Leveraging Artificial Intelligence (AI) Techniques to Detect, Forecast, and Manage Freeway Congestion: Technical Report
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2023-09-01
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Edition:September 2021–August 2023
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Abstract:Enhancing the quality and efficiency of the Texas surface transportation system necessitates reliable predictions about the initiation and dispersion of prolonged congestion, as well as effective tracking of atypical events and their potential evolution. Artificial intelligence (AI) offers a unique avenue for achieving these goals, presenting an opportunity to accurately estimate congestion measures by utilizing data from various sources, including agency-owned sensors, third-party providers, and extensive enterprise databases. The Texas Department of Transportation 0-7131 project aimed to bridge the current research gap through the implementation of two main project phases. The first phase verified the reliability of commercial data sources for transportation planning and operations. The second phase focused on identifying the most effective AI models or algorithms to meet the Agency’s needs based on specific use cases and data availability. Finally, the team developed a prototype decision support tool based on geographical information system technology. The findings provide valuable guidance for decision-makers to prioritize resources, allocate funding, and implement specific measures tailored to the unique characteristics and congestion patterns of different freeway segments.
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