MODELING HIGHWAY SAFETY: OPTIMAL DESIGN OF HORIZONTAL CURVES BASED ON MACHINE LEARNING

Authors

DOI:

https://doi.org/10.30888/2709-2267.2025-31-00-022

Keywords:

AI-augmented reliability modeling, horizontal curves, highways, machine learning, design, predictive speed analytic, road traffic, congestion, convolutional neural network (CNN).

Abstract

Highway fatalities on horizontal curves persist due to discrepancies between driver behavior and rigid geometric design standards. This study introduces an artificial intelligence (AI)-augmented reliability framework to quantify safety risks by synthesizi

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Published

2025-05-30

How to Cite

Balashova, Y., & Balashov, A. (2025). MODELING HIGHWAY SAFETY: OPTIMAL DESIGN OF HORIZONTAL CURVES BASED ON MACHINE LEARNING. Sworld-Us Conference Proceedings, 1(usc31-00), 37–41. https://doi.org/10.30888/2709-2267.2025-31-00-022

Issue

No. usc31-00 (2025): Global science and education in the modern realities '2025

Section

Abstracts

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Copyright (c) 2025 Authors

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This work is licensed under a Creative Commons Attribution 4.0 International License.