It is clear that to take advantage of the vast amount of data available to transportation safety analysts, now and in the near future, it is necessary to develop tools to handle and analyze data in an efficient manner. With that in mind, this research program employs an informatics approach, which considers how transportation safety datasets are best accessed and ingested and how they can be rapidly processed using a distributed parallel architecture. The research design will produce an analytic framework that looks to the future and provides system extensibility to facilitate the incorporation of new sources of data as they become available, while also considering future data-mining opportunities. This research will create a flexible tool that can be used to integrate and analyze disparate data sources such as current structured crash datasets, as well as natural language, social media, and sensor-type data. In addition, the informatics approach utilized in this program will ensure that researchers in the field have user-friendly tools to query features and events of interest. This research program provides a vision of how the proposed transportation research informatics platform (TRIP) can be used to integrate disparate, structured, and unstructured data sets to transform transportation systems and safety research.

Goals:

• Understand the potential sources of massive data to generate novel information for transportation safety research.
• Develop a transportation safety informatics platform that can combine and query massive datasets, including the strategic highway research program 2 naturalistic driving study data.
• Demonstrate how the informatics-based platform can enable safety analysts and researchers to develop new insights using the available massive transportation datasets.

• Exploratory Advanced Research

• FY 2002-2022 / Exploratory Advanced Research