Title:
Optimal Siting of Sub-Urban Air Mobility (sUAM) Ground Architectures using Network Flow Formulation

dc.contributor.author Venkatesh, Nikhil
dc.contributor.author Payan, Alexia P.
dc.contributor.author Justin, Cedric Y.
dc.contributor.author Kee, Ethan C.
dc.contributor.author Mavris, Dimitri N.
dc.contributor.corporatename Georgia Institute of Technology. Aerospace Systems Design Laboratory en_US
dc.contributor.corporatename American Institute of Aeronautics and Astronautics
dc.contributor.corporatename Georgia Institute of Technology. Aerospace Systems Design Laboratory
dc.date.accessioned 2020-06-15T13:27:47Z
dc.date.available 2020-06-15T13:27:47Z
dc.date.issued 2020-06
dc.description Presented at AIAA Aviation 2020 Forum en_US
dc.description.abstract Air Mobility (AM) operating models have steadily made their way into public conscience over the past decade due to increased research activity pioneered by large technology corporations such as Uber and Amazon. Estimates concur that there are around 250 startup businesses with 22 major players working on such technologies with over $25 billion dollars in venture capital funding in 2017[1]. Given the meteoric rise of Air Mobility as one of the leading 21st century disruptive technologies, research effort across the spectrum of functions that can make AM concepts a reality are burgeoning - ranging from vehicle design to operations planning. More specifically, research efforts within the operations planning space deal with service route identification, ground infrastructure (such as charging stations and ports) placement and others. To this effect, the present study seeks to evaluate the feasibility and tractability of a formalized optimization method towards the siting of "vertiports" - ground infrastructure that aids the embarkation and disembarkation of AM commuters - as applied to a Sub-Urban Air Mobility (sUAM) operating model. Mixed-Integer Programming (MIP) formulations offer qualified benefits over other heuristic methods and the authors are confident of their relative performance given the proven track record of such methods in solving generalized facility location problems (GFLP). In this study, two optimization problems were considered: capacitated vertiport siting, where any vertiport considered would need to adhere to capacity constraints; and uncapacitated vertiport siting, where any vertiport considered does not have any capacity limit and can service unlimited demand. Results indicate that a network flow formulation using an MIP methodology is able to adequately place vertiports for sUAM business operations to satisfy demand flows associated with home-work commute. en_US
dc.identifier.citation Venkatesh, N., Payan, A. P., Justin, C. Y., Kee, E., & Mavris, D. (2020). Optimal Siting of Sub-Urban Air Mobility (sUAM) Ground Architectures using Network Flow Formulation. In AIAA AVIATION 2020 FORUM. American Institute of Aeronautics and Astronautics. https://doi.org/10.2514/6.2020-2921 en_US
dc.identifier.doi 10.2514/6.2020-2921 en_US
dc.identifier.uri http://hdl.handle.net/1853/62914
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.publisher Georgia Institute of Technology
dc.publisher.original American Institute of Aeronautics and Astronautics (AIAA)
dc.relation.ispartofseries ASDL; en_US
dc.subject Urban air mobility en_US
dc.subject Network optimization en_US
dc.title Optimal Siting of Sub-Urban Air Mobility (sUAM) Ground Architectures using Network Flow Formulation en_US
dc.type Text
dc.type.genre Paper
dspace.entity.type Publication
local.contributor.author Payan, Alexia P.
local.contributor.author Mavris, Dimitri N.
local.contributor.corporatename Daniel Guggenheim School of Aerospace Engineering
local.contributor.corporatename Aerospace Systems Design Laboratory (ASDL)
local.contributor.corporatename College of Engineering
relation.isAuthorOfPublication 955c440c-fd29-4eb9-9923-a7e13f12667e
relation.isAuthorOfPublication d355c865-c3df-4bfe-8328-24541ea04f62
relation.isOrgUnitOfPublication a348b767-ea7e-4789-af1f-1f1d5925fb65
relation.isOrgUnitOfPublication a8736075-ffb0-4c28-aa40-2160181ead8c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Venkatesh_Aviation2020_Final.pdf
Size:
5.76 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
3.13 KB
Format:
Item-specific license agreed upon to submission
Description: