Community detection on urban street networks : a segmentation model for urban logistics policy and planning
Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019
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| Бусад зохиолчид: | |
| Формат: | Дипломын ажил |
| Хэл сонгох: | eng |
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Massachusetts Institute of Technology
2019
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| Онлайн хандалт: | https://hdl.handle.net/1721.1/123238 |
| _version_ | 1826217201679466496 |
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| author | Wilson, Margaret Olivia. |
| author2 | Matthias Winkenbach and Yossi Sheffi. |
| author_facet | Matthias Winkenbach and Yossi Sheffi. Wilson, Margaret Olivia. |
| author_sort | Wilson, Margaret Olivia. |
| collection | MIT |
| description | Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019 |
| first_indexed | 2024-09-23T16:59:39Z |
| format | Thesis |
| id | mit-1721.1/123238 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T16:59:39Z |
| publishDate | 2019 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1232382019-12-14T03:01:05Z Community detection on urban street networks : a segmentation model for urban logistics policy and planning Wilson, Margaret Olivia. Matthias Winkenbach and Yossi Sheffi. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering. Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Civil and Environmental Engineering. Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019 Cataloged from PDF version of thesis. Includes bibliographical references (pages 81-86). 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. This ratio describes the magnitude of detour required by network conditions, which can offer a proxy for travel efficiency due to road network variations across a city. Using this metric, network-based partitioning algorithms are shown to produce sub-networks with internal travel conditions that are on average more efficient and less variable than sub-networks produced from extant methods of urban segmentation. This result is demonstrated on a wide variety of test networks in cities worldwide. In addition, a secondary use case as a decision-support tool for policymakers is proposed. Since this algorithm creates areas with a flexible spatial resolution in which boundaries are defined by infrastructure and geography, it may constitute a useful way to delineate areas where policy interventions should be employed. Because the impact and presence of freight traffic vary with local land uses (e.g., commercial, residential, industrial), the land use characteristics of these segments are also investigated to determine if network-based segmentation models capture more variation in land use characteristics than alternative methods. by Margaret Olivia Wilson. S.M. in Transportation S.M.inTransportation Massachusetts Institute of Technology, Department of Civil and Environmental Engineering 2019-12-13T18:53:40Z 2019-12-13T18:53:40Z 2019 2019 Thesis https://hdl.handle.net/1721.1/123238 1129597909 eng 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. http://dspace.mit.edu/handle/1721.1/7582 86 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Civil and Environmental Engineering. Wilson, Margaret Olivia. Community detection on urban street networks : a segmentation model for urban logistics policy and planning |
| title | Community detection on urban street networks : a segmentation model for urban logistics policy and planning |
| title_full | Community detection on urban street networks : a segmentation model for urban logistics policy and planning |
| title_fullStr | Community detection on urban street networks : a segmentation model for urban logistics policy and planning |
| title_full_unstemmed | Community detection on urban street networks : a segmentation model for urban logistics policy and planning |
| title_short | Community detection on urban street networks : a segmentation model for urban logistics policy and planning |
| title_sort | community detection on urban street networks a segmentation model for urban logistics policy and planning |
| topic | Civil and Environmental Engineering. |
| url | https://hdl.handle.net/1721.1/123238 |
| work_keys_str_mv | AT wilsonmargaretolivia communitydetectiononurbanstreetnetworksasegmentationmodelforurbanlogisticspolicyandplanning |