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Transportation network companies (TNCs) such as Uber and Lyft have grown tremendously over the last decade, particularly in the San Francisco Bay Area. Nonetheless, relatively little publicly available data exist about the users of these services, their travel behaviors, volume of use, the times and locations of TNC trips, and how TNC services are affecting transportation system performance overall. This paper describes the methods and descriptive results of the first large-scale smartphone-based TNC user survey conducted in the California Bay Area in the fall 2018 and spring of 2019.
This study analyzes the relation between shared mobility services and greenhouse gases (GHGs) emissions by using a nationally representative sample of US young adults. We conduct a comprehensive analysis based on the data collected in the 2017 National Household Travel Survey (NHTS).
Shared micro-mobility services are rapidly expanding yet little is known about travel behaviour. Understanding mode choice, in particular, is quintessential for incorporating micro-mobility into transport simulations in order to enable effective transport planning. We contribute by collecting a large dataset with matching GPS tracks, booking data and survey data for more than 500 travellers, and by estimating a first choice model between eight transport modes, including shared e-scooters, shared e-bikes, personal e-scooters and personal e-bikes.
Technology-enhanced bikeshare features a dockless system with GPS-tracked electric bikes and a mobile app. As an additional transportation mode, it offers users greater accessibility and more flexibility compared to traditional bikeshare. This paper examines the causal impact of a tech-enhanced bikeshare program on public transit ridership, using evidence from a mid-sized metropolitan area in the Midwest of the United States.
Urbanism Next Center Director and Professor Nico Larco testified during the congressional hearing, "The Road Ahead for Automated Vehicles." Professor Larco highlighted the work of Urbanism Next and the potential cascading impacts of autonomous vehicles.
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