Vehicle Path Planning Based on Genetic Algorithm in Intelligent Transportation System

This study addresses the critical issue of vehicle path planning in the context of an Intelligent Transportation System (ITS) by harnessing the power of Genetic Algorithm (GA) optimization. As transportation systems face escalating challenges, the use of intelligent solutions becomes imperative. The rise of big data has catalyzed the development of intelligent transportation systems, where the use of advanced technologies enables improved efficiency and safety. Intelligent vehicle path planning, a cornerstone of ITS, is explored in depth in this study. A comprehensive review of related literature underscores the importance of path planning algorithms and highlights recent advances and breakthroughs. The proposed model integrates GA with quantum technology to improve search efficiency and solution quality. Through careful experimentation and analysis, the effectiveness of the GA optimization process is demonstrated, showing its ability to navigate complex road networks while minimizing travel time and risk. Simulation results highlight the robustness and adaptability of the proposed approach, paving the way for future research in this area.