Application of Big Data Approaches for Traffic Incident Management (2023) / Chapter Skim
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1 Advances in the practice of Traffic Incident Management (TIM) continue to improve the safety of responders and the traveling public, the reliability of individual travel and the movement of goods, and the time required to mitigate traffic incidents.
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2 Application of Big Data Approaches for Traffic Incident Management emphasizes that applying the big data approach to TIM will not be a trivial task given the gaps in data, technical, and institutional readiness: • Data readiness. Traffic incidents are infrequent events in the context of big data -- thousands of traffic incident records per year versus "typical" big data records of thousands per minute.
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Introduction 3 • Performing a comprehensive assessment of traditional and big data sources relevant to the use cases, • Establishing big data pipelines for the selected use cases, • Developing case studies to describe each of the big data use cases and pipelines, and • Creating guidelines that expand and refine the guidelines presented in NCHRP Research Report 904. 1.2 Organization of Report The rest of the report is organized as follows: • Chapter 2: Gather Information and Data and Define Use Cases.
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