A new parcel delivery system with drones and a public train

Hailong Huang, Andrey V. Savkin, Chao Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

In this paper, we propose a new parcel delivery system consisting of a public train and drones. The train, an already existing mobile platform in our neighbourhood, follows its normal predefined route and timetable to transport passengers. In the meanwhile, some parcels to be delivered to some customers and a delivery drone are stored on its roof. The drone can launch from the train, deliver the parcel to a customer, and return to the train. It can also travel with the train and replace its battery on the roof via an automatic battery swap system. As the parcel delivery system cannot manage the movement of the train, the route and the timetable of the train need to be accounted carefully to schedule the deliveries. We formulate an optimization problem to minimize the total delivery time of a given set of parcels, and we propose two algorithms. Though the exact algorithm gives the optimal schedule, its computational complexity is exponential to the number of parcels. To make the proposed system possible to be implemented in practice, a suboptimal algorithm is developed, which is more efficient than the exact algorithm and can achieve close performance with the exact algorithm. Additionally, we propose a simple but effective strategy to deal with the uncertainty associated with the train’s timetable. Moreover, the proposed algorithm for the single drone case is modified to deal with the multiple drone case. The effectiveness of the proposed algorithms is verified via computer simulations and comparison with existing methods. The results show that the presented approach is more cost-efficient than the Truck only scheme and the Truck plus Drone scheme. Moreover, the parcel delivery time can be reduced and the delivery area can be enlarged compared to the scheme using drones only.
Original languageEnglish
Article number2020
Pages (from-to)1341-1354
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Volume100
DOIs
Publication statusPublished - 25 Jun 2020

Cite this