Incorporating Big Data in an Activity-Based Travel Model: The Chattanooga Case Study

Passively collected anonymous cell-phone based origin-destination data was incorporated in the spatial choice models of an activity-based modeling system developed for the Chattanooga-Hamilton County-North Georgia Transportation Planning Organization. This is believed to be the first time such “big data” has been incorporated in an activity-based modeling system. The process used the cell-phone based data in conjunction with data on commuting flows from the Census Bureau to develop district level origin-destination constants for inclusion in the utility functions of the spatial choice models. In this initial application, the constants were developed iteratively using shadow pricing techniques by minimizing error versus the big data sources, holding fixed the other utility function parameters originally estimated from household survey data. The process successfully significantly improved the ability of the spatial choice models to reproduce the travel patterns observed in the big data and contributed to good overall model validation against traffic counts and transit ridership. The resulting model combines the accuracy of big data and the sensitivity of activity-based models to produce a travel model that is both grounded in a rich behavioral framework and data driven, leveraging the large sample size and relative completeness of spatial big data.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADB50 Standing Committee on Transportation Planning Applications. Alternative title: Incorporating Big Data in an Activity-Based Travel Model: The Chattanooga Experience.
• Authors:
  • Bernardin, Vincent L
  • Bowman, John L
  • Bradley, Mark
  • Chen, Jason
  • Ferdous, Nazneen
  • Lee, Yuen
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 14p

Subject/Index Terms

• TRT Terms: Case studies; Metropolitan planning organizations; Origin and destination; Spatial analysis; Travel patterns
• Identifier Terms: Chattanooga-Hamilton County/North Georgia Transportation Planning Organization
• Uncontrolled Terms: Activity based modeling; Big data
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01663015
• Record Type: Publication
• Report/Paper Numbers: 18-03725
• Files: TRIS, TRB, ATRI
• Created Date: Mar 20 2018 5:04PM