Performance Analysis of Energy-Efficient Path Planning for Sustainable Transportation

Optimizing path planning for energy efficiency is critical for achieving sustainable vehicular transportation. This paper presents a novel framework for evaluating the impact of path planning algorithms (PPAs) on energy consumption within a simulated environment. We leverage the CARLA simulator to conduct a comparative analysis between the widely used A* and a Hybrid Genetic Algorithm (HGA) across diverse vehicular scenarios. This investigation aims to quantify the influence of PPA selection on vehicle energy expenditure, enabling data-driven optimization for energy minimization. We leverage an offline energy estimation model to further streamline the comparison of the two PPAs. Extensive simulations are employed to demonstrate the efficiency and adaptability of the proposed framework. The findings contribute to the development of energy-efficient path-planning strategies, promoting advancements toward sustainable transportation systems.