Toward Sustainable Last-Mile Deliveries: A Comparative Study of Energy Consumption and Delivery Time for Drone-Only and Drone-Aided Public Transport Approaches in Urban Areas

The increasing demand for fast and energy-efficient parcel deliveries driven by the growth of e-commerce has made drones an attractive option for urban freight. However, considering drones’ energy usage throughout the entire delivery process is essential when assessing their suitability. This research introduces an energy consumption model encompassing all flight stages—takeoff, flight, landing, hovering—simulating last-mile energy consumption within drone delivery-based systems. Additionally, it conducts a novel comparison between a system relying only on drones (Drone-only system) and a system combining drones with public transportation (Drone-APT system). The comparison considers factors such as consumer distribution, warehouse locations, and drone battery characteristics. The results, based on the real 3D structure of Barcelona, demonstrate that the Drone-APT system maintains consistent power consumption across different consumer distributions and warehouse locations. Conversely, the Drone-only system ensures consistent delivery times in these same scenarios. Furthermore, the Drone-APT improves energy efficiency, especially when direct drone delivery is limited by battery life. However, this efficiency improvement leads to increased delivery time due to the unpredictable timing of public transport vehicles. Striking a balance between drone energy consumption and delivery time is crucial, warranting further research to identify the most sustainable solution for last-mile delivery. This study offers valuable insights into the advantages and trade-offs associated with integrating drones and public transportation, laying the groundwork for future optimization efforts. Future work could incorporate intelligent technologies like machine learning to effectively address these trade-offs by dynamically optimizing drone paths based on energy efficiency and delivery time.