Abstract: Complex terrains such as deep pits and high slopes in open-pit mines cause physical signal blockage and multipath fading. Furthermore, existing path-planning algorithms tend to result in unstable vehicle trajectories or congestion due to local optima, leading to low efficiency in open-pit mine vehicle scheduling. To address these issues, an intelligent vehicle scheduling method for open-pit mines based on 5G antenna and improved Dijkstra algorithm was proposed. At the communication level, based on a biconical antenna model, an L-shaped radiating stub was loaded, and rectangular and L-shaped slots were etched on the radiating patch to optimize current distribution, thereby forming an onboard dual-band omnidirectional dipole antenna. This antenna achieved coverage in the 2.3–2.7 GHz and 4.8–4.9 GHz dual frequency bands, solving the problems of signal blockage and attenuation caused by deep pits and high slopes in mining areas. At the path-planning level, depth-first search and a "container array" mechanism were introduced into the traditional Dijkstra algorithm. By recording all potential predecessor information of nodes, global path backtracking and optimal selection were realized, improving the smoothness of planned paths. Experimental results showed that the dual-band omnidirectional dipole antenna achieved a signal coverage rate of 81.2% in areas with severe signal blockage such as deep pits and high slopes, with an average signal strength of −94 dBm, outperforming traditional commercial 5G antennas. Compared with the Dijkstra algorithm, A^* algorithm, and Rapidly-exploring Random Tree (RRT) algorithm, the improved Dijkstra algorithm planned paths with shorter distance, fewer inflection points, and smoother trajectories. Moreover, in multi-vehicle cooperative transportation scenarios, it exhibited lower path conflict rate and shorter path-replanning response time. In actual open-pit mine vehicle scheduling, compared with the production-completion method, earliest-loading method, and traffic-flow planning method, the proposed method effectively reduced vehicle waiting time and shortened loaded travel distance, and performed optimally in terms of single-shift total output, empty-haul rate, and scheduling-command response delay.