Ulvi Rafizade; Matin Mammadli

doi:10.36074/grail-of-science.21.08.2026.015

SYNERGY OF ARTIFICIAL INTELLIGENCE AND NETWORK INFRASTRUCTURE IN MODERN AUTOMOTIVE CONTROL AND TRAFFIC SYSTEMS

Authors

Ulvi Rafizade Odlar Yurdu University, Azerbaijan; Azerbaijan Technological University, Azerbaijan https://orcid.org/0009-0009-6005-897X
Matin Mammadli Odlar Yurdu University, Azerbaijan https://orcid.org/0009-0007-2170-6992

DOI:

https://doi.org/10.36074/grail-of-science.21.08.2026.015

Keywords:

Automotive Control Systems, Traffic Control Systems, Network Connectivity, Artificial Intelligence (AI), Power over Ethernet (PoE), V2X Communication, Time-Sensitive Networking (TSN), Intelligent Transportation Systems (ITS)

Summary

The integration of network connectivity within traffic control systems, when combined with the capabilities of automotive control frameworks, represents a fundamental shift in modern intelligent transportation networks. By fusing artificial intelligence algorithms with high-performance industrial networking solutions—such as Power over Ethernet (PoE), V2X communication architectures, and Time-Sensitive Networking (TSN)—the automotive and traffic sectors can overcome critical operational silos. Traditionally, components such as traffic signals, V2X data streams, incident response logs, and public transit records have operated in isolation, preventing unified corridor coordination and transit prioritization. Furthermore, the absence of real-time multi-source data integration deprives control centers of critical situational awareness during congestion or emergency events, while data loss impedes the deployment of predictive analytics.

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