Review of data fusion methods for real-time and multi-sensor traffic flow analysis
Highway planning; Highway traffic control; Intelligent systems; Intelligent vehicle highway systems; Real time systems; Travel time; Data fusion methods; Decision level fusion; Feature level fusion; Intelligent transportation systems; Research and application; Testing and evaluation; Traffic control...
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Institute of Electrical and Electronics Engineers Inc.
2023
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my.uniten.dspace-265582023-05-29T17:11:56Z Review of data fusion methods for real-time and multi-sensor traffic flow analysis Kashinath S.A. Mostafa S.A. Mustapha A. Mahdin H. Lim D. Mahmoud M.A. Mohammed M.A. Al-Rimy B.A.S. Fudzee M.F.M. Yang T.J. 57222712288 37036085800 57200530694 35759460000 57222715023 55247787300 57192089894 57200494876 34971036200 57222713457 Highway planning; Highway traffic control; Intelligent systems; Intelligent vehicle highway systems; Real time systems; Travel time; Data fusion methods; Decision level fusion; Feature level fusion; Intelligent transportation systems; Research and application; Testing and evaluation; Traffic controllers; Traffic flow analysis; Sensor data fusion Recently, development in intelligent transportation systems (ITS) requires the input of various kinds of data in real-time and from multiple sources, which imposes additional research and application challenges. Ongoing studies on Data Fusion (DF) have produced significant improvement in ITS and manifested an enormous impact on its growth. This paper reviews the implementation of DF methods in ITS to facilitate traffic flow analysis (TFA) and solutions that entail the prediction of various traffic variables such as driving behavior, travel time, speed, density, incident, and traffic flow. It attempts to identify and discuss real-time and multi-sensor data sources that are used for various traffic domains, including road/highway management, traffic states estimation, and traffic controller optimization. Moreover, it attempts to associate abstractions of data level fusion, feature level fusion, and decision level fusion on DF methods to better understand the role of DF in TFA and ITS. Consequently, the main objective of this paper is to review DF methods used for real-time and multi-sensor (heterogeneous) TFA studies. The review outcomes are (i) a guideline of constructing DF methods which involve preprocessing, filtering, decision, and evaluation as core steps, (ii) a description of the recent DF algorithms or methods that adopt real-time and multi-sensor sources data and the impact of these data sources on the improvement of TFA, (iii) an examination of the testing and evaluation methodologies and the popular datasets and (iv) an identification of several research gaps, some current challenges, and new research trends. � 2013 IEEE. Final 2023-05-29T09:11:56Z 2023-05-29T09:11:56Z 2021 Review 10.1109/ACCESS.2021.3069770 2-s2.0-85103782712 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103782712&doi=10.1109%2fACCESS.2021.3069770&partnerID=40&md5=6a6594a5ec94d3973e3f529ac3015f60 https://irepository.uniten.edu.my/handle/123456789/26558 9 9389771 51258 51276 All Open Access, Gold Institute of Electrical and Electronics Engineers Inc. Scopus |
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| description |
Highway planning; Highway traffic control; Intelligent systems; Intelligent vehicle highway systems; Real time systems; Travel time; Data fusion methods; Decision level fusion; Feature level fusion; Intelligent transportation systems; Research and application; Testing and evaluation; Traffic controllers; Traffic flow analysis; Sensor data fusion |
| author2 |
57222712288 |
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57222712288 Kashinath S.A. Mostafa S.A. Mustapha A. Mahdin H. Lim D. Mahmoud M.A. Mohammed M.A. Al-Rimy B.A.S. Fudzee M.F.M. Yang T.J. |
| format |
Review |
| author |
Kashinath S.A. Mostafa S.A. Mustapha A. Mahdin H. Lim D. Mahmoud M.A. Mohammed M.A. Al-Rimy B.A.S. Fudzee M.F.M. Yang T.J. |
| spellingShingle |
Kashinath S.A. Mostafa S.A. Mustapha A. Mahdin H. Lim D. Mahmoud M.A. Mohammed M.A. Al-Rimy B.A.S. Fudzee M.F.M. Yang T.J. Review of data fusion methods for real-time and multi-sensor traffic flow analysis |
| author_sort |
Kashinath S.A. |
| title |
Review of data fusion methods for real-time and multi-sensor traffic flow analysis |
| title_short |
Review of data fusion methods for real-time and multi-sensor traffic flow analysis |
| title_full |
Review of data fusion methods for real-time and multi-sensor traffic flow analysis |
| title_fullStr |
Review of data fusion methods for real-time and multi-sensor traffic flow analysis |
| title_full_unstemmed |
Review of data fusion methods for real-time and multi-sensor traffic flow analysis |
| title_sort |
review of data fusion methods for real-time and multi-sensor traffic flow analysis |
| publisher |
Institute of Electrical and Electronics Engineers Inc. |
| publishDate |
2023 |
| _version_ |
1806425550829387776 |
| score |
13.211869 |