Comparison of light rail streetcar against shared autonomous vehicle fleet for Brooklyn–Queens connector in New York City

Lucas Mestres Mendes, Manel Rivera Bennàssar, Joseph Ying Jun Chow

Research output: Contribution to journalArticle

Abstract

Policy makers predict that autonomous vehicles will have significant market penetration in the next decade or so. In several simulation studies shared autonomous vehicle fleets have been shown to be effective public transit alternatives. This study compared the effectiveness of a shared autonomous vehicle fleet with an upcoming transit project proposed in New York City, the Brooklyn–Queens Connector light rail project. The study developed an event-based simulation model to compare the performance of the shared autonomous vehicle system with the light rail system under the same demand patterns, route alignment, and operating speeds. The simulation experiments revealed that a shared autonomous vehicle fleet of 500 vehicles of 12-person capacity (consistent with the EZ10 vehicle) would be needed to match the 39-vehicle light rail system if operated as a fixed-route system. However, as a demand-responsive system, a fleet of only 150 vehicles would lead to the same total travel time (22 min) as the 39-vehicle fleet light rail system. Furthermore, a fleet of 450 12-person vehicles in a demand-responsive operation would have the same average wait times while reducing total travel times by 36%. The implications for system resiliency, idle vehicle allocation, and vehicle modularity are discussed.

Original languageEnglish (US)
Pages (from-to)142-151
Number of pages10
JournalTransportation Research Record
Volume2650
Issue number1
DOIs
StatePublished - Jan 1 2017

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ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering

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Comparison of light rail streetcar against shared autonomous vehicle fleet for Brooklyn–Queens connector in New York City. / Mendes, Lucas Mestres; Bennàssar, Manel Rivera; Chow, Joseph Ying Jun.

In: Transportation Research Record, Vol. 2650, No. 1, 01.01.2017, p. 142-151.

Research output: Contribution to journalArticle

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