Ant colony algorithm-based path planning for drone cargo transportation in remote areas

Shen Liu; Yong Zeng; Xiaobo Xu; Yafei Wang

doi:10.1117/12.3054606

20 December 2024 Ant colony algorithm-based path planning for drone cargo transportation in remote areas

Shen Liu, Yong Zeng, Xiaobo Xu, Yafei Wang

Author Affiliations +

Proceedings Volume 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024); 134215U (2024) https://doi.org/10.1117/12.3054606
Event: Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 2024, Dalian, China

Abstract

The transportation conditions in remote areas are relatively average. In conventional transportation methods, transport vehicles have high requirements for the smoothness of roads, which causes inconvenience to the flow efficiency of goods. To solve the problem of goods transportation in remote areas, drones are applied to deliver goods. A path planning model is established with the objective function of minimizing the total delivery time. Ant colony algorithm is used for optimization and calculation. Based on standard calculation examples, the results show that drone delivery can reflect time advantages and meet the relevant needs of goods transportation effectiveness and feasibility in remote areas.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Shen Liu, Yong Zeng, Xiaobo Xu, and Yafei Wang "Ant colony algorithm-based path planning for drone cargo transportation in remote areas", Proc. SPIE 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 134215U (20 December 2024); https://doi.org/10.1117/12.3054606

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