Abstract
dc:description.abstractAdvanced Air Mobility (AAM) is a rapidly emerging sector in the aerospace industry that seeks to revolutionize transportation by integrating highly automated aircraft into the airspace. As AAM technology matures, establishing a network framework and strategic hub locations becomes crucial for transitioning from theoretical models to practical applications in transportation systems. This thesis investigates community-based strategies for hub placement within the AAM infrastructure. More specifically, it utilizes network segmentation to decompose a network into communities to simplify the hub selection process into more manageable sub-problems. Our first contribution is the development of a specialized community detection methodology called Directed Flow Communities (DFC), which is designed to accommodate the attributes of transportation networks. Next, we conduct a case study using the Freight Analysis Framework (FAF) dataset as a proxy for AAM demand. The empirical investigation focuses on three key sectors: pharmaceuticals, electronics, and comprehensive freight flows, each presenting distinct challenges and insights into the network’s structure. The findings show the effectiveness of the community detection-based methods in unveiling cost-efficient hub locations.
Degree
thesis:*- Name thesis:degree_name
- Master
- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2024
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Chavalithumrong, Alissa
- Advisor dc:contributor.advisor
-
- Balakrishnan, Hamsa
Rights
dc:rights- Statement dc:rights
-
- Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
- Copyright retained by author(s)
- Licence dc:rights.uri
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/1721.1/155480
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/155480