Predictive Analytics for Traffic Management Systems
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2024-04-01
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Edition:Final Report
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Abstract:Traffic management systems (TMSs) help transportation agencies manage roadway capacity as well as traffic demand to deliver safe, reliable, and efficient travel. As agencies look to actively manage their transportation systems, they turn to various analytic techniques—often embedded in decision support methods and tools—that help them better monitor those transportation systems, assess system performance, formulate responses, and implement the responses. This report focuses on predictive analytics, which refers to a class of analytics that develop and apply mathematical models to predict what may happen in the near or long term. The potential for predictive capabilities in traffic management is proven in the context of image and video analyses (e.g., incident detection), and significant research is under way for broader predictive analytics applications. This report explains how predictive analytics may improve the management and operations of TMSs and specific TMS functions, actions, and services. The report also lists issues when agencies are considering different potential paths to integrate prediction into the real-time operation of TMSs.
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