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Title: Drone Deliveries Optimization with Battery Energy Constraints
Accession Number: 01658352
Record Type: Component
Abstract: Drone deliveries have been tested by private companies around the world. With advanced safety and reliability features, such as automated flight and sense-and-avoid technology to prevent collisions, it appears that deliveries by drone will soon be practical. This paper deals with an automated drone delivery system, rather than cooperative delivery by drones and trucks. The study assumes that a drone can lift multiple packages within its maximum payload and serve recipients in a service area of given radius. Battery capacities, the primary energy sources for drone operation, are analyzed to relate parcel payloads and flight ranges. Numerical analysis is used to optimize the drone fleet size for a service area, by minimizing the total costs of the delivery system. Four variables are explored to show the sensitivity of system outputs to input parameters: working period, drone operating speed, demand density of service area, and battery capacity. Extended daily working periods are shown to benefit both service providers and users. Increased drone operating speed reduces the overall costs; however, it increases operating and investment costs for suppliers. The study indicates that drone deliveries are more economical in areas with high demand densities and quantifies how improvements in battery capacity can reduce the number of drones satisfying all demands in a service area.
Supplemental Notes: This paper was sponsored by TRB committee AV060 Standing Committee on Airfield and Airspace Capacity and Delay.
Report/Paper Numbers: 18-02726
Language: English
Authors: Choi, YoungminSchonfeld, Paul MPagination: 15p
Publication Date: 2018
Conference:
Transportation Research Board 97th Annual Meeting
Location:
Washington DC, United States Media Type: Digital/other
Features: Figures; Photos; References; Tables
TRT Terms: Subject Areas: Aviation; Energy; Planning and Forecasting; Vehicles and Equipment
Source Data: Transportation Research Board Annual Meeting 2018 Paper #18-02726
Files: TRIS, TRB, ATRI
Created Date: Jan 8 2018 10:39AM
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