Research on the use and route of unmanned delivery car
Yifan Gou
Shanghai University of Engineering Scienc
DOI: https://doi.org/10.59429/esta.v12i4.12659
Keywords: unmanned delivery vehicles; path planning; dynamic scheduling; campus logistics
Abstract
This study addresses the "last mile" delivery challenge in campus environments by exploring the application and route planning of unmanned delivery vehicles. By analyzing the dense pedestrian flow and complex architectural features of campus environments, we developed a dynamic scheduling model integrating timetable data with a multi-sensor fusion positioning solution, while optimizing the Dijkstra algorithm for path planning. The research introduced solar-powered systems and redundant control mechanisms to enhance reliability, along with an optimized user interface based on ffeld surveys. Experimental results demonstrate that the improved algorithm reduces path length by 12.7%, increases efffciency by 27% during peak hours, and cuts operation time by 51%. In the future, we will explore air-land collaborative distribution and ethical norms to help build a smart logistics system on campus.
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