A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Multi-Criteria Coordinated Electric Vehicle-Drone Hybrid Delivery Service Planning
According to recent works, a coordinated delivery strategy in which terrestrial and aerial electric vehicles work together effectively improves delivery throughput and energy efficiency. However, most research on logistics and transportation focuses on delivery performance and does not care about energy efficiency, with three main limitations: 1. Most of these works ignore geographic information along the delivery route, while road slope is one of the most critical energy consumption components. 2. Vehicle and drone power consumption models are simplified as driving mileage, while the delivery time is a significant concern. 3. The battery model is simplified as a linear model even though practical batteries have non-linearity properties. This work proposes a framework to provide energy- and time-efficient delivery schedules with a hybrid delivery service with terrestrial and aerial electric vehicles. We first implement accurate electric van and drone power models and a battery model based on manufacturers' system specifications and experimental data. Then, we propose a heuristic delivery scheduling algorithm to determine the electric van and drone delivery schedule. We also introduce various cost functions to evaluate the delivery scheduling results regarding time, energy, the weighted sum of time and energy, and the economic model. The proposed framework is validated on randomly implemented delivery missions and delivery scenarios in existing cities. Results indicate that the coordinated delivery saves delivery costs up to 27.25% in terms of the economic model compared with the electric van-only delivery schedule.
Multi-Criteria Coordinated Electric Vehicle-Drone Hybrid Delivery Service Planning
According to recent works, a coordinated delivery strategy in which terrestrial and aerial electric vehicles work together effectively improves delivery throughput and energy efficiency. However, most research on logistics and transportation focuses on delivery performance and does not care about energy efficiency, with three main limitations: 1. Most of these works ignore geographic information along the delivery route, while road slope is one of the most critical energy consumption components. 2. Vehicle and drone power consumption models are simplified as driving mileage, while the delivery time is a significant concern. 3. The battery model is simplified as a linear model even though practical batteries have non-linearity properties. This work proposes a framework to provide energy- and time-efficient delivery schedules with a hybrid delivery service with terrestrial and aerial electric vehicles. We first implement accurate electric van and drone power models and a battery model based on manufacturers' system specifications and experimental data. Then, we propose a heuristic delivery scheduling algorithm to determine the electric van and drone delivery schedule. We also introduce various cost functions to evaluate the delivery scheduling results regarding time, energy, the weighted sum of time and energy, and the economic model. The proposed framework is validated on randomly implemented delivery missions and delivery scenarios in existing cities. Results indicate that the coordinated delivery saves delivery costs up to 27.25% in terms of the economic model compared with the electric van-only delivery schedule.
Multi-Criteria Coordinated Electric Vehicle-Drone Hybrid Delivery Service Planning
Young Hoo Cho (author) / Donkyu Baek (author) / Yukai Chen (author) / Min Jae Jung (author) / Sara Vinco (author) / Enrico Macii (author) / Massimo Poncino (author) / Hoo Cho, Young / Baek, Donkyu / Chen, Yukai
2023-01-01
Article (Journal)
Electronic Resource
English
DDC:
690
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