Optimal control of a hybrid UAV/train parcel delivery system

Hailong Huang, Andrey V. Savkin, Chao Huang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)


This paper presents a novel parcel delivery system consisting of an unmanned aerial vehicle (UAV) and a public train. The train moves along a fixed route following a predefined timetable and carries a set of parcels. The UAV departs from the train, delivers a parcel to a customer, returns to the train, and picks another parcel. The UAV can also travel with the train and replace the battery on the roof of it. Since the train is not controlled by the parcel delivery system, its timetable should be taken into account to efficiently deliver parcels. An optimal control problem is formulated with the objective of minimizing the total delivery time and a suboptimal algorithm is developed, which is computationally efficient. A case study is conducted to evaluate the proposed algorithm and compare it with existing schemes. The proposed approach is more cost efficient than the Truck only scheme and the Truck plus UAV scheme, since there is no cost associated with the truck. Moreover, it improves delivery time and covers a larger area compare to the UAV only delivery scheme.

Original languageEnglish
Title of host publicationProceedings of the 38th Chinese Control Conference, CCC 2019
EditorsMinyue Fu, Jian Sun
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)9789881563972
Publication statusPublished - Jul 2019
Externally publishedYes
Event38th Chinese Control Conference, CCC 2019 - Guangzhou, China
Duration: 27 Jul 201930 Jul 2019

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927


Conference38th Chinese Control Conference, CCC 2019


  • Control of delivery systems
  • Parcel delivery
  • Unmanned aerial vehicles

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modelling and Simulation


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