{"id":377,"date":"2025-03-21T19:49:28","date_gmt":"2025-03-21T19:49:28","guid":{"rendered":"https:\/\/coeng.uaa.alaska.edu\/AI\/?page_id=377"},"modified":"2025-03-24T20:11:55","modified_gmt":"2025-03-24T20:11:55","slug":"raise-enhancing-crash-classification","status":"publish","type":"page","link":"https:\/\/coeng.uaa.alaska.edu\/AI\/raise-enhancing-crash-classification\/","title":{"rendered":"RAISE – Enhancing Crash Classification"},"content":{"rendered":"
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\nUAA College of Engineering\n<\/div>

\nEnhancing Crash Classification through Attention-based Models\n<\/h1>
\nA project led by Masoumeh Heidari Kapourchali\n<\/div>\n<\/div>
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\"UAA<\/div>\n<\/section>
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\nEnhancing Crash Classification through AI: Building Safer Roads for All\n<\/h1>
\nLeveraging Attention-Based Models to Identify Risk Patterns and Improve Transportation Safety\n<\/div>\n<\/div><\/div><\/div>\n<\/section>
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\nFunded by the Pacific Northwest Transportation Consortium (PacTrans), this innovative project harnesses the power of artificial intelligence to revolutionize traffic accident analysis and prevention. By employing advanced machine learning techniques, we analyze critical factors such as vehicle behavior, road conditions, and driver distractions to uncover patterns that contribute to crash risks.

Our approach focuses on developing attention-based models that prioritize key causal factors and their interactions. This enables us to evaluate high-risk scenarios dynamically and with greater accuracy. The insights derived from this analysis are integrated into a dynamic risk map\u2014a powerful tool designed to identify high-risk areas and predict potential accident locations in real-time.

This risk map serves as a resource for drivers, including those with specific needs, and city planners, empowering them to make safer decisions about road use and urban development. By proactively addressing traffic safety challenges, this project aims to enhance mobility and reduce accidents, creating safer transportation networks for everyone.

The project is led by Masoumeh Heidari Kapourchali and represents a significant step forward in using AI for transportation safety.\n<\/div><\/div>\n<\/section>
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\nFrequently Asked Questions\n<\/h1>
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