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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01dz010s497
Title: EFFECTIVE AUTONOMOUS TRANSPORTATION: CREATING A FINANCIALLY AND LOGISTICALLY PLAUSIBLE AUTONOMOUS VEHICLE SOLUTION FOR NEW JERSEY
Authors: Okafor, Sylvia
Advisors: Kornhauser, Alain
Department: Operations Research and Financial Engineering
Class Year: 2016
Abstract: Real-time ridesharing is an amenity that arranges shared rides, by matching drivers and riders on extremely short notice. Like carpooling, dynamic ridesharing makes use of empty seats in passenger cars, lowering the number of cars on the road along with fuel consumption and transportation costs. Many technology companies, like Uber and Lyft, have capitalized on this novel idea by combining dynamic ridesharing with technological advances, such as: GPS navigation, smartphones, and social networks. Yet, one has to wonder if there is a market for real-time ridesharing to make use of another recent technological advancement: autonomous vehicles. Autonomous vehicles are cars that function just like traditional cars; however, they operate independent from human input. This thesis seeks to explore the demand for ridesharing in New Jersey, in an attempt to understand the potential impact autonomous taxis (ATs) on the number of daily trips people make and real-time ridesharing in general. It will design a feasible and flexible AT system for all the counties in New Jersey and simulate the system against synthesized travel behavior of NJ residents. It will also discuss easily implementable empty-vehicle repositioning (EVR) policies, different performance level requirements, and potential management/pricing models in order to further the efficiency of the proposed system. Overall, this thesis should highlight feasible and optimal policies for managing AT systems in New Jersey.
Extent: 46 pages
URI: http://arks.princeton.edu/ark:/88435/dsp01dz010s497
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2016

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