Special Issue "Promotion of Big Data and Intelligent Transportation to Traffic Safety and Environment"
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601).
Deadline for manuscript submissions: 31 December 2019
Dr. Feng Chen
College of Transportation Engineering, Tongji University, 1239 Siping Road, Shanghai, China
Phone: +86 021 6958 5721
Fax: +86 021 6958 3813
Interests: traffic injury prevention; statistical analysis of Crash Data; vehicle dynamic model; reliability analysis; driving simulator
Dr. Kun Xie
Department of Civil and Natural Resources Engineering, University of Canterbury, 20 Kirkwood Ave, Christchurch 8041, New Zealand
Website | E-Mail
Interests: transportation safety, connected and autonomous vehicles, big data analytics,statistics and machine learning, resilience in multimodal transportation systems
Dr. Xiaoxiang Ma
College of Transportation Engineering, Tongji University, 4800 Cao'an Road, Shanghai, China
Metropolitan areas face serious traffic-related problems. Road traffic accidents cause a large number of deaths and disabilities every day. Moreover, traffic congestion has been increasingly severe around the world, causing enormous pollutant emissions to degrade air quality. Both traffic accidents and vehicle pollutions have become major public health issues. The recent development of new technologies such as big data, automated driving, and connected vehicle and cooperative vehicle infrastructure systems show great potential to enhance traffic safety and mitigate traffic congestion. By harnessing the power of these emerging technologies, a better understanding of data-driven traffic systems can be achieved, which is of practical importance to traffic safety and traffic operation.
This Special Issue aims to report on recent advances in interdisciplinary research related to understanding associated risks and the improvement of traffic safety and environment problems in transportation networks around the world. It is open to any subject area of the related theme, and research articles encompassing multiple fields, such as big data, ITS, automated driving, connected vehicle, cooperative vehicle infrastructure systems, etc., are particularly welcome. The International Journal of Environmental Research and Public Health is indexed by SCI-E, PubMed, and other databases.
Dr. Feng Chen
Dr. Kun Xie
Dr. Xiaoxiang Ma
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 papers will be 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. International Journal of Environmental Research and Public Health 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 1800 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.
- big data and traffic safety
- big data and traffic environment
- intelligent transportation and traffic safety
- intelligent transportation and traffic environment
- automatic driving
- cooperative vehicle infrastructure system
- connected car