• TRB 100th Annual Meeting

      January 24–28, 2021

    • Online Program


Annual Meeting Event Detail

Poster Session 1170

1170 - Mining Data Deeper to Understand Travel Behavior

Tuesday, January 26 11:30 AM- 1:00 PM ET
Patrick Coleman, AECOM,
Vincent Bernardin, Caliper Corporation

Sponsored by:
Standing Committee on Urban Transportation Data and Information Systems (AED20)

These presentations illustrate the wide range of applications of big data analytics to understand travel behavior and patterns. The applications include both international and U.S. studies, with analysis and insights on diverse topics including remote detection of illegal parking of e-scooters, the equity of developer impact fees, the route choice sets of taxis, origin-destination spatial patterns and repeated individual significant places, congestion, safety, and impacts of COVID-19 on travel.

No agenda available

Title Presentation Number
Interactive, Web-based Platform for “Big” Transportation Data Integration and Analytics
Xiaofan Shu, University of Missouri, Columbia
Yaw Adu-Gyamfi, University of Missouri, Columbia
Carlos Sun, University of Missouri, Columbia, Ellis Library
Praveen Edara, University of Missouri, Columbia
Show Abstract
Going the Extra Mile: Using Connected Vehicle Data to Study Commute Patterns in Relation to Impact Fees
Aisling O'Reilly (ashoreilly13@gmail.com), Civilitude
Daniel Hennessey, City of Austin (TX)
Jackson Archer, WGI
Show Abstract
Crowd-sourcing Micro-mobility Parking Violation Reporting – User Interface Design Motivation and Analytical Opportunities from Data Collected
Chintan Pathak (cp84@uw.edu), University of Washington
Borna Arabkhedri, University of Washington
Don Mackenzie, University of Washington
Show Abstract
A Big-Data Driven Approach to Analyzing and Modeling Human Mobility Trend under Non-Pharmaceutical Interventions during COVID-19 Pandemic
Songhua Hu, University of Maryland
Chenfeng Xiong (chenfeng.x@gmail.com), University of Maryland, College Park
Mofeng Yang
Hannah Younes, University of Maryland, College Park
Weiyu Luo, University of Maryland
Lei Zhang, University of Maryland, College Park
Show Abstract
Impacts of COVID-19 Pandemic on the Travel Behaviors of Free-Floating Electric Bike Sharing Service Users: An Unsupervised Learning Method
Seung Eun Choi, Yonsei University
Jinhee Kim (kim.jinhee@yonsei.ac.kr), Yonsei University
Dayoung Seo, Elecle
Yeonjin Cho, Elecle
Show Abstract
Mining Route Set Distribution Range And Affecting Factor Threshold Based On GPS Data
Yajuan Deng (yjdeng@chd.edu.cn), Chang'an University
Sang Yan, Chang'an University
Peng Zhang, China Design Group Co., Ltd.
Xianbiao Hu, Pennsylvania State University
Show Abstract
Using Big Data and Interactive Maps for Long-term and COVID-era Congestion Monitoring in San Francisco
Bhargava Sana, San Francisco County Transportation Authority (SFCTA)
Xu Zhang, Kentucky Transportation Cabinet
Joe Castiglione, San Francisco County Transportation Authority (SFCTA)
Mei Chen, Kentucky Transportation Center
Dr. Gregory Erhardt, University of Kentucky
Show Abstract
Micromobility Trip Origin and Destination Inference using General Bikeshare Feed Specification (GBFS) data
Yiming Xu (yiming.xu@ufl.edu), University of Florida
Xiang Yan, University of Florida
Virginia Sisiopiku, University of Alabama, Birmingham
Louis Merlin, Florida Atlantic University
Fangzhou Xing, Microsoft Corporation
Xilei Zhao, University of Florida
Show Abstract
Mining Vehicle Trajectories to Discover Individual Significant Places: Case Study Using Floating Car Data in the Paris Region
Danyang Sun, Ecole des Ponts ParisTech
Fabien Leurent, Ecole des Ponts ParisTech
Xiaoyan Xie, Ecole des Ponts ParisTech
Show Abstract

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