Analysis of urban mobility in South Florida using Uber Movement. Issue 4 (December 2020)

• Record Type: Journal Article
• Authors: Roy, Shouraseni Sen; Perlman, Jane; Balling, Robert C.
• Is Part Of: Case studies on transport policy. Volume 8:Issue 4(2020)
• Page Start: 1393
• Page End: 1400
• Publication Date: 2020-12
• Subjects: Ridesharing -- Uber Movement -- South Florida -- Spatial analysis; Transportation and state -- Case studies -- Periodicals; Transportation -- Planning -- Case studies -- Periodicals; Transportation -- Research -- Case studies -- Periodicals; 388.05
• DOI: 10.1016/j.cstp.2020.10.003
• Languages: English
• ISSNs: 2213-624X

Abstract

Highlights: Number of trips were higher on weekdays for both sources and destinations. Distinct spatial clustering along major thoroughfares and the two main airports. The main thoroughfares overlap with the two modes of mass transit. Most riders use mass transit to the closest station, and use Uber to destination. Abstract: Ridesharing services linked to mobile devices are increasingly playing a major role in human mobility in urban areas. With the recent release of Uber Movement data for certain large cities it is now possible to analyze urban mobility at finer spatial scales. In the present study, we used aggregate Uber trip data from 2016 to 2019 for the Miami metropolitan area. The peak hour of Uber trips and mean travel times were calculated using harmonic analysis. The total number of trips were expectedly higher on the weekdays compared to weekends for both sources and destinations. In addition, there was a distinct spatial clustering along major thoroughfares connecting the entire study area from north to south, and the two main airports of the study area, Miami International Airport and Fort Lauderdale Hollywood International Airport. The main thoroughfares along which the Uber trips were clustered also overlap with the two modes of mass transit, metro rail and Tri Rail. This is indicative of most riders using mass transit to the closest station of their destination, and then using Uber as a connection to the location of interest. The results of our study will be useful for urban planning and better understanding of human mobility across the metropolitan area.