Evaluating Traffic Operation Conditions during Wildfire Evacuation Using Connected Vehicles Data

نویسندگان

چکیده

With climate change and the resulting rise in temperatures, wildfire risk is increasing all over world, particularly Western United States. Communities wildland–urban interface (WUI) areas are at greatest of fire. Such fires cause mass evacuations can result traffic congestion, endangering lives both citizens first responders. While existing evacuation research focuses on social science surveys fire spread modeling, they lack data operations during such incidents. Additionally, traditional collection methods unable to gather large sets historical events. However, recent availability connected vehicle (CV) containing lane-level precision movement has enabled researchers assess operational performance region timeframe interest. To address this gap, study utilized a CV dataset analyze short-notice event caused by wildfire, demonstrating that an effective tool for accurately assessing delays overall operation conditions selected incident. The findings also showed provides high temporal coverage similar travel time estimates as compared alternate method estimation. thus emphasized importance utilizing advanced technologies, data, develop strategies improve emergency management.

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ژورنال

عنوان ژورنال: Fire

سال: 2023

ISSN: ['2571-6255']

DOI: https://doi.org/10.3390/fire6050184