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Traffic dynamics during the 2019 Kincade wildfire evacuation

Arthur Rohaert, Erica D. Kuligowski, Adam Ardinge, Jonathan Wahlqvist, S. Gwynne, Amanda Kimball, Noureddine Bénichou, Enrico Ronchi

2023Transportation Research Part D Transport and Environment23 citationsDOIOpen Access PDF

Abstract

Traffic models are a useful tool for evacuation planning and management in case of wildfires. Despite the availability of several evacuation models, the number of datasets that can be used for their calibration and validation is limited. This paper presents key traffic flow data collected during the 2019 Kincade Fire. The data (69 116 data points from 24 locations) have been sourced from the Performance Measurement System of the California Department of Transportation. A set of commonly used models that describe the relationships between speed, flow and density has been fit to the data and compared to the model from the Highway Capacity Manual. In evacuation scenarios, the vehicle speed is about 3.5 km/h lower in comparison with the speed in routine scenarios, both for low and high traffic density. This demonstrates that dedicated models are needed for an accurate estimation of traffic evacuation times.

Topics & Concepts

Traffic flow (computer networking)Computer scienceTransport engineeringCalibrationKey (lock)Traffic speedSet (abstract data type)Data setEnvironmental scienceEngineeringStatisticsMathematicsComputer securityProgramming languageArtificial intelligenceEvacuation and Crowd DynamicsFire effects on ecosystemsTraffic and Road Safety
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