An Analysis on Tradable Permit Models for Last-Mile Delivery Drones
| Autor: | Vitor Venceslau Curtis, Marcos R. O. A. Maximo, Johnny Cardoso Marques, Elton F. Sbruzzi, Cesar Augusto Cavalheiro Marcondes, Lourenço Alves Pereira Júnior, Filipe Alves Neto Verri, Denis S. Loubach |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Complex systems General Computer Science Operations research Computer science UAV air traffic management (ATM) Context (language use) 02 engineering and technology Atmospheric model 020901 industrial engineering & automation drones Flight dynamics 0502 economics and business last-mile delivery (LMD) General Materials Science tradable permit model (TPM) Resilience (network) 050210 logistics & transportation SIMPLE (military communications protocol) 05 social sciences General Engineering simulation Drone Last mile lcsh:Electrical engineering. Electronics. Nuclear engineering Airspace class lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 8, Pp 186279-186290 (2020) |
| ISSN: | 2169-3536 |
| Popis: | Drones can play a game-changing role in reducing both cost and time in the context of last-mile deliveries. This paper addresses the last-mile delivery problem from a complex system viewpoint, where the collective performance of the drones is investigated. We consider a last-mile delivery system with a tradable permit model (TPM) for airspace use. Typically, in other research works regarding last-mile delivery drones, a fully cooperative centralized scenario is contemplated. In our approach, due to the TPM, the agents (i.e. drones) need to compete for airspace permits in a distributed manner. We simulate the system and evaluate how different parameters, such as the arrival rate and airspace dimensions, impact the system behavior in terms of the cost and time needed by the drones to acquire flight permits, and the airspace utilization. We use a simplified simulation model, where the agents' strategies are naïve, and the drones' flight dynamics are not accounted for. Nevertheless, the simulation's level of detail is adequate for capturing interesting properties from the agents' collective behavior, as our results support. The obtained results show that the system's performance is satisfactory, even with naïve agents and under high traffic conditions. Moreover, a real-world implementation of our competitive decentralized approach would lead to advantages, such as fast permit transactions, simple computational infrastructures, and error resilience. |
| Databáze: | OpenAIRE |
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