Emerging Transportation Solutions for Safer and Greener Future Mobility

Dear Colleagues,

With the emergence of new technologies such as connected and automated vehicles, big data, shared mobility, and electric vehicles, intelligent transportation systems (ITS) are constantly being updated and upgraded to provide comprehensive services that are safer, more sustainable, and more efficient. However, opportunities are always accompanied by challenges. New technologies bring a great deal of new research and practical questions as well, which need collective efforts from interdisciplinary fields.

At present, safety issues in ITS have attracted extensive attention, and human factors have been found to be one of the most important sources of risk. More in-depth investigations on potential impacting factors and prevention methods of human-factor-related traffic accidents are still needed—for example, the driving styles and risk compensation behavior under ITS, the effectiveness of advanced driver-assistance systems in preventing traffic accidents, behavior modeling and safety protection of vulnerable road users (e.g., cyclists, pedestrians), dangerous scenarios under autonomous driving, etc. Meanwhile, ITS bring a large amount of multi-source heterogeneous data, including natural driving data, crash data of autonomous vehicles, and wide-range vehicle trajectory data. This leads to the extension of the corresponding analysis methods, from traditional statistical methods to machine learning and deep learning. The application of these novel methods will further improve traffic safety in emerging ITS.

COP27 has further urged the world to take solid actions to reduce greenhouse emissions from different sectors. Electric vehicles, shared mobility, and intelligent connected vehicles are potential sustainable solutions in the transportation sector, but need further scientific planning, operation optimization, promotion strategies, and regulations to fulfill their sustainable merits. For instance, many cities are in the early stages of electrifying transportation systems, with insufficient planning and inadequate charging facilities. The rapid increase in loads from electric vehicle charging is not incorporated into the power grid maintenance and upgrade plans. Additionally, due to range limitations and charging needs, electric buses operate with lower availability than conventional buses, and many users are not willing to shift towards sustainable mobility alternatives. Although some studies have investigated these topics to some extent, more explorations should be made to advance these areas by leveraging emerging methods such as big data, machine learning, and edge computing, which are expected to have superior performances.

This Special Issue is devoted to addressing challenges in the modeling, optimization, analysis, and policymaking of utilizing emerging transportation solutions for improving transportation safety and reducing emissions. This Special Issue especially welcomes studies that utilize machine learning, new data resources, and interdisciplinary solutions to promote the safety and sustainability of transportation systems. It is open to any subject area of the related theme; of particular interest are traffic safety and risk analysis, human factors in ITS, eco-driving, transportation electrification and shared mobility, connected and automated vehicles, advanced driver-assistance systems, etc.

Dr. Bo Yu
Dr. Kun Gao
Dr. Yueru Xu
Dr. You Kong
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. International Journal of Environmental Research and Public Health is an international peer-reviewed open access monthly 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 2500 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.