public transportation and shared mobility, establishing laws and policies aiming at crash prevention and protection of vulnerable road users, along with education and enforcement initiatives, can help reduce the number of fatalities and injuries from road traffic crashes and their impacts.

This Special Issue focuses on the nexus between traffic safety, sustainability, and transportation operations. The impacts of new and emerging technologies on user mobility, road safety, and congestion management will be further considered. Submissions are encouraged to explore the role of initiatives and practices that support sustainability objectives in traffic operations, traffic safety, and their interactions. Case studies that explore the role of new technologies and sustainable transportation options on traffic safety and transportation management can provide valuable insights on the opportunities and challenges associated with the implementation of novel traffic management techniques and crash reduction strategies as part of the sustainability agenda.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Sustainable mobility and traffic safety;
  • Traffic safety and sustainability considerations in traffic management;
  • Planning for safe, sustainable, and efficient transportation options;
  • Impacts of traffic safety on traffic operations in urban and rural settings;
  • Addressing the mobility and traffic safety needs of vulnerable road users;
  • The role of green transportation modes in improving traffic safety and reducing congestion.

I look forward to receiving your contributions.

Prof. Dr. Virginia P. Sisiopiku
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 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

  • traffic safety
  • sustainability
  • transportation operations
  • traffic management
  • vulnerable transportation users
  • green transportation modes

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.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (1 paper)

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

Research

38 pages, 5080 KiB  
Article
An Ensemble of Machine Learning Models for the Classification and Selection of Categorical Variables in Traffic Inspection Work of Importance for the Sustainable Execution of Events
by Aleksandar Đukić, Milorad K. Banjanin, Mirko Stojčić, Tihomir Đurić, Radenka Đekić and Dejan Anđelković
Sustainability 2024, 16(22), 9720; https://doi.org/10.3390/su16229720 - 7 Nov 2024
Viewed by 614
Abstract
Traffic inspection (TraffIns) work in this article is positioned as a specific module of road traffic with its primary function oriented towards monitoring and sustainably controlling safe traffic and the execution of significant events within a particular geographic area. Exploratory research on the [...] Read more.
Traffic inspection (TraffIns) work in this article is positioned as a specific module of road traffic with its primary function oriented towards monitoring and sustainably controlling safe traffic and the execution of significant events within a particular geographic area. Exploratory research on the significance of event execution in simple, complicated, and complex traffic flow and process situations is related to the activities of monitoring and controlling functional states and performance of categorical variables. These variables include objects and locations of road infrastructure, communication infrastructure, and networks of traffic inspection resources. It is emphasized that the words “work” and “traffic” have the semantic status as synonyms (in one world language), which is explained in the design of the Agent-based model of the complexity of content and contextual structure of TraffIns work at the singular and plural levels with 12 points of interest (POI) in the thematic research. An Event Execution Log (EEL) was created for on-site data collection with eight variables, seven of which are independent (event type, activities, objects, locations, host, duration period, and periodicity of the event) and one dependent (significance of the event) variable. The structured dataset includes 10,994 input-output vectors in 970 categories collected in the EEL created by 32 human agents (traffic inspectors) over a 30-day period. An algorithmic presentation of the methodological research procedure for preprocessing and final data processing in the ensemble of machine learning models for classification and selection of TraffIns tasks is provided. Data cleaning was performed on the available dataset to increase data consistency for further processing. Vector elimination has been carried out based on the Location variable, such that the total number of vectors equals the number of unique categories of this variable, which is 636. The main result of this research is the classification modeling of the significance of events in TraffIns work based on machine learning techniques and the Stacking ensemble. The created machine learning models for Event Significance classification modeling have high accuracy values. To evaluate the performance metrics of the Stacking ensemble of the models, the confusion matrix, Precision, Recall, and F1 score are used. Full article
(This article belongs to the Special Issue Traffic Safety, Traffic Management, and Sustainable Mobility)
Show Figures

Figure 1

Back to TopTop