Resource Allocation in V2X Environment

Abstract

With the growing number of vehicles on the road and the increased need for efficient transportation systems, optimising traffic efficiency has become an essential component of smart cities. This article gives a complete analysis on enhancing traffic efficiency in V2X (Vehicle-to-Everything) communication through optimised channel allocation. Our project's goal was to address the difficulties of urban traffic congestion and limited resources by intelligently distributing communication channels to cars. To properly distribute channels, we suggested an enhanced optimisation approach based on the Elitist Genetic approach (EGA). The performance of the algorithm was compared to random channel allocation schemes, and the findings showed considerable increases in traffic efficiency in terms of maximized throughput, sum rate and channel gain. Our research findings lead to the development of intelligent transportation systems, which improve traffic management and overall traffic flow. This work presents a comprehensive study on EGA-based channel allocation in V2X communication and highlights its effectiveness in improving traffic efficiency. The findings from this project have practical implications for traffic management and can aid in the development of intelligent transportation systems in traffic-affected areas. Future research can explore the scalability and real-world implementation of EGA-based channel allocation algorithms to further enhance traffic efficiency and alleviate congestion in urban environments.