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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01x059c995s
Title: ANALYZING GTFS DATA TO STUDY THE POTENTIAL FOR AN AUTONOMOUS RIDE SHARING TRANSIT NETWORK IN NAIROBI, KENYA.
Authors: Manyara, Kevin
Advisors: Kornhauser, Alain L.
Department: Operations Research and Financial Engineering
Class Year: 2017
Abstract: With the recent technological advancements in smartphones, mobile applications, and GPS, ridesharing has been leveraged, commercialized and popularized by companies such as Uber, Lyft and Didi Chuxing as a transit feature with high potential for reducing energy consumption, automobile carbon emissions, urban traffic congestion and overall trips. Ridesharing increases transit efficiency by ensuring that vehicle empty seats are taken up by passengers travelling to similar destinations. The future of ridesharing, however, is closely tied to the development of on-demand autonomous cars. Currently the public road testing of advanced level 2 to level 4 autonomous ridesharing vehicles by companies such as Uber, Google, GM and Ford are being done is cities such as San Francisco, California and Las Vegas, with the potential of implementation into these cities within the next decade. The research, development, andpromise for the introduction of autonomous public ridesharing vehicles has, however, mostly been limited to large cities in developed countries with advanced road transit infrastructures. In contrast, developing countries such as Kenya are still grappling with the challenge of poor transit systems for both passengers and freight, and as such, any prospects of future introduction of autonomous ridesharing systems are upset by the prioritization of developing, or improving current transit networks. The slow-paced development of efficient modern transit networks across all modes will surely slow down any progress of introducing large scale autonomous ridesharing systems. This thesis studies the current road transit system in Nairobi,Kenya, paying attention to population mobility demand, modal split, spatiotemporal factors, road safety and systemic challenges with the aim of uncovering the opportunities of introducing an autonomous ridesharing public road transit system. Considering that more than 70% of passenger mobility in Nairobi is through road transit, an autonomous ride sharing public road transit system will not only increase road safety due to advanced accident avoidance technologies, but also add efficiency to the most popular mode of public transit which for decades has been blamed for the city’s high accident statistics and traffic jams.
URI: http://arks.princeton.edu/ark:/88435/dsp01x059c995s
Type of Material: Princeton University Senior Theses
Language: en_US
Appears in Collections:Operations Research and Financial Engineering, 2000-2020

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