Application of Big Data Approaches for Traffic Incident Management (2023) / Chapter Skim
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Pages 78-88
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78 This chapter presents guidelines for transportation agencies and TIM programs regarding the development and implementation of TIM big data pipelines. NCHRP Research Report 904 provides a basis for NCHRP Project 03-138; the report presents eight initial guidelines for agencies to explore the application of big data approaches for TIM and to begin positioning themselves for the shift to big data.
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TIM Big Data Guidelines 79 • Data acquisition and quality; • Data environment, platform, and architecture; • Data management; • Data processing, tools, and mining techniques; • Data pipeline development and operations costs; and • Data sharing. Each of the 18 guidelines also includes recommended actions that can be taken to implement the guideline.
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Category Guidelines Implementation Actions Data Acquisition and Quality 1. Collect more data.
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7. Maintain data accessibility.
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Category Guidelines Implementation Actions Data Pipeline Development and Operations Costs 13. Use pay-as-you-go (or payfor-what-you-use)
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TIM Big Data Guidelines 83 – Improve the quality of the data. Focus on controlling and maintaining data quality across every dataset.
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84 Application of Big Data Approaches for Traffic Incident Management 4. Centralize the data in a common storage environment to facilitate the integration of data.
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TIM Big Data Guidelines 85 typing, some data elements are left ignored and others are unavailable in some states. This reduces the usefulness of many data elements when doing cross-state analyses.
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86 Application of Big Data Approaches for Traffic Incident Management – Consider how to integrate CV "driver event" data with "vehicle movement" data. For security purposes, there is no unique identifier available to join the two datasets.
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TIM Big Data Guidelines 87 – Constantly monitor the analytics results, and redesign the system to optimize performance and quality. – Conduct regular reviews of the data pipeline and dashboard tools, and update them with more efficient and effective techniques and tools.
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88 Application of Big Data Approaches for Traffic Incident Management 6.6 Data Sharing Opening and sharing data helps to build a data culture across an organization by increasing transparency and accountability; developing trust, credibility, and reputation; promoting progress and innovation; and encouraging public education and community engagement.
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