MONTATER MUHSNHASAN,GULNOZ MUROTOVA ,DR R. UDAYAKUMAR
DOI: https://doi.org/The modern context of the transport infrastructure is witnessing the adoption of Intelligent Transportation Systems (ITS). These systems have enabled real-time decision-making and intelligent mobility in conjunction with vehicle infrastructure systems. Urgent applications, such as Autonomous Vehicle Maneuvering, Automated Collision Emergency Alerts, Real-time video surveillance, and Dynamic Signal Control (DSC), require unparalleled communication speed and maximum processing power. Failure to resolve these issues will impede the prevention of road perils, massive traffic blockages in densely populated areas, and disruption of urban life. Addressing the minimal attainable delay, tailoring individual requirements, is another obstacle that needs to be addressed in the highly volatile network, with stochastic traffic conditions, on-board processing capabilities, and numerous other technical constraints. The goal of this research work is to provide an in-depth analysis of a structure that aims to resolve these constraints through driving scenarios, subject to limitations about the available technology and the extreme requirements of latency. A new integrated framework is presented to address these issues by incorporating edge computing, adaptive data packet prioritization, and contemporary communication protocols, which facilitate prompt communication among vehicles connected to the network. Through system architecture, process flow diagrams, and calculations with defined latency for severe delay conditions, heuristic analytical simulations that employ realistic vehicular datasets validate the framework's capability for improved delay refinement, marking an enhancement over existing methodologies. Furthermore, the Austro control structures for urban traffic management systems validate the frameworks from a practical standpoint. Research indicates that managing the sensitivity of delays to an appropriate level is attainable and highly beneficial for the development of future vehicle networks.
