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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Analysis of Autonomous Buses impact on transportation between Stockholm’s universities

Urtasun López, Marc January 2019 (has links)
The city of Stockholm is developing fast and its population is strongly growing,new solutions for urban mobility must be found. Implementations in the publictransport network are needed and the use of automated buses is a present topicfor efficient and sustainable transportation. The Vetenskapsstaden area has threeof the main university campus coexisting, this leads to a generation of campusto-campus trips which creates an impact in the Stockholm’s public transport.The unique environment and singular users arise the aim to execute a potentialsolution to release ridership from the public transport network. This thesisanalyzes and evaluates whether a new automated bus line is needed or not inthe studied area. A cost model will study the proposed solutions through therated decision variables: frequency and capacity, commercial speed and differentrates of demand. The relative efficiency of the proposed implementations isstudied compared with the costs of the current public transport modes used inthe area. Numerical analysis and results are given for two different scenarios:implementing one bus line connecting the three campuses or three lines betweencampuses. The former scenario shows to be more sensitive to the studied variablesand presents higher costs whereas the second-option costs have a robust responseand lower overall price evaluation. For both infrastructure models, the rateof demand is crucial to evaluate the advantages of a potential solution. Theestablished method and criteria contributes to a better understanding of theimpact of autonomous buses to low-demand analytic models.

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