High quality data for transportation safety planning has been expensive and slow to obtain. Recently, new big data sources allow more detailed analysis of vehicle, transit, bicycle, and pedestrian trips than ever before. However, big data generally represents transactions rather than trips–inherently including a range of biases related to representation. Big data sources offer both prospect and problems for transportation planning, regarding how well they reflect the broad population of transportation system users, or individual markets subject to digital divide and other biases of representation. Research has identified far-reaching bias issues in big data sources, but this study will focus on those with an impact to planning for transportation safety. Using a synthetic literature review, and interviews with expert practitioners, Results suggest implications for transportation safety research and practice to identify and mitigate bias in big data.
Webinar (ppt): Griffin, G. (2018, June 26). “What do the Experts Do? Insights from Interviews & Literature to Deal with Bias in Big Data.” In Conversations about Counting: Big Data – Implications for Bicycle and Pedestrian Traffic Analysis, Webinar Presentation to the Transportation Research Board Bicycle and Pedestrian Data Subcommittee.
Student Impact Statement (pdf): Two students were funded under this project (PhD student Greg Griffin from TTI and Master’s student Meg Mulhall from UT). This file contains a statement of the impact this project made on these students’ education and workforce development.
Griffin, G. P., Mulhall, M., Simek, C., and Riggs, W. W. (2019) Mitigating Bias in Big Data for Transportation. Proceedings of the Transportation Research Board 98th Annual Meeting, No. 19-03196. Washington, D.C., Transportation Research Board. (Presented)
This project contributed to the following master’s thesis or Ph.D. dissertations:
The final dataset for this project is located in the Safe-D Collection on the VTTI Dataverse; DOI: 10.15787/VTT1/KRTX66
Start Date: 2017-08-01
End Date: 2018-05-31
Grant Number: 69A3551747115
Total Funding: $21,761
Source Organization: Safe-D National UTC
Project Number: 02-026
Planning for Safety
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Texas A&M University
Texas A&M Transportation Institute
College Station, Texas 77843-3135