The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Comparison of energy demands of drone-based and ground-based parcel delivery services
Abstract
Abstract Drones are one of the most intensively studied technologies in logistics in recent years. They combine technological features matching current trends in transport industry and society like autonomy, flexibility, and agility. Among the various concepts for using drones in logistics, parcel delivery is one of the most popular application scenarios. Companies like Amazon test drones particularly for last-mile delivery intending to achieve both reducing total cost and increasing customer satisfaction by fast deliveries. As drones are electric vehicles, they are also often claimed to be an eco-friendly mean of transportation. In this paper an energy consumption model for drones is proposed to describe the energy demand for drone deliveries depending on environmental conditions and the flight pattern. The model is used to simulate the energy demand of a stationary parcel delivery system which serves a set customers from a depot. The energy consumed by drones is compared to the energy demand of Diesel trucks and electric trucks serving the same customers from the same depot. The results indicate that switching to a solely drone-based parcel delivery system is not worthwhile from an energetic perspective in most scenarios. A stationary drone-based parcel delivery system requires more energy than a truck-based parcel delivery system particularly in urban areas where customer density is high and truck tours are comparatively short. In rather rural settings with long distances between customers, a drone-based parcel delivery system creates an energy demand comparable to a parcel delivery system with electric trucks provided environmental conditions are moderate.
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Citations
Cites
The Traveling salesman problem: a computational study
(2007) · Choice Reviews Online · doi:10.5860/choice.45-0928 · Cited by 1,726
The flying sidekick traveling salesman problem: Optimization of drone-assisted parcel delivery
Murray, C. C., & Chu, A. G. (2015) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2015.03.005 · Cited by 1,715
Bektaş, T., & Laporte, G. (2011) · Transportation Research Part B: Methodological · doi:10.1016/j.trb.2011.02.004 · Cited by 1,219
Well-to-Wheels Analysis of Future Automotive Fuels and Powertrains in the European Context
Edwards, R., Mahieu, V., Griesemann, J.-C., Larivé, J.-F., & Rickeard, D. J. (2004) · SAE Technical Paper Series · doi:10.4271/2004-01-1924 · Cited by 1,036
Optimization Approaches for the Traveling Salesman Problem with Drone
Agatz, N., Bouman, P., & Schmidt, M. (2018) · Transportation Science · doi:10.1287/trsc.2017.0791 · Cited by 1,029
Otto, A., Agatz, N., Campbell, J., Golden, B., & Pesch, E. (2018) · Networks · doi:10.1002/net.21818 · Cited by 985 · cited 1×
“Otto et al. (2018) provides an extensive overview about civil applications of UAVs.”
BackgroundA review of recent research on green road freight transportation
Demir, E., Bektaş, T., & Laporte, G. (2014) · European Journal of Operational Research · doi:10.1016/j.ejor.2013.12.033 · Cited by 772
On the min-cost Traveling Salesman Problem with Drone
Ha, Q. M., Deville, Y., Pham, Q. D., & Hà, M. H. (2018) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2017.11.015 · Cited by 622
Routing a mixed fleet of electric and conventional vehicles
Goeke, D., & Schneider, M. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.01.049 · Cited by 607
The multiple flying sidekicks traveling salesman problem: Parcel delivery with multiple drones
Murray, C. C., & Raj, R. (2020) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2019.11.003 · Cited by 575
Cited by
ElSayed, M., Foda, A., & Mohamed, M. (2024) · Transport Policy · doi:10.1016/j.tranpol.2023.10.002 · Cited by 19
Grote, M., Oakey, A., Pilko, A., Krol, J., Blakesley, A., Cherrett, T., Scanlan, J., Anvari, B., & Martinez-Sykora, A. (2025) · International Journal of Sustainable Transportation · doi:10.1080/15568318.2025.2564851 · Cited by 5
Metadata
- Authors
- Kirschstein, T.
- Venue
- Transportation Research Part D: Transport and Environment
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 78
- Pages
- 102209
- ISSN
- 1361-9209 (ISSN-L)
- OpenAlex
- W2996999140
- Cited by
- 264
- References
- 36
- FWCI
- 12.64
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
