Efficient route planning for overhead transmission lines is crucial for reducing construction costs, ensuring operational safety, and improving environmental adaptability. Traditional algorithms such as Dijkstra and rapidly-exploring random tree (RRT) demonstrate certain advantages in finding feasible paths or exploring complex terrain features, yet they still suffer from issues including excessive turning angles, high terrain undulation sensitivity, and suboptimal overall path smoothness. To address these limitations, this paper proposes an improved A*-based route planning method that incorporates a multi-source constraint cost function that simultaneously considers path length, terrain undulation, number of crossings through risk areas, and turning angle. Simulation results indicate that the proposed method achieves a more balanced optimization effect among multiple metrics. Comparative experiments based on four different cost function methods demonstrate that Method D (the final proposed method) provides optimal performance with a path length of 5482 m, an average terrain undulation of 1.9 m, six crossings, and the lowest turning angle of 51.8°. Further compared with Dijkstra and RRT, the improved A* method reduces the total turning angle by 28.6% and 46.5%, respectively, while maintaining a competitive path length and minimizing cross-terrain risk. Overall, the proposed method improves route smoothness and environmental adaptability while ensuring routing feasibility, which verifies its applicability for intelligent transmission line planning and offers references for engineering practice.
Chen et al. (Wed,) studied this question.