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Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering

The integration of cellular networks and vehicular networks is complex and heterogeneous. Synchronization among vehicles in heterogeneous vehicular clusters plays an important role in effective data sharing and the stability of the cluster. This synchronization depends on the smooth exchange of info...

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Main Authors: Ahmad, Iftikhar, Md Noor, Rafidah, Alroobaea, Roobaea, Talha, Muhammad, Ahmed, Zaheed, Habiba, Umm-e, Ali, Ihsan
Format: Article
Published: Wiley 2021
Subjects:
QA Mathematics
T Technology (General)
Online Access:http://eprints.um.edu.my/28635/
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spelling my.um.eprints.286352022-03-01T02:34:07Z http://eprints.um.edu.my/28635/ Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering Ahmad, Iftikhar Md Noor, Rafidah Alroobaea, Roobaea Talha, Muhammad Ahmed, Zaheed Habiba, Umm-e Ali, Ihsan QA Mathematics T Technology (General) The integration of cellular networks and vehicular networks is complex and heterogeneous. Synchronization among vehicles in heterogeneous vehicular clusters plays an important role in effective data sharing and the stability of the cluster. This synchronization depends on the smooth exchange of information between vehicles and remote servers over the Internet. The remote servers predict road traffic patterns by adopting deep learning methods to help drivers on the roads. At the same time, local data processing at the vehicular cluster level may increase the capabilities of remote servers. However, global positioning system (GPS) signal interruption, especially in the urban environment, plays a big part in the detritions of synchronization among the vehicles that lead to the instability of the cluster. Instability of connections is a major hurdle in developing cost-effective solutions for deriving assistance and route planning applications. To solve this problem, a self-localization scheme within the vehicular cluster is proposed. The proposed self-localization scheme handles GPS signal interruption to the vehicle within the cluster. A unique clustering criterion and a synchronization mechanism for sharing traffic information system (TIS) data among multiple vehicles are developed. The developed scheme is simulated and compared with existing known approaches. The results show the better performance of our proposed scheme over others. Wiley 2021-01-19 Article PeerReviewed Ahmad, Iftikhar and Md Noor, Rafidah and Alroobaea, Roobaea and Talha, Muhammad and Ahmed, Zaheed and Habiba, Umm-e and Ali, Ihsan (2021) Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering. Complexity, 2021. ISSN 1076-2787, DOI https://doi.org/10.1155/2021/6627539 <https://doi.org/10.1155/2021/6627539>. 10.1155/2021/6627539
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic QA Mathematics
T Technology (General)
spellingShingle QA Mathematics
T Technology (General)
Ahmad, Iftikhar
Md Noor, Rafidah
Alroobaea, Roobaea
Talha, Muhammad
Ahmed, Zaheed
Habiba, Umm-e
Ali, Ihsan
Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering
description The integration of cellular networks and vehicular networks is complex and heterogeneous. Synchronization among vehicles in heterogeneous vehicular clusters plays an important role in effective data sharing and the stability of the cluster. This synchronization depends on the smooth exchange of information between vehicles and remote servers over the Internet. The remote servers predict road traffic patterns by adopting deep learning methods to help drivers on the roads. At the same time, local data processing at the vehicular cluster level may increase the capabilities of remote servers. However, global positioning system (GPS) signal interruption, especially in the urban environment, plays a big part in the detritions of synchronization among the vehicles that lead to the instability of the cluster. Instability of connections is a major hurdle in developing cost-effective solutions for deriving assistance and route planning applications. To solve this problem, a self-localization scheme within the vehicular cluster is proposed. The proposed self-localization scheme handles GPS signal interruption to the vehicle within the cluster. A unique clustering criterion and a synchronization mechanism for sharing traffic information system (TIS) data among multiple vehicles are developed. The developed scheme is simulated and compared with existing known approaches. The results show the better performance of our proposed scheme over others.
format Article
author Ahmad, Iftikhar
Md Noor, Rafidah
Alroobaea, Roobaea
Talha, Muhammad
Ahmed, Zaheed
Habiba, Umm-e
Ali, Ihsan
author_facet Ahmad, Iftikhar
Md Noor, Rafidah
Alroobaea, Roobaea
Talha, Muhammad
Ahmed, Zaheed
Habiba, Umm-e
Ali, Ihsan
author_sort Ahmad, Iftikhar
title Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering
title_short Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering
title_full Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering
title_fullStr Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering
title_full_unstemmed Aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering
title_sort aiding traffic prediction servers through self-localization to increase stability in complex vehicular clustering
publisher Wiley
publishDate 2021
url http://eprints.um.edu.my/28635/
_version_ 1735409565738991616
score 13.223943

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