International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Artificial Intelligence Based Traffic Control for Edge Computing Assisted Vehicle Networks |
|---|---|
| ABSTRACT | Edge computing supported vehicle networks have attracted considerable attention in recent years both from industry and academia due to their extensive applications in urban traffic control systems. We present a general overview of Artificial Intelligence (AI)-based traffic control approaches which focuses mainly on dynamic traffic control via edge computing devices. A collaborative edge computing network embedded in the AI-based traffic control system is proposed to process the massive data from roadside sensors to shorten the real-time response time, which supports efficient traffic control and maximizes the utilization of computing resources in terms of incident levels associated with different rescue schemes. Furthermore, several open research issues and indicated future directions are discussed. |
| AUTHOR | SUDEEP HONGAL, TARUN M, PRANAM SWAMY DJ, SUDARSHAN TS, DR MALATESH SH Student, Dept. of Computer Science and Engineering, MS Engineering College, Bengaluru, Karnataka, India HOD, Dept. of Computer Science and Engineering, MS Engineering College, Bengaluru, Karnataka, India |
| VOLUME | 180 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1401027 |
| pdf/27_Artificial Intelligence Based Traffic Control for Edge Computing Assisted Vehicle Networks.pdf | |
| KEYWORDS | |
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