Webinar: Leveraging Big Data to Improve Traffic Incident Management (NCHRP 17-75)

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Start Date:

December 13, 2018 from 1:00 pm – 2:30 pm EST


As the era of “Big Data” is upon us, there is an overwhelming number of data sources to draw from to improve traffic incident management (TIM). Big Data is not just “a lot of data,” it is a fundamental change in how to collect, analyze, and use data to uncover trends and relationships. In general, advances in technology have significantly increased data quantity, improved data quality, and enhanced data analytics. There is an urgent need for transportation agencies to become fluent in these technologies and to successfully integrate them within their operations so that they may benefit from the large set of existing and emerging Big Data data sources and tools. Big Data holds the potential for leveraging the greatest return on investment in traffic incident management and associated public safety outcomes.

Click here to register for the webinar.

Learning Objectives:

Better understand how to prepare for and leverage Big Data.


Eileen Singleton, Principal Transportation Engineer, Baltimore Metropolitan Council
Kelley Pecheux – Director of Transportation Operations and Safety, AEM Corporation - Principal Investigator for the project

Benjamin Pecheux – Director of Information Research, AEM Corporation

Todd A. Leiss - Traffic Incident Management Coordinator, Pennsylvania Turnpike Commission

John Parker - Traffic Operations Project Manager, Pennsylvania Turnpike Commission

David Ward - Sap Business Intelligence Supervisor, Pennsylvania Turnpike Commission

Chris Lambert- Systems Consultant, Kentucky Transportation Cabinet

Target Audience:

Public and private transportation agencies that collect, analyze, or use TIM data. Consultants that support state and local transportation agencies with data management, analysis, and reporting.

Event Type:


Organizational Capability Element:

  • Traffic Incident Management

Operations Area of Practice:

  • Data Acquisition, Support and Hosting
  • Regional environmental data sets and models
  • Traffic Incident Management