As the nation enters the era of “Big Data” there is an overwhelming number of data sources to draw from to improve traffic incident management. 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, recent advances in transportation data technology have significantly increased data quantity, improved data quality, and enhanced data analytics. Recognizing the tremendous potential of transportation and non-transportation applications to collect and record traffic incident management data, many agencies are faced with the challenge of using or even identifying the rich datasets that could be used to analyze traffic incident management efforts. There is a need to develop tools for the management of Big Data in traffic flow information from multiple data sources. Big Data holds the potential for leveraging the greatest return on investment in traffic incident management and associated public safety outcomes. Big Data offers opportunities to bring multiple, comprehensive datasets together to derive useful information and relationships that could improve Traffic Incident Management agencies’ efforts to reduce clearance times and increase highway safety. The ability to mine information on heretofore unanticipated trends can provide significant opportunities for improving protocols, resource management, scene management, and real-time data sharing. The challenge is to discover datasets, uncover relationships, and identify trends that may occur outside the traditional evaluation processes to create frameworks for developing Big Data analytics to improve traffic incident management.
The objective of this research is to provide guidelines that: (1) describe current and emerging sources of Big Data that could improve traffic incident management; (2) describe potential opportunities to leverage Big Data that could advance traffic incident management state of the practice; (3) identify potential challenges (e.g., security, proprietary, inter-operability issues) for Traffic Incident Management agencies to leverage Big Data; and (4) develop a matrix of Big Data options for Traffic Incident Management agencies to use based on their current capabilities. The research should address a broad range of issues related to Big Data and its use to enhance traffic incident management such as, but not limited to the following:
- An assessment of research, practices, and innovative approaches in the United States and other countries that complement the research objective;
- Data (including non-traditional public and private sources) that are available and the range of costs to access them;
- Relationships that could be identified between the objectives of improved safety, quick clearance, reduced delay, and existing data that would support improved protocols or resources;
- Critical actions, using Big Data analytics, that could result in significant improvements in safety and incident delay;
- Data sharing limitations, regulations, and agreements that need to be addressed to fully realize the potential of Big Data in traffic incident management;
- Big Data uses for identifying and evaluating traffic incident management performance measures, including, but not limited to roadway clearance time, incident clearance time, and secondary crashes; and
- The use of Big Data analytics for predictive traffic incident management.
The NCHRP is seeking the insights of proposers on how best to achieve the research objective. Proposers are expected to describe research plans that can realistically be accomplished within the constraints of available funds and contract time. Proposals must present the proposers' current thinking in sufficient detail to demonstrate their understanding of the issues and the soundness of their approach to meeting the research objective.
A kick-off teleconference of the research team and NCHRP shall be scheduled within 1 month of the contract’s execution. The work plan proposed must be divided into tasks, with each task described in detail. There must be an interim report and a face-to-face meeting scheduled with NCHRP to discuss the interim report. The project schedule shall include 1 month for NCHRP review and approval of the interim report. The final deliverables will include (1) guidelines and appropriate outreach materials that contain: (a) current and emerging sources of Big Data that could improve traffic incident management; (b) potential opportunities to leverage Big Data that could advance traffic incident management state of the practice; (c) potential challenges (e.g., security, proprietary, inter-operability issues) for Traffic Incident Management agencies to leverage Big Data; and (d) a matrix of Big Data options for Traffic Incident Management agencies to use based on their current capabilities; (2) a final report documenting the entire project, incorporating all other specified deliverable products of the research; (3) an executive summary that outlines the research results; (4) recommendations, needs, and priorities for additional related research; and (5) a stand-alone technical memorandum titled “Implementation of Research Findings and Products” (see Special Note C for additional information).