Graph Analytics and Optimization Methods for Insights from the Uber Movement Data

Conference · Sun Aug 18 04:00:00 EDT 2019

OSTI ID:1574471

Visweswara Sathanur, Arun ^[1]; Amatya, Vinay C. ^[1]; Khan, Md Ariful H. ^[1]; Rallo Moya, Roberto J. ^[1]; Maass, Kelsey L. ^[1]

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1. BATTELLE (PACIFIC NW LAB)

In this work we leverage the Uber movement dataset for the Los Angeles (LA) area where partial TAZ to TAZ (Traffic Analysis Zone) trip time data is available. We first create a TAZ-TAZ network based on nearest neighbors and propose a model that allows us to complete the $(O-D)$ (Origin-Destination) travel time matrix, using optimization methods such as non-negative least squares. We apply these algorithms for several communities in the TAZ-TAZ network and present insights in the form of completed $(O-D)$ matrices and associated temporal trends. We qualify the error performance and scalability of our flows. We conclude by pointing out the directions in our ongoing work to improve the quality and scale of travel time estimation.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1574471
• Report Number(s): PNNL-SA-146172
• Country of Publication: United States
• Language: English