Abstract This study evaluates how various UAV flight policies affect energy consumption and the required charging infrastructure in last-mile parcel delivery applications. International UAV policies are reviewed and subcategorized into nine categories based on their stringency. Assuming autonomous operations of small-size quadrotor UAVs (13 min flight range), an experimentally verified energy model and demand data are used to simulate 3D trajectories of UAV missions in a digital-twin model, simulating last-mile parcel deliveries in Toronto. A novel optimization model is developed to minimize the allocated charging stations. The results show that the maximum and minimum altitude limitations increase the required charging stations by up to 52%. Minimum horizontal clearing distance increases the required charging stations by up to 75%. The results highlight increased cost per parcel delivery associated with policy strictness ranging from $0.078 (lean policies) to $0.086 (strict policies). Overall, the results highlight the need for contextual-based policy solutions.

Highlights • International UAV flight regulations are synthesized and classified into nine policy permutations. • Last-mile parcel delivery for Toronto City is simulated for autonomous quadrotor UAVs. • A novel optimization model is developed to minimize the required charging stations based on policy permutations. • There are 5536 daily demand points, necessitating 26 to 58 landing stations. • UAV policy strictness approximately triples the required number of charging stations. • UAV policy strictness severely impacts the required number of charging sites (up to 223% increase). • Horizontal clearing distance is more impactful than altitude limitations. • However, the impact of UAV policies on energy consumption and cost per parcel is marginal (up to an 8% increase).