Big Data Approaches for Traffic Incident Management
NCHRP's "Application of Big Data Approaches for Traffic Incident Management" applies the guidelines presented in Research Report 904 "Leveraging Big Data to Improve Traffic Incident Management" to validate the feasibility and value of the big data approach for Traffic Incident Management (TIM) among transportation and other responder agencies.
Big data is evolving and maturing rapidly, and much attention has been focused on the opportunities that big data may provide state DOTs in managing their transportation networks. Using big data could help state and local transportation officials achieve system reliability and safety goals, among others.
However, challenges for DOTs include how to use the data and in what situations, such as how and when to access data, identify staff resources to prepare and maintain data, or integrate data into new/existing tools for analysis.
Supplemental to the report are Appendix A – P, which detail findings from traditional and big data sources for the TIM use cases.
Who is NCHRP?
The National Cooperative Highway Research Program conducts research in problem areas that affect highway planning, design, construction, operation, and maintenance in the United States.
Administered under the Transportation Research Board (TRB), NCHRP is a collaborative effort between the Federal Highway Administration (FHWA) and the National Academy of Sciences.
Traffic Incident Management
TIM is the planned and coordinated multi-disciplinary process to detect, respond to, and clear traffic incidents so that traffic flow may be restored as safely and quickly as possible.
Effective TIM reduces the duration and impacts of traffic incidents; improves the safety of motorists, crash victims, and emergency responders; and reduces the frequency of secondary crashes.
