Congestion-aware Bi-modal Delivery Systems Utilizing Drones

Mark Beliaev, Negar Mehr, Ramtin Pedarsani

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Bi-modal delivery systems are a promising solution to the challenges posed by the increasing demand of e-commerce. Due to the potential benefit drones can have on logistics networks such as delivery systems, some countries have taken steps towards integrating drones into their airspace. In this paper we aim to quantify this potential by developing a mathematical model for a Bi-modal delivery system composed of trucks and drones. We propose an optimization formulation that can be efficiently solved in order to design socially-optimal routing and allocation policies. We incorporate both societal cost in terms of road congestion and parcel delivery latency in our formulation. Our model is able to quantify the effect drones have on mitigating road congestion, and can solve for the path routing needed to minimize the chosen objective. To accurately capture the effect of stopping trucks on road latency, we model it using SUMO by simulating roads shared by trucks and cars. Based on this, we show that the proposed framework is computationally feasible to scale due to its reliance on convex quadratic optimization techniques.

Original languageEnglish (US)
Title of host publication2022 European Control Conference, ECC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9783907144077
StatePublished - 2022
Externally publishedYes
Event2022 European Control Conference, ECC 2022 - London, United Kingdom
Duration: Jul 12 2022Jul 15 2022

Publication series

Name2022 European Control Conference, ECC 2022


Conference2022 European Control Conference, ECC 2022
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems and Management
  • Control and Systems Engineering
  • Control and Optimization
  • Modeling and Simulation


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