Urban Vehicular Networks: Real-Time Intersection-Based Segment Aware Allocation: An Important and Complex Method
摘要
Intelligent as well as responsive solutions are required in the field of autonomous automobile navigation due to the growing problems posed by dynamic traffic conditions. This paper presents STARVAN, an advanced navigation system designed to meet the complex requirements of contemporary traffic scenarios. STARVAN stands for Smart Traffic-Aware Responding Vehicle Autonomous Navigation. Through the integration of dynamic decision-making and real-time traffic monitoring, STARVAN goes beyond traditional planning of paths and avoids obstacles. By focusing on proactive response to traffic circumstances and taking motivation on the inadequacies of current systems, STARVAN offers a paradigm change toward greater independence and dependability in automobile navigation. This study represents a major breakthrough in automobile navigation technology by demonstrating the superiority of STARVAN with regard to of adaptability, effectiveness, and reliability through thorough simulations and quantitative assessments.