Community detection on urban street networks : a segmentation model for urban logistics policy and planning

This thesis considers the community detection methods employed by network studies in a wide variety of contexts and adapts their use to the segmentation of an urban street network. In order to form partitions of urban street networks that are manageable as delivery territories or similar units of spatial aggregation, e.g., discrete demand zones, to be used in a study of urban freight distribution, extant community detection methods are assessed and adapted. Numerical experiments demonstrate that the sub-networks formed by these partitions display travel properties that make them a useful model for logistics transportation, especially in contexts where continuum approximation methods might be employed. The ratio of simulated trip distances over the actual road network to the idealized distance between the trip endpoints is used as a metric to quantify some travel properties of these segments.

Name thesis:degree_name

Master

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Civil and Environmental Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2019

Author dc:creator

• Wilson, Margaret Olivia.

Advisor dc:contributor.advisor

• Matthias Winkenbach and Yossi Sheffi.

• Civil and Environmental Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

https://hdl.handle.net/1721.1/123238

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/123238