{"id":{"repo_id":"alabama","oai_identifier":"oai:ir.ua.edu:123456789/7916"},"canonical_url":"https://search.dev.ndltd.org/etd/alabama/oai:ir.ua.edu:123456789/7916","repository":{"repo_id":"alabama","name":"University of Alabama","base_url":"https://ir-api.ua.edu/oai/request"},"display":{"title":"A study of infrastructural connectivity on a college campus: the case of the University of Alabama","abstract":"As the University of Alabama and the City of Tuscaloosa continue to undergo unprecedented growth, more students than ever need to commute to campus. While most students choose to drive to campus, this places stress on the University’s parking lots and development plans. In an attempt to combat that stress, the multimodal network infrastructure, was evaluated to identify the overall connectivity for student commuting. This evaluation was completed by using graph theory applications to gauge to overall connectivity of the sidewalk, bike lane, and bus route networks available to students at the University of Alabama. Through GIS mapping, relationships between these networks were identified, as well as gaps in these networks. Along with these graph theory metrics, a survey of student’s commuting patterns was performed to identify how students travel to campus and their overall familiarity with the alternative transportation networks. Together, this data was compiled to identify areas in which connectivity is limiting a student’s ability to commute to campus, either due to gaps in the network or lack of awareness of the network. These results were used to create policy recommendations which sought to improve connectivity metrics and overall mobility for students at the University of Alabama in an effort to combat the recent unprecedented growth.","abstract_html":"As the University of Alabama and the City of Tuscaloosa continue to undergo unprecedented growth, more students than ever need to commute to campus. While most students choose to drive to campus, this places stress on the University’s parking lots and development plans. In an attempt to combat that stress, the multimodal network infrastructure, was evaluated to identify the overall connectivity for student commuting. This evaluation was completed by using graph theory applications to gauge to overall connectivity of the sidewalk, bike lane, and bus route networks available to students at the University of Alabama. Through GIS mapping, relationships between these networks were identified, as well as gaps in these networks. Along with these graph theory metrics, a survey of student’s commuting patterns was performed to identify how students travel to campus and their overall familiarity with the alternative transportation networks. Together, this data was compiled to identify areas in which connectivity is limiting a student’s ability to commute to campus, either due to gaps in the network or lack of awareness of the network. 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