Big data is evolving and maturing rapidly, and much attention has been focused on the opportunities that big data may provide state departments of transportation (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 existing or new tools for analysis.
NCHRP Research Report 1071: Application of Big Data Approaches for Traffic Incident Management, from TRB's National Cooperative Highway Research Program, applies the guidelines presented in NCHRP 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.
Supplemental to the report are Appendix A through Appendix P, which detail findings from traditional and big data sources for the TIM use cases; a PowerPoint presentation of the research results; and an Implementation Memo.
National Academies of Sciences, Engineering, and Medicine. 2023. Application of Big Data Approaches for Traffic Incident Management. Washington, DC: The National Academies Press. https://doi.org/10.17226/27300.
|Chapter 1 - Introduction
|Chapter 2 - Gather Information and Data and Define Use Cases
|Chapter 3 - Datasets and Data Quality
|Chapter 4 - TIM Big Data Use Cases
|Chapter 5 - Estimated Costs of Cloud Environments and Data Pipelines
|Chapter 6 - TIM Big Data Guidelines
|Chapter 7 - Conclusions and Recommendations
|References and Bibliography
|Acronyms and Abbreviations
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