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<p>This paper proposes a corridor-based drone–carrier framework for last-mile urban delivery that explicitly minimizes environmental impact while improving logistics efficiency. Starting from a central warehouse, customer locations are first partitioned into clusters using the <i>k</i>-means algorithm, and a carrier vehicle transports multiple drones–each loaded with up to a specified number of packages and equipped with on-board charging–and sequentially pauses at optimized “corridor entrance” points. At each entrance, a drone departs along a corridor toward its assigned customer cluster. By confining drone trajectories within narrow corridors instead of allowing point-to-point flights, noise dispersion and ecological disturbances are substantially reduced, and airspace congestion is minimized. Within each cluster, the drone applies a nearest-neighbor heuristic followed by a refinement strategy to sequence deliveries, ensuring that battery endurance and payload constraints are respected. After completing its sortie, the drone returns along the same corridor to rendezvous with the moving carrier; if necessary, it may hover until the vehicle arrives. In alternative scenarios, temporary depot stations located near corridor entrances support battery recharging and package replenishment–thus avoiding unnecessary drone hovering and eliminating redundant carrier movement–further extending the operational range without detours into densely populated areas. We additionally quantify the environmental and spatial benefits of this strategy by introducing an airspace footprint metric that measures the total aerial area occupied by drone operations. Simulations on realistic urban instances show that the proposed corridor-based system achieves comparable mission times while reducing the overall airspace footprint by up to 48% relative to conventional single-depot point-to-point models. Overall, the results demonstrate that this approach not only lowers total travel distance and delivery time but also confines noise and emissions to narrow aerial corridors, fostering sustainable, community-friendly drone logistics.</p>

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A corridor-based drone-carrier vehicle system for environment-aware last-mile delivery

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月29日

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  • Falak Fatima,
  • P. B. Sujit,
  • Debasish Ghose

摘要

This paper proposes a corridor-based drone–carrier framework for last-mile urban delivery that explicitly minimizes environmental impact while improving logistics efficiency. Starting from a central warehouse, customer locations are first partitioned into clusters using the k-means algorithm, and a carrier vehicle transports multiple drones–each loaded with up to a specified number of packages and equipped with on-board charging–and sequentially pauses at optimized “corridor entrance” points. At each entrance, a drone departs along a corridor toward its assigned customer cluster. By confining drone trajectories within narrow corridors instead of allowing point-to-point flights, noise dispersion and ecological disturbances are substantially reduced, and airspace congestion is minimized. Within each cluster, the drone applies a nearest-neighbor heuristic followed by a refinement strategy to sequence deliveries, ensuring that battery endurance and payload constraints are respected. After completing its sortie, the drone returns along the same corridor to rendezvous with the moving carrier; if necessary, it may hover until the vehicle arrives. In alternative scenarios, temporary depot stations located near corridor entrances support battery recharging and package replenishment–thus avoiding unnecessary drone hovering and eliminating redundant carrier movement–further extending the operational range without detours into densely populated areas. We additionally quantify the environmental and spatial benefits of this strategy by introducing an airspace footprint metric that measures the total aerial area occupied by drone operations. Simulations on realistic urban instances show that the proposed corridor-based system achieves comparable mission times while reducing the overall airspace footprint by up to 48% relative to conventional single-depot point-to-point models. Overall, the results demonstrate that this approach not only lowers total travel distance and delivery time but also confines noise and emissions to narrow aerial corridors, fostering sustainable, community-friendly drone logistics.