Authors: Yuchuan Huang*, University of Minnesota - Minneapolis, Ying Song, University of Minnesota - Minneapolis
Topics: Transportation Geography, Temporal GIS, Geographic Information Science and Systems
Keywords: bike sharing, public transit, spatiotemporal database, spatio-temporal analysis, data mining
Session Type: Paper
Start / End Time: 5:00 PM / 6:40 PM
Room: Capital Room, Omni, Lobby Level
Presentation File: No File Uploaded
Public transit offers many socioeconomic and environmental benefits but a significant barrier for many people wanting to travel by bus or train is the so-called “first/last-mile problem”. The emergence of bike sharing systems promises to bridge this first/last-mile and increase the use of transit. However, it is simply unknown whether bike sharing can help transit, or whether it may instead compete with transit by offering people a way to avoid the waiting time entirely. Recent research has examined the spatial relationships between bike sharing and transit but has ignored important temporal aspects, that is, the timing of bike sharing reservation and transit boarding and alighting. This paper develops novel methods for investigating the spatiotemporal relationships between bike sharing and public transit systems. We build a new spatiotemporal database using bike sharing transactions from Nice Ride Minnesota and automated passenger counter (APC) data from Metro Transit. We investigate the competitive and complimentary relationships between bike sharing and transit ridership through spatio-temporal analysis and data mining.