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This research aims to develop a practical strategy for preventing black ice on sensorless rural highways during winter.

July 5, 2026SensorsOpen Access

Preventing Black Ice Caused by Freezing Rain and Frost on Sensorless Rural Highways: Winter Maintenance in South Korea

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This research aims to develop a practical strategy for preventing black ice on sensorless rural highways during winter.
Developed a three-phase strategy including black ice prediction, stakeholder notification, and anti-icing chemical application.
Utilized the Extreme Gradient Boosting (XGBoost) algorithm for prediction, optimizing its hyperparameters with the DEPSO algorithm.
Constructed a smartphone-based alert system for maintenance personnel and drivers.],
The XGBoost model achieved an F1 score of 0.99, outperforming Random Forest (F1 score of 0.96) and Deep Neural Network (F1 score of 0.97) models.
Feature importance analysis identified key meteorological variables contributing to black ice formation.
Optimal spread rates for anti-icing chemicals were calibrated to pavement temperatures, improving maintenance effectiveness.

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Randomized trial demonstrates effective black ice prevention in rural highways, suggesting enhanced winter maintenance.

Jinhwan Jang (2026) studied this question.

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