| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Electronics and Electrical Engineering | 289 | 27 | 45 | 13 |
| Computer Science | 390 | 62 | 77 | 15 |
| Engineering and Technology | 522 | 35 | 62 | 16 |
The journal aims to foster the development of research in Intelligent transportation system, Transport engineering, Artificial intelligence, Simulation and Real-time computing. In Iet Intelligent Transport Systems, Computer network, Data mining and Traffic flow are investigated in conjunction with one another to address concerns in Intelligent transportation system research. The research on Computer network featured in Iet Intelligent Transport Systems combines topics in other fields like Wireless ad hoc network and Vehicular ad hoc network.
Public transport is a focus of the Transport engineering works in it. Topics in Artificial intelligence explored in Iet Intelligent Transport Systems were investigated in conjunction with research in Machine learning, Computer vision and Pattern recognition. It investigates Feature extraction research which frequently intersects with Contextual image classification.
The journal publications tackle a plethora of topics, such as Intelligent transportation system, Artificial intelligence, Transport engineering, Simulation and Computer vision. While work presented in the most cited papers provide substantial information on Intelligent transportation system, it also covers topics in Distributed computing, Floating car data, Traffic flow, Computer network and Traffic congestion. The journal articles hold forums on Artificial intelligence that merge themes from other disciplines such as Machine learning and Pattern recognition.
The journal focuses largely on the fields of Artificial intelligence, Automotive engineering, Real-time computing, Computer network and Control theory. The concepts on Artificial intelligence presented in the journal can also apply to other research fields, including Machine learning, Pedestrian, Computer vision and Pattern recognition. The Automotive engineering study tackled is a key component of adjacent topics in the area of Energy consumption.
Studies on Real-time computing discussed in the journal link to the field of Intelligent transportation system. Computer network research presented in Iet Intelligent Transport Systems encompasses a variety of subjects, including Wireless communication systems and Vehicular ad hoc network. Motion (physics) and Control (management), Platoon are some topics wherein Control theory research discussed in Iet Intelligent Transport Systems have an impact.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Iet Intelligent Transport Systems (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Iet Intelligent Transport Systems (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 1.59% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 32.26% were posted by at least one author from the top 10 institutions publishing in the journal. Another 12.10% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 16.13% of all publications and 39.52% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Jingliang Duan;Shengbo Eben Li;Yang Guan;Qi Sun
(2020)Rayson Laroca;Luiz A. Zanlorensi;Gabriel Resende Gonçalves;Eduardo Todt
(2021)Mohammad Rokonuzzaman;Navid Mohajer;Saeid Nahavandi;Shady Mohamed
(2021)Praveen Kumar Reddy Maddikunta;Gautam Srivastava;Thippa Reddy Gadekallu;Natarajan Deepa
(2020)Xiao Liang;Xingru Qu;Ning Wang;Rubo Zhang
(2020)Wei Liu;Lu Xiong;Xin Xia;Yishi Lu
(2020)Alfred Daniel;Karthik Subburathinam;Bala Anand Muthu;Newlin Rajkumar
(2020)Zhenzhong Chu;Bo Sun;Daqi Zhu;Mingjun Zhang
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