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Abstract:
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Recent technological advances have enabled transportation researchers to collect large amounts of driving data from participants in naturalistic driving studies. These include highly identifying data on the research participants such as geospatial data (trip traces), face video and other information that can be combined to identify participants. The data, including identifying data, have high value to researchers in safety, traffic engineering, planning, modeling and many other fields. However, U.S. federal regulations and international policy and guidelines require the protection of research participant identity. This talk will discuss lessons learned from the SHRP2 Naturalistic Driving Study and other such studies conducted at Virginia Tech as to how to make such data widely available to researchers around the world while still protecting participant privacy and adhering to the promises made when they enrolled in these studies. The use of online repositories for non-identifying data and the use of secure data enclaves for identifying data will be discussed, as well as considerations for international collaborations.
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