CO2 emissions and delivery time of last-mile drone delivery using trucks

被引:6
作者
Hur, Sung Ho [1 ]
Won, Minsu [2 ,3 ]
机构
[1] Seoul Natl Univ, Grad Sch Environm Studies, Seoul, South Korea
[2] Korea Transport Inst KOTI, Dept Transport Big Data, Sejong, South Korea
[3] 370 Sicheong Daero, Sejong Si 30147, South Korea
关键词
air transportation; cooperative systems; emission; freight; logistics; vehicle routing; GENETIC ALGORITHM; VEHICLE; SUSTAINABILITY; IMPACT;
D O I
10.1049/itr2.12437
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The shift in consumer behaviour from in-person to online shopping has led to an increase in parcel delivery volume and its associated negative impacts, such as CO2 emissions in cities. With the emergence of drone-delivery technologies, the authors analyzed a joint delivery method using drones and trucks, which is an emerging alternative solution for last-mile delivery in terms of CO2 emissions and delivery time. The analysis verified the highest possible level of reduction in CO2 emissions for the simultaneous and strategic operation of drones and trucks compared to diesel- or electric-only truck operations. Moreover, this approach leads to reduced delivery times. A sensitivity analysis was performed to optimize the delivery-drone flight performance in a drone-and-truck delivery strategy. It was found that a 1.5-km drone flight performance was sufficient when considering the reasonable assumptions adopted in this study. Furthermore, based on the analysis results, drone-and-truck cooperative delivery strategies may not provide a significant advantage in terms of CO2 emissions compared with alternative transportation modes, such as fuel-cell trucks with sufficiently low emissions. It has been empirically verified that changes in CO2 emissions are proportional to the number of clusters. However, there is a risk of local optima due to microscopic fluctuations among neighbouring cluster numbers, which occurs during the search for the optimal number of clusters.
引用
收藏
页码:101 / 113
页数:13
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