Aiding Traffic Prediction Servers through Self-Localization to Increase Stability in Complex Vehicular Clustering

Author:

Ahmad Iftikhar12ORCID,Md Noor Rafidah2ORCID,Alroobaea Roobaea3ORCID,Talha Muhammad4ORCID,Ahmed Zaheed5,Habiba Umm-e-5,Ali Ihsan2ORCID

Affiliation:

1. Department of CS and IT, Mirpur University of Science and Technology (MUST), Mirpur-10250, Azad Jammu and Kashmir (AJK), Pakistan

2. Department of Computer System and Technology, Faculty of Computer Science and Information Technology, University of Malaya, Kuala Lumpur 50603, Malaysia

3. Department of Computer Science, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif 21944, Saudi Arabia

4. Deanship of Scientific Research, King Saud University, Riyadh, Saudi Arabia

5. Faculty of Computing & Engineering, University of Kotli, Azad Jammu and Kashmir (AJK), Pakistan

Abstract

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.

Funder

Taif University

Publisher

Hindawi Limited

Subject

Multidisciplinary,General Computer Science

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