Transportation Research Part C: Emerging Technologies

Transportation Research Part C: Emerging Technologies - ISSN 0968-090X
Source Normalized Impact per Paper (SNIP): 3.547 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 3.185 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 8.089 (2020) Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
5 Year Impact Factor: 8.795 (2020) Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
Volumes: Volume 12
Issues: 12 issues
ISSN: 0968090X
Editor-in-Chief: Geroliminis

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The focus of Transportation Research: Part C (TR_C) is high-quality, scholarly research that addresses development, applications, and implications, in the field of transportation systems and emerging technologies . The interest is not in the individual technologies per se, but in their ultimate implications for the planning, design, operation, control, maintenance and rehabilitation of transportation systems, services and components. In other words, the intellectual core of the journal is on the transportation side, not on the technology side. The integration of quantitative methods from fields such as operations research, control systems, complex networks, computer science, artificial intelligence are encouraged.

Of particular interest are the impacts of emerging technologies on transportation system performance, in terms of monitoring, efficiency, safety, reliability, resource consumption and the environment. Submissions in the following areas of transportation are welcome: multimodal and intermodal transportation; on-demand transport; intelligent transportation systems; traffic and demand management; real-time operations; connected and autonomous vehicles; logistics; railways; resource and infrastructure management; aviation; pedestrians and soft modes.

Special emphasis is given in open science initiatives and promoting the opening of large-scale datasets for papers published in TR_C that can support transferability and benchmarking of different approaches. The realization of data opportunities that arise from emerging technologies and new sensors in transportation can revolutionize how this data reshape our understanding of congestion mechanisms and can contribute in efficient and sustainable mobility management.