3-5: Using Disaggregate Vehicle Data to Investigate How Transit Accessibility Influences the Use of Ride-Hailing Services and Personal Vehicles
|Principal Investigator||Daniel Chatman|
|Final Report (DOI)||Available Soon|
|Policy Brief||Available Soon|
This project will benefit current practice by being the first study to explore the influence of ride-hailing services on vehicle use across levels of transit access through a population comprehensive analysis of changes occurring in the use patterns of individual vehicles as Uber launched in Massachusetts. In contrast to previous research which has relied primarily upon surveys or scenario modeling, the proposed study uses data that can more directly measure whether access to TNCs, or access to both TNCs and public transit, affect the use of individual personal vehicles by analyzing changes in individual vehicle VMT as recorded in the Massachusetts Vehicle Census (MAVC). The MAVC includes annual odometer readings from every vehicle inspection in Massachusetts between the years 2009 to 2014 (and eventually to 2020). Each record is associated with a VIN number and a registered storage location, allowing researchers to track changes in vehicle use across time and with regards to transit access and the distance between transit nodes and where each vehicle is stored. To our knowledge, this will be the first study looking at TNCs relationship with vehicle use and transit access to focus on changes occurring in individual vehicles. By comparing changes in the average daily VMT of individual vehicles across levels of transit access and Uber availability as Uber rolled out in the Boston area, this study will be the first to explore at the individual vehicle level the nascent effects of the introduction of TNC services to a large American metropolis with an established transit network.TNCs/taxis from other modes (e.g., public transportation) if they feel unsafe waiting for the next bus or train or vice versa. As such, understanding safety-related concerns and their impacts on TNC/taxi travel behavior is complex and may vary depending on the context. Additionally, strategies may be needed to improve the perceived and actual safety of female drivers. More research is needed to better understand these concerns and to identify potential strategies that make TNCs/taxis more equitable across gender lines. This project proposes to employ a combination of methods based on grounded theory and narrative/discourse analysis in the U.S. Through qualitative and quantitative research, this study will collect data on women traveler and women driver views, values, and perceptions around TNC/taxi safety. The intent of the qualitative engagements is not to rank priorities per se but to seek a deeper understanding of issues as participants understand them and build critical group understanding. These engagements will be analyzed using thematic content analysis tools, such as ATLAS.ti to help systemically analyze complex phenomena hidden in unstructured data. The study will also deploy a TNC/taxi driver and user survey focused on women in the U.S. This study will inform how TNC/taxi travel behavior varies by gender, factors that contribute to heavy and light TNC/taxi use, and potential strategies that help overcome gender-specific concerns such safety in both drivers and travelers.