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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp017s75dg22w
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DC FieldValueLanguage
dc.contributor.advisorKornhauser, Alain-
dc.contributor.authorBao, Larry-
dc.date.accessioned2019-08-16T13:05:43Z-
dc.date.available2019-08-16T13:05:43Z-
dc.date.created2019-04-16-
dc.date.issued2019-08-16-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp017s75dg22w-
dc.description.abstractAutonomous vehicles have developed at an incredible pace, and society must prepare for the inevitable adoption of autonomous taxis as the primary mode of transportation. Self-driving cars will change existing transportation systems as individual car ownership becomes unnecessary. Autonomous ridesharing will become the norm, with tremendous environmental and social benefi ts. Ridesharing allows for fewer total vehicle miles traveled and higher average vehicle occupancy, especially when coupled with other forms of transportation such as airplanes and transit. Using a data set of synthesized vehicle travel demand for the United States and various adjustable parameters, this thesis analyzes the nationwide potential for reducing vehicle miles traveled of car trips by using autonomous taxi trips with other modes of transportation, including walking, transit, and flight. Using a multi-modal model with autonomous taxis, ridesharing holds enormous potential for drastically increasing nationwide AVO for the United States and substantially reducing greenhouse gas emissions.en_US
dc.format.mimetypeapplication/pdf-
dc.language.isoenen_US
dc.titleRidesharing and Autonomous Taxis: Analysis of a Multi-Modal Transportation Demand Modelen_US
dc.typePrinceton University Senior Theses-
pu.date.classyear2019en_US
pu.departmentOperations Research and Financial Engineering*
pu.pdf.coverpageSeniorThesisCoverPage-
pu.contributor.authorid961191533-
pu.certificateApplications of Computing Programen_US
pu.certificateFinance Programen_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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